diff --git "a/y_gee_gee.py" "b/y_gee_gee.py"
new file mode 100644--- /dev/null
+++ "b/y_gee_gee.py"
@@ -0,0 +1,4402 @@
+import ee
+import os
+import pandas as pd
+
+def data_gee():
+    file = (os.path.dirname(os.path.abspath(__file__)) + '/data_gee/gee_catalog.csv')
+    data = pd.read_csv(file)
+    delete = []
+    for i in range(len(data)):
+        d = data['title'].iloc[i]
+        f = d.find('deprecated')
+        if f != -1:
+            delete.append(i)
+            
+    data = data.drop(delete, axis=0).reset_index(drop=True)
+    f = data[['id', 'title']]
+    return(f, data)
+
+def type_map(Map, cod):
+    if cod == 'AAFC/ACI':
+        dataset = ee.ImageCollection('AAFC/ACI')
+        crop2016 = dataset.filter(ee.Filter.date('2016-01-01', '2016-12-31')).first()
+        Map.setCenter(-103.8881, 53.0371, 10)
+        Map.addLayer(crop2016)
+        
+    elif cod == 'ACA/reef_habitat/v2_0':
+        dataset = ee.Image('ACA/reef_habitat/v2_0')
+        reefExtent = dataset.select('reef_mask').selfMask()
+        geomorphicZonation = dataset.select('geomorphic').selfMask()
+        benthicHabitat = dataset.select('benthic').selfMask()
+        Map.setCenter(-149.56194, -17.00872, 13);
+        Map.setOptions('SATELLITE')
+        Map.addLayer(reefExtent, {}, 'Global reef extent')
+        Map.addLayer(geomorphicZonation, {}, 'Geomorphic zonation')
+        Map.addLayer(benthicHabitat, {}, 'Benthic habitat')
+        
+    elif cod == 'AHN/AHN2_05M_INT':
+        dataset = ee.Image('AHN/AHN2_05M_INT')
+        elevation = dataset.select('elevation')
+        elevationVis = {'min': -5.0,'max': 30.0}
+        Map.setCenter(5.76583, 51.855276, 16)
+        Map.addLayer(elevation, elevationVis, 'Elevation')
+        
+    elif cod == 'AHN/AHN2_05M_NON':
+        dataset = ee.Image('AHN/AHN2_05M_NON')
+        elevation = dataset.select('elevation')
+        elevationVis = {
+          'min': -5.0,
+          'max': 30.0
+        }
+        Map.setCenter(5.80258, 51.78547, 14)
+        Map.addLayer(elevation, elevationVis, 'Elevation')
+        
+    elif cod == 'AHN/AHN2_05M_RUW':
+        dataset = ee.Image('AHN/AHN2_05M_RUW')
+        elevation = dataset.select('elevation')
+        elevationVis = {
+          'min': -5.0,
+          'max': 30.0
+        }
+        Map.setCenter(5.76583, 51.855276, 16)
+        Map.addLayer(elevation, elevationVis, 'Elevation')
+        
+    elif cod == 'ASTER/AST_L1T_003':
+        dataset = ee.ImageCollection('ASTER/AST_L1T_003').filter(ee.Filter.date('2018-01-01', '2018-08-15'))
+        falseColor = dataset.select(['B3N', 'B02', 'B01'])
+        falseColorVis = {
+          'min': 0.0,
+          'max': 255.0,
+        }
+        Map.setCenter(-122.0272, 39.6734, 11)
+        Map.addLayer(falseColor.median(), falseColorVis, 'False Color')
+        
+    elif cod == 'AU/GA/AUSTRALIA_5M_DEM':
+        dataset = ee.ImageCollection('AU/GA/AUSTRALIA_5M_DEM')
+        elevation = dataset.select('elevation')
+        elevationVis = {
+          'min': 0.0,
+          'max': 150.0,
+          'palette': ['0000ff', '00ffff', 'ffff00', 'ff0000', 'ffffff']
+        }
+        Map.setCenter(140.1883, -35.9113, 8)
+        Map.addLayer(elevation, elevationVis, 'Elevation')
+        
+    elif cod == 'AU/GA/DEM_1SEC/v10/DEM-H':
+        dataset = ee.Image('AU/GA/DEM_1SEC/v10/DEM-H')
+        elevation = dataset.select('elevation')
+        elevationVis = {
+          'min': -10.0,
+          'max': 1300.0,
+          'palette': [
+            '3ae237', 'b5e22e', 'd6e21f', 'fff705', 'ffd611', 'ffb613', 'ff8b13',
+            'ff6e08', 'ff500d', 'ff0000', 'de0101', 'c21301', '0602ff', '235cb1',
+            '307ef3', '269db1', '30c8e2', '32d3ef', '3be285', '3ff38f', '86e26f'
+          ],
+        }
+        Map.setCenter(133.95, -24.69, 5)
+        Map.addLayer(elevation, elevationVis, 'Elevation')
+        
+    elif cod == 'AU/GA/DEM_1SEC/v10/DEM-S':
+        dataset = ee.Image('AU/GA/DEM_1SEC/v10/DEM-S')
+        elevation = dataset.select('elevation')
+        elevationVis = {
+          'min': -10.0,
+          'max': 1300.0,
+          'palette': [
+            '3ae237', 'b5e22e', 'd6e21f', 'fff705', 'ffd611', 'ffb613', 'ff8b13',
+            'ff6e08', 'ff500d', 'ff0000', 'de0101', 'c21301', '0602ff', '235cb1',
+            '307ef3', '269db1', '30c8e2', '32d3ef', '3be285', '3ff38f', '86e26f'
+          ],
+        }
+        Map.setCenter(133.95, -24.69, 5)
+        Map.addLayer(elevation, elevationVis, 'Elevation')
+        
+    elif cod == 'BIOPAMA/GlobalOilPalm/v1':
+        dataset = ee.ImageCollection('BIOPAMA/GlobalOilPalm/v1')
+        opClass = dataset.select('classification')
+        mosaic = opClass.mosaic()
+        classificationVis = {
+          'min': 1,
+          'max': 3,
+          'palette': ['ff0000','ef00ff', '696969']
+        }
+        mask = mosaic.neq(3)
+        mask = mask.where(mask.eq(0), 0.6)
+
+        Map.addLayer(mosaic.updateMask(mask), classificationVis, 'Oil palm plantation type', True)
+        Map.setCenter(-73.628998,7.320244,8)
+        
+    elif cod == "BLM/AIM/v1/TerrADat/TerrestrialAIM":
+        greens = ee.List(["#00441B", "#00682A", "#37A055", "#5DB96B", "#AEDEA7", "#E7F6E2", "#F7FCF5"])
+        reds = ee.List(["#67000D", "#9E0D14", "#E32F27", "#F6553D", "#FCA082", "#FEE2D5", "#FFF5F0"])
+
+        def normalize(value, min, max):
+            return value.subtract(min).divide(ee.Number(max).subtract(min))
+
+        def setColor(feature, property, min, max, palette):
+            value = normalize(feature.getNumber(property), min, max).multiply(palette.size()).min(palette.size().subtract(1)).max(0)
+            return feature.set({"style": {"color": palette.get(value.int())}})
+
+        fc = ee.FeatureCollection("BLM/AIM/v1/TerrADat/TerrestrialAIM")
+        woodyHeightStyle = lambda f:setColor(f, "WoodyHgt_Avg", 0, 100, greens)
+        bareSoilStyle = lambda f: setColor(f, "BareSoilCover_FH", 0, 100, reds)
+
+        treeHeight = fc.filter("WoodyHgt_Avg > 1").map(woodyHeightStyle)
+        bareSoil = fc.filter("BareSoilCover_FH > 1").map(bareSoilStyle)
+        Map.addLayer(bareSoil.style({"styleProperty": "style", "pointSize": 3}))
+        Map.addLayer(treeHeight.style({"styleProperty": "style", "pointSize": 1}))
+        Map.setCenter(-110, 40, 6)
+
+    elif cod == "BNU/FGS/CCNL/v1":
+        dataset = ee.ImageCollection("BNU/FGS/CCNL/v1").filter(ee.Filter.date("2010-01-01", "2010-12-31"))
+        nighttimeLights = dataset.select("b1")
+        nighttimeLightsVis = {
+            "min": 3.0,
+            "max": 60.0,
+        }
+        Map.setCenter(31.4, 30, 6)
+        Map.addLayer(nighttimeLights, nighttimeLightsVis, "Nighttime Lights")
+
+    elif cod == "CAS/IGSNRR/PML/V2_v017":
+        dataset = ee.ImageCollection("CAS/IGSNRR/PML/V2_v017")
+        visualization = {
+            'bands': ["GPP"],
+            "min": 0.0,
+            "max": 9.0,
+            "palette": ["a50026", "d73027", "f46d43", "fdae61", "fee08b", "ffffbf",
+                  "d9ef8b", "a6d96a", "66bd63", "1a9850", "006837"]}
+        Map.setCenter(0.0, 15.0, 2)
+        Map.addLayer(dataset, visualization, "PML_V2 0.1.7 Gross Primary Product (GPP)")
+
+    elif cod == "CGIAR/SRTM90_V4":
+        dataset = ee.Image("CGIAR/SRTM90_V4")
+        elevation = dataset.select("elevation")
+        slope = ee.Terrain.slope(elevation)
+        Map.setCenter(-112.8598, 36.2841, 10)
+        Map.addLayer(slope, {"min": 0, "max": 60}, "slope")
+
+    elif cod == "CIESIN/GPWv411/GPW_Basic_Demographic_Characteristics":
+        dataset = ee.ImageCollection("CIESIN/GPWv411/GPW_Basic_Demographic_Characteristics").first()
+        raster = dataset.select("basic_demographic_characteristics")
+        raster_vis = {
+            "max": 1000.0,
+            "palette": ["ffffe7","86a192","509791","307296","2c4484","000066"],
+            "min": 0.0
+        }
+        Map.setCenter(79.1, 19.81, 3)
+        Map.addLayer(raster, raster_vis, "basic_demographic_characteristics")
+
+    elif cod == "CIESIN/GPWv411/GPW_Data_Context":
+        dataset = ee.Image("CIESIN/GPWv411/GPW_Data_Context")
+        raster = dataset.select("data_context")
+        raster_vis = {
+            "min": 200.0,
+            "palette": ["ffffff","099506","f04923","e62440","706984","a5a5a5","ffe152","d4cc11","000000"],
+            "max": 207.0
+        }
+        Map.setCenter(-88.6, 26.4, 1)
+        Map.addLayer(raster, raster_vis, "data_context")
+
+    elif cod == "CIESIN/GPWv411/GPW_Land_Area":
+        dataset = ee.Image("CIESIN/GPWv411/GPW_Land_Area")
+        raster = dataset.select("land_area")
+        raster_vis = {
+            "min": 0.0,
+            "palette": ["ecefb7","745638"],
+            "max": 0.86
+        }
+        Map.setCenter(26.4, 19.81, 1)
+        Map.addLayer(raster, raster_vis, "land_area")
+
+    elif cod == "CIESIN/GPWv411/GPW_Mean_Administrative_Unit_Area":
+        dataset = ee.Image("CIESIN/GPWv411/GPW_Mean_Administrative_Unit_Area")
+        raster = dataset.select("mean_administrative_unit_area")
+        raster_vis = {
+            "min": 0.0,
+            "palette": ["ffffff","747474","656565","3c3c3c","2f2f2f","000000"],
+            "max": 40000.0
+        }
+        Map.setCenter(-88.6, 26.4, 1)
+        Map.addLayer(raster, raster_vis, "mean_administrative_unit_area")
+
+    elif cod == "CIESIN/GPWv411/GPW_National_Identifier_Grid":
+        dataset = ee.Image("CIESIN/GPWv411/GPW_National_Identifier_Grid")
+        raster = dataset.select("national_identifier_grid")
+        raster_vis = {
+        "min": 4.0,
+        "palette": ["000000","ffffff"],
+        "max": 999.0
+        }
+        Map.setCenter(-88.6, 26.4, 1)
+        Map.addLayer(raster, raster_vis, "national_identifier_grid")
+        
+    elif cod == "CIESIN/GPWv411/GPW_Population_Count":
+        dataset = ee.ImageCollection("CIESIN/GPWv411/GPW_Population_Count").first()
+        raster = dataset.select("population_count")
+        raster_vis = {
+        "max": 1000.0, 
+        "palette": ["ffffe7","86a192","509791","307296","2c4484","000066"],
+        "min": 0.0}
+        Map.setCenter(79.1, 19.81, 3)
+        Map.addLayer(raster, raster_vis, "population_count")
+        
+    elif cod == "CIESIN/GPWv411/GPW_Population_Density":
+        dataset = ee.ImageCollection("CIESIN/GPWv411/GPW_Population_Density").first()
+        raster = dataset.select("population_density")
+        raster_vis = {
+            "max": 1000.0,
+            "palette": ["ffffe7","FFc869","ffac1d","e17735","f2552c","9f0c21"],
+            "min": 200.0
+        }
+        Map.setCenter(79.1, 19.81, 3)
+        Map.addLayer(raster, raster_vis, "population_density")
+
+    elif cod == "CIESIN/GPWv411/GPW_UNWPP-Adjusted_Population_Count":
+        dataset = ee.ImageCollection("CIESIN/GPWv411/GPW_UNWPP-Adjusted_Population_Count").first()
+        raster = dataset.select("unwpp-adjusted_population_count")
+        raster_vis = {"max": 1000.0, "palette": ["ffffe7","86a192","509791","307296","2c4484","000066"], "min": 0.0}
+        Map.setCenter(79.1, 19.81, 3)
+        Map.addLayer(raster, raster_vis, "unwpp-adjusted_population_count")
+
+    elif cod == "CIESIN/GPWv411/GPW_UNWPP-Adjusted_Population_Density":
+        dataset = ee.ImageCollection("CIESIN/GPWv411/GPW_UNWPP-Adjusted_Population_Density").first()
+        raster = dataset.select("unwpp-adjusted_population_density")
+        raster_vis = {"max": 1000.0, "palette": ["ffffe7","FFc869","ffac1d","e17735","f2552c","9f0c21"], "min": 0.0}
+        Map.setCenter(79.1, 19.81, 3)
+        Map.addLayer(raster, raster_vis, "unwpp-adjusted_population_density")
+
+    elif cod == "CIESIN/GPWv411/GPW_Water_Area":
+        dataset = ee.Image("CIESIN/GPWv411/GPW_Water_Area")
+        raster = dataset.select("water_area")
+        raster_vis = {
+            "min": 0.0,
+            "palette": ["f5f6da","180d02"],
+            "max": 0.860558}
+        Map.setCenter(79.1, 19.81, 3)
+        Map.addLayer(raster, raster_vis, "water_area")
+
+    elif cod == "CIESIN/GPWv411/GPW_Water_Mask":
+        dataset = ee.Image("CIESIN/GPWv411/GPW_Water_Mask")
+        raster = dataset.select("water_mask")
+        raster_vis = {
+        "min": 0.0,
+        "palette": ["005ce6","00ffc5","bed2ff","aed0f1"],
+        "max": 3.0
+        }
+        Map.setCenter(-88.6, 26.4, 1)
+        Map.addLayer(raster, raster_vis, "water_mask")
+
+    elif cod == "COPERNICUS/CORINE/V20/100m/2012":
+        dataset = ee.Image("COPERNICUS/CORINE/V20/100m/2012")
+        landCover = dataset.select("landcover")
+        Map.setCenter(16.436, 39.825, 6)
+        Map.addLayer(landCover, {}, "Land Cover")
+
+
+    elif cod == "COPERNICUS/DEM/GLO30":
+        dataset = ee.ImageCollection("COPERNICUS/DEM/GLO30")
+        elevation = dataset.select("DEM")
+        elevationVis = {
+        "min": 0.0,
+        "max": 1000.0,
+        'palette': ["0000ff","00ffff","ffff00","ff0000","ffffff"],
+        }
+        Map.setCenter(-73.388672,5.353521, 4)
+        Map.addLayer(elevation, elevationVis, "DEM")
+
+    elif cod == "COPERNICUS/Landcover/100m/Proba-V-C3/Global": 
+        dataset = ee.Image("COPERNICUS/Landcover/100m/Proba-V-C3/Global/2019").select("discrete_classification")
+        Map.setCenter(-88.6, 26.4, 1)
+        Map.addLayer(dataset, {}, "Land Cover")
+
+    elif cod == "COPERNICUS/S1_GRD":
+        def ff(image):
+            edge = image.lt(-30.0)
+            maskedImage = image.mask()
+            maskedImage = maskedImage.And(edge.Not())
+            return image.updateMask(maskedImage)
+        
+        imgVV = ee.ImageCollection("COPERNICUS/S1_GRD") \
+        .filter(ee.Filter.listContains("transmitterReceiverPolarisation", "VV")) \
+        .filter(ee.Filter.eq("instrumentMode", "IW")) \
+        .select("VV") \
+        .map(lambda x:ff(x))
+        
+        desc = imgVV.filter(ee.Filter.eq("orbitProperties_pass", "DESCENDING"))
+        asc = imgVV.filter(ee.Filter.eq("orbitProperties_pass", "ASCENDING"))
+    
+        spring = ee.Filter.date("2015-03-01", "2015-04-20")
+        lateSpring = ee.Filter.date("2015-04-21", "2015-06-10")
+        summer = ee.Filter.date("2015-06-11", "2015-08-31")
+
+        descChange = ee.Image.cat(desc.filter(spring).mean(),desc.filter(lateSpring).mean(),desc.filter(summer).mean())
+        ascChange = ee.Image.cat(asc.filter(spring).mean(),asc.filter(lateSpring).mean(),asc.filter(summer).mean())
+        Map.setCenter(-73.388672,5.353521, 6)
+        Map.addLayer(ascChange, {"min": -25, "max": 5}, "Multi-T Mean ASC", True)
+        Map.addLayer(descChange, {"min": -25, "max": 5}, "Multi-T Mean DESC", True)
+
+    elif cod == "COPERNICUS/S2":
+        def maskS2clouds(image):
+            qa = image.select("QA60")
+            cloudBitMask = 1 << 10
+            cirrusBitMask = 1 << 11
+            mask = qa.bitwiseAnd(cloudBitMask).eq(0).And(qa.bitwiseAnd(cirrusBitMask).eq(0))
+            return image.updateMask(mask).divide(10000)
+        
+        dataset = ee.ImageCollection("COPERNICUS/S2").filterDate("2018-01-01", "2018-01-31").filter(ee.Filter.lt("CLOUDY_PIXEL_PERCENTAGE", 20)).map(maskS2clouds)
+        rgbVis = {"min": 0.0, "max": 0.3,"bands": ["B4", "B3", "B2"]
+                 }
+        Map.setCenter(-73.388672,5.353521, 6)
+        Map.addLayer(dataset.median(), rgbVis, "RGB")
+        
+    elif cod == "COPERNICUS/S2_CLOUD_PROBABILITY":
+        s2Sr = ee.ImageCollection("COPERNICUS/S2_SR")
+        s2Clouds = ee.ImageCollection("COPERNICUS/S2_CLOUD_PROBABILITY")
+        START_DATE = ee.Date("2019-01-01")
+        END_DATE = ee.Date("2019-03-01")
+        MAX_CLOUD_PROBABILITY = 65
+        region = ee.Geometry.Rectangle([[-76.5, 2.0], [-74, 4.0]])
+        Map.setCenter(-75, 3, 12)
+        
+        def maskClouds(img):
+            clouds = ee.Image(img.get("cloud_mask")).select("probability")
+            isNotCloud = clouds.lt(MAX_CLOUD_PROBABILITY)
+            return img.updateMask(isNotCloud)
+
+        def maskEdges(s2_img):
+            return s2_img.updateMask(s2_img.select("B8A").mask().updateMask(s2_img.select("B9").mask()))
+    
+        criteria = ee.Filter.And(ee.Filter.bounds(region), ee.Filter.date(START_DATE, END_DATE))
+        s2Sr = s2Sr.filter(criteria).map(maskEdges)
+        s2Clouds = s2Clouds.filter(criteria)
+        
+        s2SrWithCloudMask = ee.Join.saveFirst("cloud_mask").apply({
+            'primary': s2Sr,
+            'secondary': s2Clouds,
+            'condition': ee.Filter.equals(leftField= "system:index", rightField= "system:index")
+        })
+        
+        s2CloudMasked = ee.ImageCollection(s2SrWithCloudMask).map(maskClouds).median()
+        rgbVis = {"min": 0, "max": 3000, "bands": ["B4", "B3", "B2"]}
+        
+        Map.addLayer(s2CloudMasked, rgbVis, "S2 SR masked at " + MAX_CLOUD_PROBABILITY + "%", True)
+
+    elif cod == "COPERNICUS/S2_HARMONIZED":
+        def maskS2clouds(image):
+            qa = image.select("QA60")
+            cloudBitMask = 1 << 10
+            cirrusBitMask = 1 << 11
+            mask = qa.bitwiseAnd(cloudBitMask).eq(0).And(qa.bitwiseAnd(cirrusBitMask).eq(0))
+            return image.updateMask(mask).divide(10000)
+
+        dataset = ee.ImageCollection("COPERNICUS/S2_HARMONIZED") \
+        .filterDate("2022-01-01", "2022-01-31") \
+        .filter(ee.Filter.lt("CLOUDY_PIXEL_PERCENTAGE", 20)) \
+        .map(maskS2clouds)
+        rgbVis = {
+            "min": 0.0,
+            "max": 0.3,
+            "bands": ["B4", "B3", "B2"],
+        }
+
+        Map.setCenter(-73.388672,5.353521, 6)
+        Map.addLayer(dataset.median(), rgbVis, "RGB")
+
+    elif cod == "COPERNICUS/S2_SR":
+        def maskS2clouds(image):
+            qa = image.select("QA60")
+            cloudBitMask = 1 << 10
+            cirrusBitMask = 1 << 11
+            mask = qa.bitwiseAnd(cloudBitMask).eq(0).And(qa.bitwiseAnd(cirrusBitMask).eq(0))
+            return image.updateMask(mask).divide(10000)
+        dataset = ee.ImageCollection("COPERNICUS/S2_SR") \
+        .filterDate("2020-01-01", "2020-01-30") \
+        .filter(ee.Filter.lt("CLOUDY_PIXEL_PERCENTAGE",20)) \
+        .map(maskS2clouds)
+        visualization = {
+            "min": 0.0,
+            "max": 0.3,
+            'bands': ["B4", "B3", "B2"],
+        }
+        Map.setCenter(83.277, 17.7009, 12)
+        Map.addLayer(dataset.mean(), visualization, "RGB")
+    
+
+    elif cod == "COPERNICUS/S2_SR_HARMONIZED":
+        def maskS2clouds(image):
+            qa = image.select("QA60")
+            cloudBitMask = 1 << 10
+            cirrusBitMask = 1 << 11
+            mask = qa.bitwiseAnd(cloudBitMask).eq(0).And(qa.bitwiseAnd(cirrusBitMask).eq(0))
+            return image.updateMask(mask).divide(10000)
+        dataset = ee.ImageCollection("COPERNICUS/S2_SR_HARMONIZED") \
+        .filterDate("2020-01-01", "2020-01-30") \
+        .filter(ee.Filter.lt("CLOUDY_PIXEL_PERCENTAGE",20)) \
+        .map(maskS2clouds)
+        visualization = {
+          "min": 0.0,
+          "max": 0.3,
+          "bands": ["B4", "B3", "B2"],
+        }
+        Map.setCenter(83.277, 17.7009, 12)
+        Map.addLayer(dataset.mean(), visualization, "RGB")
+
+    elif cod == "COPERNICUS/S3/OLCI":
+        dataset = ee.ImageCollection("COPERNICUS/S3/OLCI") \
+        .filterDate("2018-04-01", "2018-04-04")
+        rgb = dataset.select(["Oa08_radiance", "Oa06_radiance", "Oa04_radiance"]) \
+        .median().multiply(ee.Image([0.00876539, 0.0123538, 0.0115198]))
+        visParams = {"min": 0, "max": 6, "gamma": 1.5,}
+        Map.setCenter(46.043, 1.45, 5)
+        Map.addLayer(rgb, visParams, "RGB")
+
+    elif cod == "COPERNICUS/S5P/NRTI/L3_AER_AI":
+        collection = ee.ImageCollection("COPERNICUS/S5P/NRTI/L3_AER_AI") \
+        .select("absorbing_aerosol_index") \
+        .filterDate("2019-06-01", "2019-06-06")
+        band_viz = {
+          "min": -1,
+          "max": 2.0,
+          "palette": ["black", "blue", "purple", "cyan", "green", "yellow", "red"]
+          }
+        Map.addLayer(collection.mean(), band_viz, "S5P Aerosol")
+        Map.setCenter(-118.82, 36.1, 5)
+
+    elif cod == "COPERNICUS/S5P/NRTI/L3_AER_LH":
+        collection = ee.ImageCollection("COPERNICUS/S5P/NRTI/L3_AER_LH") \
+        .select("aerosol_height") \
+        .filterDate("2019-06-01", "2019-06-06")
+        band_viz = {
+          "min": -81.17,
+          "max": 67622.56,
+          "palette": ["blue", "purple", "cyan", "green", "yellow", "red"]
+          }
+        Map.addLayer(collection.mean(), band_viz, "S5P Aerosol Height")
+        Map.setCenter(44.09, 24.27, 4)
+
+    elif cod == "COPERNICUS/S5P/NRTI/L3_CLOUD":
+        collection = ee.ImageCollection("COPERNICUS/S5P/NRTI/L3_CLOUD") \
+        .select("cloud_fraction") \
+        .filterDate("2019-06-01", "2019-06-02")
+        band_viz = {
+          "min": 0,
+          "max": 0.95,
+          "palette": ["black", "blue", "purple", "cyan", "green", "yellow", "red"]
+          }
+        Map.addLayer(collection.mean(), band_viz, "S5P Cloud")
+        Map.setCenter(-58.14, -10.47, 2)
+
+    elif cod == "COPERNICUS/S5P/NRTI/L3_CO":
+        collection = ee.ImageCollection("COPERNICUS/S5P/NRTI/L3_CO") \
+        .select("CO_column_number_density") \
+        .filterDate("2019-06-01", "2019-06-11")
+        band_viz = {
+          "min": 0,
+          "max": 0.05,
+          "palette": ["black", "blue", "purple", "cyan", "green", "yellow", "red"]
+          }
+        Map.addLayer(collection.mean(), band_viz, "S5P CO")
+        Map.setCenter(-25.01, -4.28, 4)
+
+    elif cod == "COPERNICUS/S5P/NRTI/L3_HCHO":
+        collection = ee.ImageCollection("COPERNICUS/S5P/NRTI/L3_HCHO") \
+        .select("tropospheric_HCHO_column_number_density") \
+        .filterDate("2019-06-01", "2019-06-06")
+        band_viz = {
+          "min": 0.0,
+          "max": 0.0003,
+          "palette": ["black", "blue", "purple", "cyan", "green", "yellow", "red"]
+        }
+        Map.addLayer(collection.mean(), band_viz, "S5P HCHO")
+        Map.setCenter(0.0, 0.0, 2)
+
+    elif cod == "COPERNICUS/S5P/NRTI/L3_NO2":
+        collection = ee.ImageCollection("COPERNICUS/S5P/NRTI/L3_NO2") \
+        .select("NO2_column_number_density") \
+        .filterDate("2019-06-01", "2019-06-06")
+        band_viz = {
+          "min": 0,
+          "max": 0.0002,
+          "palette": ["black", "blue", "purple", "cyan", "green", "yellow", "red"]
+        }
+        Map.addLayer(collection.mean(), band_viz, "S5P N02")
+        Map.setCenter(65.27, 24.11, 4)
+
+    elif cod == "COPERNICUS/S5P/NRTI/L3_O3":
+        collection = ee.ImageCollection("COPERNICUS/S5P/NRTI/L3_O3") \
+        .select("O3_column_number_density") \
+        .filterDate("2019-06-01", "2019-06-05")
+        band_viz = {
+          "min": 0.12,
+          "max": 0.15,
+          "palette": ["black", "blue", "purple", "cyan", "green", "yellow", "red"]
+        }
+        Map.addLayer(collection.mean(), band_viz, "S5P O3")
+        Map.setCenter(0.0, 0.0, 2)
+
+    elif cod == "COPERNICUS/S5P/NRTI/L3_SO2":
+        collection = ee.ImageCollection("COPERNICUS/S5P/NRTI/L3_SO2") \
+        .select("SO2_column_number_density") \
+        .filterDate("2019-06-01", "2019-06-11")
+        band_viz = {
+          "min": 0.0,
+          "max": 0.0005,
+          "palette": ["black", "blue", "purple", "cyan", "green", "yellow", "red"]
+        }
+        Map.addLayer(collection.mean(), band_viz, "S5P SO2")
+        Map.setCenter(0.0, 0.0, 2)
+
+    elif cod == "COPERNICUS/S5P/OFFL/L3_AER_AI":
+        collection = ee.ImageCollection("COPERNICUS/S5P/OFFL/L3_AER_AI") \
+        .select("absorbing_aerosol_index") \
+        .filterDate("2019-06-01", "2019-06-06")
+        band_viz = {
+          "min": -1,
+          "max": 2.0,
+          "palette": ["black", "blue", "purple", "cyan", "green", "yellow", "red"]
+        }
+        Map.addLayer(collection.mean(), band_viz, "S5P Aerosol")
+        Map.setCenter(-118.82, 36.1, 5)
+
+    elif cod == "COPERNICUS/S5P/OFFL/L3_AER_LH":
+        collection = ee.ImageCollection("COPERNICUS/S5P/OFFL/L3_AER_LH") \
+        .select("aerosol_height") \
+        .filterDate("2019-06-01", "2019-06-05")
+        visualization = {
+          "min": 0,
+          "max": 6000,
+          "palette": ["blue", "purple", "cyan", "green", "yellow", "red"]
+        }
+        Map.setCenter(44.09, 24.27, 4)
+        Map.addLayer(collection.mean(), visualization, "S5P Aerosol Height")
+    
+    elif cod == "COPERNICUS/S5P/OFFL/L3_CH4":
+        collection = ee.ImageCollection("COPERNICUS/S5P/OFFL/L3_CH4") \
+        .select("CH4_column_volume_mixing_ratio_dry_air") \
+        .filterDate("2019-06-01", "2019-07-16")
+        band_viz = {
+          "min": 1750,
+          "max": 1900,
+          "palette": ["black", "blue", "purple", "cyan", "green", "yellow", "red"]
+        }
+        Map.addLayer(collection.mean(), band_viz, "S5P CH4")
+        Map.setCenter(0.0, 0.0, 2)
+
+    elif cod == "COPERNICUS/S5P/OFFL/L3_CLOUD":
+        collection = ee.ImageCollection("COPERNICUS/S5P/OFFL/L3_CLOUD") \
+        .select("cloud_fraction") \
+        .filterDate("2019-06-01", "2019-06-02")
+        band_viz = {
+          "min": 0,
+          "max": 0.95,
+          "palette": ["black", "blue", "purple", "cyan", "green", "yellow", "red"]
+        }
+        Map.addLayer(collection.mean(), band_viz, "S5P Cloud")
+        Map.setCenter(-58.14, -10.47, 2)
+
+    elif cod == "COPERNICUS/S5P/OFFL/L3_CO":
+        collection = ee.ImageCollection("COPERNICUS/S5P/OFFL/L3_CO") \
+        .select("CO_column_number_density") \
+        .filterDate("2019-06-01", "2019-06-11")
+        band_viz = {
+          "min": 0,
+          "max": 0.05,
+          "palette": ["black", "blue", "purple", "cyan", "green", "yellow", "red"]
+        }
+        Map.addLayer(collection.mean(), band_viz, "S5P CO")
+        Map.setCenter(-25.01, -4.28, 4)
+
+    elif cod == "COPERNICUS/S5P/OFFL/L3_HCHO":
+        collection = ee.ImageCollection("COPERNICUS/S5P/OFFL/L3_HCHO") \
+        .select("tropospheric_HCHO_column_number_density") \
+        .filterDate("2019-06-01", "2019-06-06")
+        band_viz = {
+          "min": 0.0,
+          "max": 0.0003,
+          "palette": ["black", "blue", "purple", "cyan", "green", "yellow", "red"]
+        }
+        Map.addLayer(collection.mean(), band_viz, "S5P HCHO")
+        Map.setCenter(0.0, 0.0, 2)
+
+    elif cod == "COPERNICUS/S5P/OFFL/L3_NO2":
+        collection = ee.ImageCollection("COPERNICUS/S5P/OFFL/L3_NO2") \
+        .select("tropospheric_NO2_column_number_density") \
+        .filterDate("2019-06-01", "2019-06-06")
+        band_viz = {
+          "min": 0,
+          "max": 0.0002,
+          "palette": ["black", "blue", "purple", "cyan", "green", "yellow", "red"]
+        }
+        Map.addLayer(collection.mean(), band_viz, "S5P N02")
+        Map.setCenter(65.27, 24.11, 4)
+
+    elif cod == "COPERNICUS/S5P/OFFL/L3_O3":
+        collection = ee.ImageCollection("COPERNICUS/S5P/OFFL/L3_O3") \
+        .select("O3_column_number_density") \
+        .filterDate("2019-06-01", "2019-06-05")
+        band_viz = {
+          "min": 0.12,
+          "max": 0.15,
+          "palette": ["black", "blue", "purple", "cyan", "green", "yellow", "red"]
+        }
+        Map.addLayer(collection.mean(), band_viz, "S5P O3")
+        Map.setCenter(0.0, 0.0, 2)
+
+    elif cod == "COPERNICUS/S5P/OFFL/L3_O3_TCL":
+        collection = ee.ImageCollection("COPERNICUS/S5P/OFFL/L3_O3_TCL") \
+        .select("ozone_tropospheric_vertical_column") \
+        .filterDate("2019-06-01", "2019-07-01")
+        band_viz = {
+          "min": 0,
+          "max": 0.02,
+          "palette": ["black", "blue", "purple", "cyan", "green", "yellow", "red"]
+        }
+        Map.addLayer(collection.mean(), band_viz, "S5P O3")
+        Map.setCenter(0.0, 0.0, 2)
+
+    elif cod == "COPERNICUS/S5P/OFFL/L3_SO2":
+        collection = ee.ImageCollection("COPERNICUS/S5P/OFFL/L3_SO2") \
+        .select("SO2_column_number_density") \
+        .filterDate("2019-06-01", "2019-06-11")
+        band_viz = {
+          "min": 0.0,
+          "max": 0.0005,
+          "palette": ["black", "blue", "purple", "cyan", "green", "yellow", "red"]
+        }
+        Map.addLayer(collection.mean(), band_viz, "S5P SO2")
+        Map.setCenter(0.0, 0.0, 2)
+
+    elif cod == "CPOM/CryoSat2/ANTARCTICA_DEM":
+        dataset = ee.Image("CPOM/CryoSat2/ANTARCTICA_DEM")
+        visualization = {
+          "bands": ["elevation"],
+          "min": 0.0,
+          "max": 4000.0,
+          "palette": ["001fff", "00ffff", "fbff00", "ff0000"]
+        }
+        Map.setCenter(17.0, -76.0, 3)
+        Map.addLayer(dataset, visualization, "Elevation")
+
+    elif cod == "CSIRO/SLGA":
+        dataset = ee.ImageCollection("CSIRO/SLGA") \
+        .filter(ee.Filter.eq("attribute_code", "DES"))
+        soilDepth = dataset.select("DES_000_200_EV")
+        soilDepthVis = {
+          "min": 0.1,
+          "max": 1.84,
+          "palette": ["8d6738", "252525"],
+        }
+        Map.setCenter(132.495, -21.984, 5)
+        Map.addLayer(soilDepth, soilDepthVis, "Soil Depth")
+
+    elif cod == "CSP/ERGo/1_0/Global/ALOS_CHILI":
+        dataset = ee.Image("CSP/ERGo/1_0/Global/ALOS_CHILI")
+        alosChili = dataset.select("constant")
+        alosChiliVis = {
+            "min": 0.0,
+            "max": 255.0,
+        }
+        Map.setCenter(-105.8636, 40.3439, 11)
+        Map.addLayer(alosChili, alosChiliVis, "ALOS CHILI")
+        
+    elif cod == "CSP/ERGo/1_0/Global/ALOS_landforms":
+        dataset = ee.Image("CSP/ERGo/1_0/Global/ALOS_landforms")
+        landforms = dataset.select("constant")
+        landformsVis = {
+            "min": 11.0,
+            "max": 42.0,
+            "palette": [
+            "141414", "383838", "808080", "EBEB8F", "F7D311", "AA0000", "D89382",
+            "DDC9C9", "DCCDCE", "1C6330", "68AA63", "B5C98E", "E1F0E5", "a975ba",
+            "6f198c"
+            ],
+        }
+        Map.setCenter(-105.58, 40.5498, 11)
+        Map.addLayer(landforms, landformsVis, "Landforms")
+
+    elif cod == "CSP/ERGo/1_0/Global/ALOS_mTPI":
+        dataset = ee.Image("CSP/ERGo/1_0/Global/ALOS_mTPI")
+        alosMtpi = dataset.select("AVE")
+        alosMtpiVis = {
+            "min": -200.0,
+            "max": 200.0,
+            "palette": ["0b1eff", "4be450", "fffca4", "ffa011", "ff0000"],
+        }
+        Map.setCenter(-105.8636, 40.3439, 11)
+        Map.addLayer(alosMtpi, alosMtpiVis, "ALOS mTPI")
+
+    elif cod == "CSP/ERGo/1_0/Global/ALOS_topoDiversity":
+        dataset = ee.Image("CSP/ERGo/1_0/Global/ALOS_topoDiversity")
+        alosTopographicDiversity = dataset.select("constant")
+        alosTopographicDiversityVis = {
+            "min": 0.0,
+            "max": 1.0,
+        }
+        Map.setCenter(-111.313, 39.724, 6)
+        Map.addLayer(alosTopographicDiversity, alosTopographicDiversityVis, "ALOS Topographic Diversity")
+            
+    elif cod == "CSP/ERGo/1_0/Global/SRTM_CHILI":
+        dataset = ee.Image("CSP/ERGo/1_0/Global/SRTM_CHILI")
+        srtmChili = dataset.select("constant")
+        srtmChiliVis = {
+            "min": 0.0,
+            "max": 255.0,
+        }
+        Map.setCenter(-105.8636, 40.3439, 11)
+        Map.addLayer(srtmChili, srtmChiliVis, "SRTM CHILI")
+        
+    elif cod == "CSP/ERGo/1_0/Global/SRTM_landforms":
+        dataset = ee.Image("CSP/ERGo/1_0/Global/SRTM_landforms")
+        landforms = dataset.select("constant")
+        landformsVis = {
+            "min": 11.0,
+            "max": 42.0,
+            "palette": [
+            "141414", "383838", "808080", "EBEB8F", "F7D311", "AA0000", "D89382",
+            "DDC9C9", "DCCDCE", "1C6330", "68AA63", "B5C98E", "E1F0E5", "a975ba",
+            "6f198c"
+            ],
+        }
+        Map.setCenter(-105.58, 40.5498, 11)
+        Map.addLayer(landforms, landformsVis, "Landforms")
+
+    elif cod == "CSP/ERGo/1_0/Global/SRTM_mTPI":
+        dataset = ee.Image("CSP/ERGo/1_0/Global/SRTM_mTPI")
+        srtmMtpi = dataset.select("elevation")
+        srtmMtpiVis = {
+            "min": -200.0,
+            "max": 200.0,
+            "palette": ["0b1eff", "4be450", "fffca4", "ffa011", "ff0000"],
+        }
+        Map.setCenter(-105.8636, 40.3439, 11)
+        Map.addLayer(srtmMtpi, srtmMtpiVis, "SRTM mTPI")
+
+    elif cod == "CSP/ERGo/1_0/Global/SRTM_topoDiversity":
+        dataset = ee.Image("CSP/ERGo/1_0/Global/SRTM_topoDiversity")
+        srtmTopographicDiversity = dataset.select("constant")
+        srtmTopographicDiversityVis = {
+            "min": 0.0,
+            "max": 1.0,
+        }
+        Map.setCenter(-111.313, 39.724, 6)
+        Map.addLayer(srtmTopographicDiversity, srtmTopographicDiversityVis,"SRTM Topographic Diversity")
+
+    elif cod == "CSP/ERGo/1_0/US/CHILI":
+        dataset = ee.Image("CSP/ERGo/1_0/US/CHILI")
+        usChili = dataset.select("constant")
+        usChiliVis = {
+            "min": 0.0,
+            "max": 255.0,
+        }
+        Map.setCenter(-105.8636, 40.3439, 11)
+        Map.addLayer(usChili, usChiliVis, "US CHILI")
+
+    elif cod == "CSP/ERGo/1_0/US/landforms":
+        dataset = ee.Image("CSP/ERGo/1_0/US/landforms")
+        landforms = dataset.select("constant")
+        landformsVis = {
+            "min": 11.0,
+            "max": 42.0,
+            "palette": [
+            "141414", "383838", "808080", "EBEB8F", "F7D311", "AA0000", "D89382",
+            "DDC9C9", "DCCDCE", "1C6330", "68AA63", "B5C98E", "E1F0E5", "a975ba",
+            "6f198c"
+            ],
+        }
+        Map.setCenter(-105.58, 40.5498, 11)
+        Map.addLayer(landforms, landformsVis, "Landforms")
+
+    elif cod == "CSP/ERGo/1_0/US/lithology":
+        dataset = ee.Image("CSP/ERGo/1_0/US/lithology")
+        lithology = dataset.select("b1")
+        lithologyVis = {
+            "min": 0.0,
+            "max": 20.0,
+            "palette": [
+            "356EFF", "ACB6DA", "D6B879", "313131", "EDA800", "616161", "D6D6D6",
+            "D0DDAE", "B8D279", "D5D378", "141414", "6DB155", "9B6D55", "FEEEC9",
+            "D6B879", "00B7EC", "FFDA90", "F8B28C"
+            ],
+        }
+        Map.setCenter(-105.8636, 40.3439, 11)
+        Map.addLayer(lithology, lithologyVis, "Lithology")
+
+    elif cod == "CSP/ERGo/1_0/US/mTPI":
+        dataset = ee.Image("CSP/ERGo/1_0/US/mTPI") 
+        usMtpi = dataset.select("elevation")
+        usMtpiVis = {
+            "min": -200.0,
+            "max": 200.0,
+            "palette": ["0b1eff", "4be450", "fffca4", "ffa011", "ff0000"],
+        }
+        Map.setCenter(-105.8636, 40.3439, 11)
+        Map.addLayer(usMtpi, usMtpiVis, "US mTPI")
+
+    elif cod == "CSP/ERGo/1_0/US/physioDiversity":
+        dataset = ee.Image("CSP/ERGo/1_0/US/physioDiversity")
+        physiographicDiversity = dataset.select("b1")
+        physiographicDiversityVis = {
+            "min": 0.0,
+            "max": 1.0,
+        }
+        Map.setCenter(-94.625, 39.825, 7)
+        Map.addLayer(physiographicDiversity, physiographicDiversityVis,"Physiographic Diversity")
+
+    elif cod == "CSP/ERGo/1_0/US/physiography":
+        dataset = ee.Image("CSP/ERGo/1_0/US/physiography")
+        physiography = dataset.select("constant")
+        physiographyVis = {
+            "min": 1100.0,
+            "max": 4220.0,
+        }
+        Map.setCenter(-105.4248, 40.5242, 8)
+        Map.addLayer(physiography, physiographyVis, "Physiography")
+        
+    elif cod == "CSP/ERGo/1_0/US/topoDiversity":
+        dataset = ee.Image("CSP/ERGo/1_0/US/topoDiversity")
+        usTopographicDiversity = dataset.select("constant")
+        usTopographicDiversityVis = {
+            "min": 0.0,
+            "max": 1.0,
+        }
+        Map.setCenter(-111.313, 39.724, 6)
+        Map.addLayer(usTopographicDiversity, usTopographicDiversityVis, "US Topographic Diversity")
+
+    elif cod == "CSP/HM/GlobalHumanModification":
+        dataset = ee.ImageCollection("CSP/HM/GlobalHumanModification")
+        visualization = {"bands": ["gHM"],
+                        "min": 0.0,
+                        "max": 1.0,
+                        "palette": ["0c0c0c", "071aff", "ff0000", "ffbd03", "fbff05", "fffdfd"]
+        }
+        Map.centerObject(dataset)
+        Map.addLayer(dataset, visualization, "Human modification")
+
+    elif cod == "DLR/WSF/WSF2015/v1":
+        dataset = ee.Image("DLR/WSF/WSF2015/v1")
+        opacity = 0.75
+        blackBackground = ee.Image(0)
+        Map.addLayer(blackBackground, None, "Black background", True, opacity)
+        visualization = {
+          "min": 0,
+          "max": 255,
+        }
+        Map.addLayer(dataset, visualization, "Human settlement areas")
+        Map.setCenter(90.45, 23.7, 7)
+
+    elif cod == "DOE/ORNL/LandScan_HD/Ukraine_202201":
+        dataset = ee.Image("DOE/ORNL/LandScan_HD/Ukraine_202201")
+        vis = {
+          "min": 0.0,
+          "max": 10.0,
+          "palette":["lemonchiffon", "khaki", "orange","orangered", "red", "maroon"],
+        }
+        Map.centerObject(dataset)
+        Map.addLayer(dataset, vis, "Population Count")
+
+    elif cod == "ECMWF/CAMS/NRT":
+        dataset = ee.ImageCollection("ECMWF/CAMS/NRT").filter(ee.Filter.date("2019-01-01", "2019-01-31"))
+        aod = dataset.select("total_aerosol_optical_depth_at_550nm_surface")
+        visParams = {
+          "min": 0.000096,
+          "max": 3.582552,
+          "palette": [
+          "5E4FA2", "3288BD", "66C2A5", "ABE0A4",
+          "E6F598", "FFFFBF", "FEE08B", "FDAE61",
+          "F46D43", "D53E4F", "9E0142"
+          ]
+        }
+        Map.setCenter(-94.18, 16.8, 1)
+        Map.addLayer(aod, visParams, "Total Aerosal Optical Depth")
+    
+    elif cod == "ECMWF/ERA5/DAILY":
+        era5_2mt = ee.ImageCollection("ECMWF/ERA5/DAILY").select("mean_2m_air_temperature").filter(ee.Filter.date("2019-07-01", "2019-07-31"))
+        
+        era5_tp = ee.ImageCollection("ECMWF/ERA5/DAILY").select("total_precipitation").filter(ee.Filter.date("2019-07-01", "2019-07-31"))
+        era5_2d = ee.ImageCollection("ECMWF/ERA5/DAILY").select("dewpoint_2m_temperature").filter(ee.Filter.date("2019-07-01", "2019-07-31"))
+        era5_mslp = ee.ImageCollection("ECMWF/ERA5/DAILY").select("mean_sea_level_pressure").filter(ee.Filter.date("2019-07-01", "2019-07-31")) 
+        era5_sp = ee.ImageCollection("ECMWF/ERA5/DAILY").select("surface_pressure").filter(ee.Filter.date("2019-07-01", "2019-07-31"))
+        era5_u_wind_10m = ee.ImageCollection("ECMWF/ERA5/DAILY").select("u_component_of_wind_10m").filter(ee.Filter.date("2019-07-01", "2019-07-31"))
+        era5_sp = era5_sp.map(lambda image: image.divide(100).set("system:time_start", image.get("system:time_start")))
+        visTp = {"min": 0, "max": 0.1, "palette": ["#FFFFFF", "#00FFFF", "#0080FF", "#DA00FF", "#FFA400", "#FF0000"]}
+        vis2mt = {"min": 250, 
+                  "max": 320, 
+                  "palette": [
+                          "#000080", "#0000D9", "#4000FF", "#8000FF", "#0080FF", "#00FFFF", "#00FF80",
+                          "#80FF00", "#DAFF00", "#FFFF00", "#FFF500", "#FFDA00", "#FFB000", "#FFA400",
+                          "#FF4F00", "#FF2500", "#FF0A00", "#FF00FF"]
+        }
+        visWind = {"min": 0, 
+                   "max": 30, 
+                   "palette": [
+                           "#FFFFFF", "#FFFF71", "#DEFF00", "#9EFF00", "#77B038", "#007E55", "#005F51",
+                           "#004B51", "#013A7B", "#023AAD"]
+        }
+        visPressure = {"min": 500, 
+                       "max": 1150,
+                       "palette": ["#01FFFF", "#058BFF", "#0600FF", "#DF00FF", "#FF00FF", "#FF8C00", "#FF8C00"]
+        }
+        Map.addLayer(era5_tp.filter(ee.Filter.date("2019-07-15")), visTp, "Daily total precipitation sums")
+        Map.addLayer(era5_2d.filter(ee.Filter.date("2019-07-15")), vis2mt, "Daily mean 2m dewpoint temperature")
+        Map.addLayer(era5_2mt.filter(ee.Filter.date("2019-07-15")), vis2mt, "Daily mean 2m air temperature")
+        Map.addLayer(era5_u_wind_10m.filter(ee.Filter.date("2019-07-15")), visWind, "Daily mean 10m u-component of wind")
+        Map.addLayer(era5_sp.filter(ee.Filter.date("2019-07-15")), visPressure, "Daily mean surface pressure")
+        Map.setCenter(21.2, 22.2, 2)
+                                
+    elif cod == "ECMWF/ERA5/MONTHLY":
+        dataset = ee.ImageCollection("ECMWF/ERA5/MONTHLY")
+        visualization = {
+             "bands": ["mean_2m_air_temperature"],
+             "min": 250.0,
+             "max": 320.0,
+             "palette": ["#000080","#0000D9","#4000FF","#8000FF","#0080FF","#00FFFF","#00FF80","#80FF00","#DAFF00","#FFFF00","#FFF500","#FFDA00","#FFB000","#FFA400","#FF4F00","#FF2500","#FF0A00","#FF00FF"]
+             }
+        Map.setCenter(22.2, 21.2, 0)
+        Map.addLayer(dataset, visualization, "Monthly average air temperature [K] at 2m height")
+
+    elif cod == "ECMWF/ERA5_LAND/DAILY_RAW":
+        dataset = ee.ImageCollection("ECMWF/ERA5_LAND/DAILY_RAW").filter(ee.Filter.date("2021-06-01", "2021-07-01"))
+        visualization = {
+             "bands": ["temperature_2m"],
+             "min": 250.0,
+             "max": 320.0,
+             "palette": ["#000080","#0000D9","#4000FF","#8000FF","#0080FF","#00FFFF","#00FF80","#80FF00","#DAFF00","#FFFF00","#FFF500","#FFDA00","#FFB000","#FFA400","#FF4F00","#FF2500","#FF0A00","#FF00FF"]
+             }
+        Map.setCenter(-170.13, 45.62, 2)
+        Map.addLayer(dataset, visualization, "Air temperature [K] at 2m height")
+
+    elif cod == "ECMWF/ERA5_LAND/HOURLY":
+        dataset = ee.ImageCollection("ECMWF/ERA5_LAND/HOURLY").filter(ee.Filter.date("2020-07-01", "2020-07-02"))
+        visualization = {
+             "bands": ["temperature_2m"],
+             "min": 250.0,
+             "max": 320.0,
+             "palette": ["#000080","#0000D9","#4000FF","#8000FF","#0080FF","#00FFFF","#00FF80","#80FF00","#DAFF00","#FFFF00","#FFF500","#FFDA00","#FFB000","#FFA400","#FF4F00","#FF2500","#FF0A00","#FF00FF"]
+             }
+        Map.setCenter(22.2, 21.2, 0)
+        Map.addLayer(dataset, visualization, "Air temperature [K] at 2m height")
+                     
+    elif cod == "ECMWF/ERA5_LAND/MONTHLY_AGGR":
+        dataset = ee.ImageCollection("ECMWF/ERA5_LAND/MONTHLY_AGGR").filter(ee.Filter.date("2020-02-01", "2020-07-10"))
+        visualization = {
+             "bands": ["temperature_2m"],
+             "min": 250.0,
+             "max": 320.0,
+             "palette": ["#000080","#0000D9","#4000FF","#8000FF","#0080FF","#00FFFF","#00FF80","#80FF00","#DAFF00","#FFFF00","#FFF500","#FFDA00","#FFB000","#FFA400","#FF4F00","#FF2500","#FF0A00","#FF00FF"]
+             }
+        Map.setCenter(-170.13, 45.62, 2)
+        Map.addLayer(dataset, visualization, "Air temperature [K] at 2m height")
+                     
+    elif cod == "ECMWF/ERA5_LAND/MONTHLY_BY_HOUR": 
+        dataset = ee.ImageCollection("ECMWF/ERA5_LAND/MONTHLY_BY_HOUR").filter(ee.Filter.date("2020-07-01", "2020-08-01"))
+        visualization = {
+             "bands": ["temperature_2m"],
+             "min": 250.0,
+             "max": 320.0,
+             "palette": ["#000080","#0000D9","#4000FF","#8000FF","#0080FF","#00FFFF","#00FF80","#80FF00","#DAFF00","#FFFF00","#FFF500","#FFDA00","#FFB000","#FFA400","#FF4F00","#FF2500","#FF0A00","#FF00FF"]
+             }
+        Map.setCenter(22.2, 21.2, 0)
+        Map.addLayer(dataset, visualization, "Air temperature [K] at 2m height")
+
+    elif cod == "EO1/HYPERION":
+        dataset = ee.ImageCollection("EO1/HYPERION").filter(ee.Filter.date("2016-01-01", "2017-03-01"))
+        rgb = dataset.select(["B050", "B023", "B015"])
+        rgbVis = {
+             "min": 1000.0,
+             "max": 14000.0,
+             "gamma": 2.5,
+             }
+        Map.setCenter(162.0044, -77.3463, 9)
+        Map.addLayer(rgb.median(), rgbVis, "RGB")
+
+    elif cod == "EPA/Ecoregions/2013/L3":
+        dataset = ee.FeatureCollection("EPA/Ecoregions/2013/L3")
+        visParams = {
+             "palette": ["0a3b04", "1a9924", "15d812"],
+             "min": 23.0,
+             "max": 3.57e+11,
+             "opacity": 0.8,
+             }
+        image = ee.Image().float().paint(dataset, "shape_area")
+        Map.setCenter(-99.814, 40.166, 5)
+        Map.addLayer(image, visParams, "EPA/Ecoregions/2013/L3")
+        Map.addLayer(dataset, None, "for Inspector", False)
+
+    elif cod == "EPA/Ecoregions/2013/L4":
+        dataset = ee.FeatureCollection("EPA/Ecoregions/2013/L4")
+        visParams = {
+             "palette": ["0a3b04", "1a9924", "15d812"],
+             "min": 0.0,
+             "max": 67800000000.0,
+             "opacity": 0.8,
+             }
+        image = ee.Image().float().paint(dataset, "shape_area")
+        Map.setCenter(-99.814, 40.166, 5)
+        Map.addLayer(image, visParams, "EPA/Ecoregions/2013/L4")
+        Map.addLayer(dataset, None, "for Inspector", False)
+
+    elif cod == "ESA/CCI/FireCCI/5_1":
+        dataset = ee.ImageCollection("ESA/CCI/FireCCI/5_1").filterDate("2020-01-01", "2020-12-31")
+        burnedArea = dataset.select("BurnDate")
+        baVis = {
+             "min": 1,
+             "max": 366,
+             "palette": ["ff0000", "fd4100", "fb8200", "f9c400", "f2ff00", "b6ff05","7aff0a", "3eff0f", "02ff15", "00ff55", "00ff99", "00ffdd","00ddff", "0098ff", "0052ff", "0210ff", "3a0dfb", "7209f6","a905f1", "e102ed", "ff00cc", "ff0089", "ff0047", "ff0004"]
+             }
+        maxBA = burnedArea.max()
+        Map.setCenter(0, 18, 2.1)
+        Map.addLayer(maxBA, baVis, "Burned Area")
+
+    elif cod == "ESA/GLOBCOVER_L4_200901_200912_V2_3":
+        dataset = ee.Image("ESA/GLOBCOVER_L4_200901_200912_V2_3")
+        landcover = dataset.select("landcover")
+        Map.setCenter(-88.6, 26.4, 3)
+        Map.addLayer(landcover, {}, "Landcover")
+
+    elif cod == "ESA/WorldCover/v100":
+        dataset = ee.ImageCollection("ESA/WorldCover/v100").first()
+        visualization = {
+             "bands": ["Map"],
+             }
+        Map.centerObject(dataset)
+        Map.addLayer(dataset, visualization, "Landcover")
+                     
+    elif cod == "ESA/WorldCover/v200":
+        dataset = ee.ImageCollection("ESA/WorldCover/v200").first()
+        visualization = {
+             "bands": ["Map"],
+             }
+        Map.centerObject(dataset)
+        Map.addLayer(dataset, visualization, "Landcover")
+                     
+    elif cod == "FAO/GAUL/2015/level0":
+        dataset = ee.FeatureCollection("FAO/GAUL/2015/level0")
+        Map.setCenter(7.82, 49.1, 4)
+        styleParams = {
+             "fillColor": "#b5ffb4",
+             "color": "#00909F",
+             "width": 1.0,
+             }
+        dataset = dataset.style(styleParams)
+        Map.addLayer(dataset, {}, "Country Boundaries")
+
+    elif cod == "FAO/GAUL/2015/level1":
+        dataset = ee.FeatureCollection("FAO/GAUL/2015/level1")
+        Map.setCenter(7.82, 49.1, 4)
+        styleParams = {
+             "fillColor": "b5ffb4",
+             "color": "#00909F",
+             "width": 1.0,
+             }
+        dataset = dataset.style(styleParams)
+        Map.addLayer(dataset, {}, "First Level Administrative Units")
+                     
+    elif cod == "FAO/GAUL/2015/level2":
+        dataset = ee.FeatureCollection("FAO/GAUL/2015/level2")
+        Map.setCenter(12.876, 42.682, 5)
+        styleParams = {
+             "fillColor": "#b5ffb4",
+             "color": "#00909F",
+             "width": 1.0,
+             }
+        dataset = dataset.style(styleParams)
+        Map.addLayer(dataset, {}, "Second Level Administrative Units")
+
+    elif cod == "FAO/GAUL_SIMPLIFIED_500m/2015/level0": 
+        dataset = ee.FeatureCollection("FAO/GAUL_SIMPLIFIED_500m/2015/level0")
+        Map.setCenter(7.82, 49.1, 4)
+        styleParams = {
+             "fillColor": "#b5ffb4",
+             "color": "#00909F",
+             "width": 1.0,
+             }
+        dataset = dataset.style(styleParams)
+        Map.addLayer(dataset, {}, "Country Boundaries")
+                     
+    elif cod == "FAO/GAUL_SIMPLIFIED_500m/2015/level1":
+        dataset = ee.FeatureCollection("FAO/GAUL_SIMPLIFIED_500m/2015/level1")
+        Map.setCenter(7.82, 49.1, 4)
+        styleParams = {
+             "fillColor": "#b5ffb4",
+             "color": "#00909F",
+             "width": 1.0,
+             }
+        dataset = dataset.style(styleParams)
+        Map.addLayer(dataset, {}, "First Level Administrative Units")
+
+    elif cod == "FAO/GAUL_SIMPLIFIED_500m/2015/level2":
+        dataset = ee.FeatureCollection("FAO/GAUL_SIMPLIFIED_500m/2015/level2")
+        Map.setCenter(12.876, 42.682, 5)
+        styleParams = {
+             "fillColor": "b5ffb4",
+             "color": "00909F",
+             "width": 1.0,
+             }
+        dataset = dataset.style(styleParams)
+        Map.addLayer(dataset, {}, "Second Level Administrative Units")
+        
+    elif cod == "FAO/GHG/1/DROSA_A":
+        dataset = ee.ImageCollection("FAO/GHG/1/DROSA_A")
+        visualization = {
+        "bands": ["cropland"],
+        "min": 1.0,
+        "max": 60.0,
+        "palette": ["white", "red"]
+        }
+        Map.setCenter(108.0, -0.4, 6)
+        Map.addLayer(dataset, visualization, "Cropland area drained (Annual)")
+
+    elif cod == "FAO/GHG/1/DROSE_A":
+        dataset = ee.ImageCollection("FAO/GHG/1/DROSE_A")
+        visualization = {
+        "bands": ["croplandc"],
+        "min": 0.1,
+        "max": 0.1,
+        "palette": ["yellow", "red"]
+        }
+        Map.setCenter(108.0, -0.4, 6)
+        Map.addLayer(dataset, visualization, "Cropland C emissions (Annual)")
+
+    elif cod == "FAO/SOFO/1/FPP":
+        coll = ee.ImageCollection("FAO/SOFO/1/FPP")
+        image = coll.first().select("FPP_1km")
+        Map.setCenter(17.5, 20, 3)
+        Map.addLayer(image, {"min": 0, "max": 12, "palette": ["blue", "yellow", "red"]},"Forest proximate people – 1km cutoff distance")
+
+    elif cod == "FAO/SOFO/1/TPP":
+        coll = ee.ImageCollection("FAO/SOFO/1/TPP")
+        image = coll.first().select("TPP_1km")
+        Map.setCenter(17.5, 20, 3)
+        Map.addLayer(
+        image, {"min": 0, "max": 12, "palette": ["blue", "yellow", "red"]}, "Tree proximate people – 1km cutoff distance")
+
+    elif cod == "FAO/WAPOR/2/L1_AETI_D":
+        coll = ee.ImageCollection("FAO/WAPOR/2/L1_AETI_D")
+        image = coll.first()
+        Map.setCenter(17.5, 20, 3)
+        Map.addLayer(image, {"min": 0, "max": 50})
+
+    elif cod == "FAO/WAPOR/2/L1_E_D":
+        coll = ee.ImageCollection("FAO/WAPOR/2/L1_E_D")
+        image = coll.first()
+        Map.setCenter(17.5, 20, 3)
+        Map.addLayer(image, {"min": 0, "max": 10})
+
+    elif cod == "FAO/WAPOR/2/L1_I_D":
+        coll = ee.ImageCollection("FAO/WAPOR/2/L1_I_D")
+        image = coll.first()
+        Map.setCenter(17.5, 20, 3)
+        Map.addLayer(image, {"min": 0, "max": 50})
+        
+    elif cod == "FAO/WAPOR/2/L1_NPP_D":
+        coll = ee.ImageCollection("FAO/WAPOR/2/L1_NPP_D")
+        image = coll.first()
+        Map.setCenter(17.5, 20, 3)
+        Map.addLayer(image, {"min": 0, "max": 5000})
+
+    elif cod == "FAO/WAPOR/2/L1_RET_D":
+        coll = ee.ImageCollection("FAO/WAPOR/2/L1_RET_D")
+        image = coll.first()
+        Map.setCenter(17.5, 20, 3)
+        Map.addLayer(image, {"min": 0, "max": 100})
+
+    elif cod == "FAO/WAPOR/2/L1_RET_E":
+        coll = ee.ImageCollection("FAO/WAPOR/2/L1_RET_E")
+        image = coll.first()
+        Map.setCenter(17.5, 20, 3)
+        Map.addLayer(image, {"min": 0, "max": 100})
+
+    elif cod == "FAO/WAPOR/2/L1_T_D":
+        coll = ee.ImageCollection("FAO/WAPOR/2/L1_T_D")
+        image = coll.first()
+        Map.setCenter(17.5, 20, 3)
+        Map.addLayer(image, {"min": 0, "max": 50})
+
+    elif cod == "FIRMS":
+        dataset = ee.ImageCollection("FIRMS").filter(
+        ee.Filter.date("2018-08-01", "2018-08-10"))
+        fires = dataset.select("T21")
+        firesVis = {
+        "min": 325.0,
+        "max": 400.0,
+        "palette": ["red", "orange", "yellow"],
+        }
+        Map.setCenter(-119.086, 47.295, 6)
+        Map.addLayer(fires, firesVis, "Fires")
+
+    elif cod == "Finland/MAVI/VV/50cm":
+        dataset = ee.ImageCollection("Finland/MAVI/VV/50cm")
+        Map.setCenter(25.7416, 62.2446, 16)
+        Map.addLayer(dataset, None, "Finland 50 cm(False color)")
+
+    elif cod == "GFW/GFF/V1/fishing_hours":
+        dataset = ee.ImageCollection("GFW/GFF/V1/fishing_hours").filter(ee.Filter.date("2016-12-01", "2017-01-01"))
+        trawlers = dataset.select("trawlers")
+        trawlersVis = {
+        "min": 0.0,
+        "max": 5.0,
+        }
+        Map.setCenter(16.201, 36.316, 7)
+        Map.addLayer(trawlers.max(), trawlersVis, "Trawlers")
+
+    elif cod == "GFW/GFF/V1/vessel_hours":
+        dataset = ee.ImageCollection("GFW/GFF/V1/vessel_hours").filter(ee.Filter.date("2016-12-01", "2017-01-01"))
+        trawlers = dataset.select("trawlers")
+        trawlersVis = {
+        "min": 0.0,
+        "max": 5.0,
+        }
+        Map.setCenter(130.61, 34.287, 8)
+        Map.addLayer(trawlers.max(), trawlersVis, "Trawlers")
+
+    elif cod == "GLCF/GLS_WATER":
+        dataset = ee.ImageCollection("GLCF/GLS_WATER")
+        water = dataset.select("water")
+        waterVis = {
+        "min": 1.0,
+        "max": 4.0,
+        "palette": ["FAFAFA", "00C5FF", "DF73FF", "828282", "CCCCCC"],
+        }
+        Map.setCenter(-79.3094, 44.5693, 8)
+        Map.addLayer(water, waterVis, "Water")
+
+    elif cod == "GLIMS/20210914":
+        dataset = ee.FeatureCollection("GLIMS/20210914")
+        visParams = {
+        "palette": ["gray", "cyan", "blue"],
+        "min": 0.0,
+        "max": 10.0,
+        "opacity": 0.8,
+        }
+        image = ee.Image().float().paint(dataset, "area")
+        Map.setCenter(-35.618, 66.743, 7)
+        Map.addLayer(image, visParams, "GLIMS/20210914")
+        Map.addLayer(dataset, None, "for Inspector", False)
+
+    elif cod == "Finland/SMK/VV/50cm":
+        dataset = ee.ImageCollection("Finland/SMK/VV/50cm")
+        Map.setCenter(25.7416, 62.2446, 16)
+        Map.addLayer(dataset, None, "Finland 50 cm(False color)")
+
+    elif cod == "Finland/SMK/V/50cm":
+        dataset = ee.ImageCollection("Finland/SMK/V/50cm")
+        Map.setCenter(24.9, 60.2, 17)
+        Map.addLayer(dataset, None, "Finland 50 cm(color)")
+
+    elif cod == "GLIMS/current":
+        dataset = ee.FeatureCollection("GLIMS/current")
+        visParams = {
+        "palette": ["gray", "cyan", "blue"],
+        "min": 0.0,
+        "max": 10.0,
+        "opacity": 0.8,
+        }
+        image = ee.Image().float().paint(dataset, "area")
+        Map.setCenter(-35.618, 66.743, 7)
+        Map.addLayer(image, visParams, "GLIMS/current")
+        Map.addLayer(dataset, None, "for Inspector", False)
+
+    elif cod == "GLOBAL_FLOOD_DB/MODIS_EVENTS/V1":
+        gfd = ee.ImageCollection("GLOBAL_FLOOD_DB/MODIS_EVENTS/V1")
+        hurricaneIsaacDartmouthId = 3977
+        hurricaneIsaacUsa = ee.Image(gfd.filterMetadata("id", "equals", hurricaneIsaacDartmouthId).first())
+        Map.setOptions("SATELLITE")
+        Map.setCenter(-90.2922, 29.4064, 9)
+        Map.addLayer(
+        hurricaneIsaacUsa.select("flooded").selfMask(),{"min": 0, "max": 1, "palette": "001133"},"Hurricane Isaac - Inundation Extent")
+        durationPalette = ["C3EFFE", "1341E8", "051CB0", "001133"]
+        Map.addLayer(hurricaneIsaacUsa.select("duration").selfMask(),{"min": 0, "max": 4, "palette": durationPalette},"Hurricane Isaac - Duration")
+        gfdFloodedSum = gfd.select("flooded").sum()
+        Map.addLayer(gfdFloodedSum.selfMask(),{"min": 0, "max": 10, "palette": durationPalette},"GFD Satellite Observed Flood Plain")
+        jrc = gfd.select("jrc_perm_water").sum().gte(1)
+        Map.addLayer(jrc.selfMask(),{"min": 0, "max": 1, "palette": "C3EFFE"},"JRC Permanent Water")
+
+    elif cod == "GOOGLE/DYNAMICWORLD/V1":
+        COL_FILTER = ee.Filter.And(ee.Filter.bounds(ee.Geometry.Point(20.6729, 52.4305)),ee.Filter.date("2021-04-02", "2021-04-03"))
+        dwCol = ee.ImageCollection("GOOGLE/DYNAMICWORLD/V1").filter(COL_FILTER)
+        s2Col = ee.ImageCollection("COPERNICUS/S2").filter(COL_FILTER)
+        DwS2Col = ee.Join.saveFirst("s2_img").apply(dwCol, s2Col,
+        ee.Filter.equals({"leftField": "system:index", "rightField": "system:index"}))
+        dwImage = ee.Image(DwS2Col.first())
+        s2Image = ee.Image(dwImage.get("s2_img"))
+        CLASS_NAMES = ["water", "trees", "grass", "flooded_vegetation", "crops","shrub_and_scrub", "built", "bare", "snow_and_ice"]
+        VIS_PALETTE = ["419BDF", "397D49", "88B053", "7A87C6","E49635", "DFC35A", "C4281B", "A59B8F","B39FE1"]
+        dwRgb = dwImage.select("label").visualize({"min": 0, "max": 8, "palette": VIS_PALETTE}).divide(255)
+        top1Prob = dwImage.select(CLASS_NAMES).reduce(ee.Reducer.max())
+        top1ProbHillshade = ee.Terrain.hillshade(top1Prob.multiply(100)).divide(255)
+        dwRgbHillshade = dwRgb.multiply(top1ProbHillshade)
+        Map.setCenter(20.6729, 52.4305, 12)
+        Map.addLayer(s2Image,{"min": 0, "max": 3000, "bands": ["B4", "B3", "B2"]},"Sentinel-2 L1C")
+        Map.addLayer(dwRgbHillshade,{"min": 0, "max": 0.65},"Dynamic World")
+
+    elif cod == "GOOGLE/Research/open-buildings/v2/polygons":
+        t = ee.FeatureCollection("GOOGLE/Research/open-buildings/v2/polygons")
+        t_060_065 = t.filter("confidence >= 0.60 && confidence < 0.65")
+        t_065_070 = t.filter("confidence >= 0.65 && confidence < 0.70")
+        t_gte_070 = t.filter("confidence >= 0.70")
+        Map.addLayer(t_060_065, {"color": "FF0000"}, "Buildings confidence [0.60 0.65)")
+        Map.addLayer(t_065_070, {"color": "FFFF00"}, "Buildings confidence [0.65 0.70)")
+        Map.addLayer(t_gte_070, {"color": "00FF00"}, "Buildings confidence >= 0.70")
+        Map.setCenter(3.389, 6.492, 17)
+        Map.setOptions("SATELLITE")
+
+    elif cod == "GRIDMET/DROUGHT":
+        collection = ee.ImageCollection("GRIDMET/DROUGHT")
+        dS = "2020-03-30"
+        dE = "2020-03-30"
+        dSUTC = ee.Date(dS, "GMT")
+        dEUTC = ee.Date(dE, "GMT")
+        filtered = collection.filterDate(dSUTC, dEUTC.advance(1, "day"))
+        PDSI = filtered.select("pdsi")
+        Z = filtered.select("z")
+        SPI2y = filtered.select("spi2y")
+        SPEI2y = filtered.select("spei2y")
+        EDDI2y = filtered.select("spei2y")
+        usdmColors = ["0000aa","0000ff","00aaff","00ffff","aaff55","ffffff","ffff00","fcd37f","ffaa00","e60000","730000"]
+        minColorbar= -2.5
+        maxColorbar= 2.5
+        colorbarOptions1 = {
+            "min":minColorbar,
+            "max":maxColorbar,
+            "palette": usdmColors}
+        minColorbar= -6
+        maxColorbar= 6
+        colorbarOptions2 = {
+            "min":minColorbar,
+            "max":maxColorbar,
+            "palette": usdmColors}
+        Map.addLayer(ee.Image(PDSI.first()), colorbarOptions2, "PDSI")
+        Map.addLayer(ee.Image(Z.first()), colorbarOptions2, "Palmer-Z")
+        Map.addLayer(ee.Image(SPI2y.first()), colorbarOptions1, "SPI-48months")
+        Map.addLayer(ee.Image(SPEI2y.first()), colorbarOptions1, "SPEI-48months")
+        Map.addLayer(ee.Image(EDDI2y.first()), colorbarOptions1, "EDDI-48months")
+
+    elif cod == "Germany/Brandenburg/orthos/20cm":
+        dataset = ee.Image("Germany/Brandenburg/orthos/20cm")
+        Map.setCenter(13.386091, 52.507899, 18)
+        Map.addLayer(dataset, None, "Brandenburg 20cm")
+
+    elif cod == "HYCOM/sea_surface_elevation":
+        dataset = ee.ImageCollection("HYCOM/sea_surface_elevation").filter(ee.Filter.date("2018-08-01", "2018-08-15"))
+        surfaceElevation = dataset.select("surface_elevation")
+        surfaceElevationVis = {
+        "min": -2000.0,
+        "max": 2000.0,
+        "palette": ["blue", "cyan", "yellow", "red"],
+        }
+        Map.setCenter(-28.1, 28.3, 1)
+        Map.addLayer(surfaceElevation, surfaceElevationVis, "Surface Elevation")
+
+    elif cod == "HYCOM/sea_temp_salinity":
+        dataset = ee.ImageCollection("HYCOM/sea_temp_salinity").filter(ee.Filter.date("2018-08-01", "2018-08-15"))
+        seaWaterTemperature = dataset.select("water_temp_0").map(lambda image: ee.Image(image).multiply(0.001).add(20))
+        visParams = {
+        "min": -2.0,
+        "max": 34.0,
+        "palette": ["000000", "005aff", "43c8c8", "fff700", "ff0000"],
+        }
+        Map.setCenter(-88.6, 26.4, 1)
+        Map.addLayer(seaWaterTemperature.mean(), visParams, "Sea Water Temperature")
+
+
+    elif cod == "HYCOM/sea_water_velocity":
+        velocity = ee.Image("HYCOM/sea_water_velocity/2014040700").divide(1000)
+        Map.addLayer(velocity.select("velocity_u_0").hypot(velocity.select("velocity_v_0")))
+        Map.setCenter(-60, 33, 5)
+
+    elif cod == "IDAHO_EPSCOR/GRIDMET":
+        dataset = ee.ImageCollection("IDAHO_EPSCOR/GRIDMET").filter(ee.Filter.date("2018-08-01", "2018-08-15"))
+        maximumTemperature = dataset.select("tmmx")
+        maximumTemperatureVis = {
+        "min": 290.0,
+        "max": 314.0,
+        "palette": ["d8d8d8", "4addff", "5affa3", "f2ff89", "ff725c"],
+        }
+        Map.setCenter(-115.356, 38.686, 5)
+        Map.addLayer(maximumTemperature, maximumTemperatureVis, "Maximum Temperature")
+
+    elif cod == "IDAHO_EPSCOR/MACAv2_METDATA":
+        dataset = ee.ImageCollection("IDAHO_EPSCOR/MACAv2_METDATA").filter(ee.Filter.date("2018-08-01", "2018-08-15"))
+        maximumTemperature = dataset.select("tasmax")
+        maximumTemperatureVis = {
+        "min": 290.0,
+        "max": 314.0,
+        "palette": ["d8d8d8", "4addff", "5affa3", "f2ff89", "ff725c"],
+        }
+        Map.setCenter(-84.37, 33.5, 5)
+        Map.addLayer(maximumTemperature, maximumTemperatureVis, "Maximum Temperature")
+
+    elif cod == "IDAHO_EPSCOR/MACAv2_METDATA_MONTHLY":
+        dataset = ee.ImageCollection("IDAHO_EPSCOR/MACAv2_METDATA_MONTHLY").filter(ee.Filter.date("2018-07-01", "2018-08-01"))
+        maximumTemperature = dataset.select("tasmax")
+        maximumTemperatureVis = {
+        "min": 290.0,
+        "max": 314.0,
+        "palette": ["d8d8d8", "4addff", "5affa3", "f2ff89", "ff725c"],
+        }
+        Map.setCenter(-115.356, 38.686, 5)
+        Map.addLayer(maximumTemperature, maximumTemperatureVis, "Maximum Temperature")
+
+    elif cod == "IDAHO_EPSCOR/TERRACLIMATE":
+        dataset = ee.ImageCollection("IDAHO_EPSCOR/TERRACLIMATE").filter(ee.Filter.date("2017-07-01", "2017-08-01"))
+        maximumTemperature = dataset.select("tmmx")
+        maximumTemperatureVis = {
+        "min": -300.0,
+        "max": 300.0,
+        "palette": ["1a3678", "2955bc", "5699ff", "8dbae9", "acd1ff", "caebff", "e5f9ff",
+                    "fdffb4", "ffe6a2", "ffc969", "ffa12d", "ff7c1f", "ca531a", "ff0000", "ab0000"]}
+        Map.setCenter(71.72, 52.48, 3)
+        Map.addLayer(maximumTemperature, maximumTemperatureVis, "Maximum Temperature")
+
+    elif cod == "IGN/RGE_ALTI/1M/2_0/FXX":
+        dataset = ee.Image("IGN/RGE_ALTI/1M/2_0/FXX")
+        elevation = dataset.select("MNT")
+        elevationVis = {
+            "min": 0,
+            "max": 1000,
+            "palette": ["006600", "002200", "fff700", "ab7634", "c4d0ff", "ffffff"]}
+        Map.addLayer(elevation, elevationVis, "Elevation")
+        Map.setCenter(3, 47, 5)
+
+    ###https://developers.google.com/earth-engine/datasets/catalog/ISDASOIL_Africa_v1_aluminium_extractable
+
+    elif cod == "ISDASOIL/Africa/v1/aluminium_extractable":
+        mean_0_20 = """
+            <RasterSymbolizer>
+            <ColorMap type="ramp">
+            <ColorMapEntry color="#000004" label="0-21.2" opacity="1" quantity="31"/>
+            <ColorMapEntry color="#0C0927" label="21.2-35.6" opacity="1" quantity="36"/>
+            <ColorMapEntry color="#231151" label="35.6-53.6" opacity="1" quantity="40"/>
+            <ColorMapEntry color="#410F75" label="53.6-65.7" opacity="1" quantity="42"/>
+            <ColorMapEntry color="#5F187F" label="65.7-72.7" opacity="1" quantity="43"/>
+            <ColorMapEntry color="#7B2382" label="72.7-80.5" opacity="1" quantity="44"/>
+            <ColorMapEntry color="#982D80" label="80.5-89" opacity="1" quantity="45"/>
+            <ColorMapEntry color="#B63679" label="89-98.5" opacity="1" quantity="46"/>
+            <ColorMapEntry color="#D3436E" label="98.5-108.9" opacity="1" quantity="47"/>
+            <ColorMapEntry color="#EB5760" label="108.9-120.5" opacity="1" quantity="48"/>
+            <ColorMapEntry color="#F8765C" label="120.5-133.3" opacity="1" quantity="49"/>
+            <ColorMapEntry color="#FD9969" label="133.3-147.4" opacity="1" quantity="50"/>
+            <ColorMapEntry color="#FEBA80" label="147.4-163" opacity="1" quantity="51"/>
+            <ColorMapEntry color="#FDDC9E" label="163-199.3" opacity="1" quantity="53"/>
+            <ColorMapEntry color="#FCFDBF" label="199.3-1800" opacity="1" quantity="55"/>
+            </ColorMap>
+            <ContrastEnhancement/>
+            </RasterSymbolizer> """
+        mean_20_50 = """
+            <RasterSymbolizer>
+            <ColorMap type="ramp">
+            <ColorMapEntry color="#000004" label="0-21.2" opacity="1" quantity="31"/>
+            <ColorMapEntry color="#0C0927" label="21.2-35.6" opacity="1" quantity="36"/>
+            <ColorMapEntry color="#231151" label="35.6-53.6" opacity="1" quantity="40"/>
+            <ColorMapEntry color="#410F75" label="53.6-65.7" opacity="1" quantity="42"/>
+            <ColorMapEntry color="#5F187F" label="65.7-72.7" opacity="1" quantity="43"/>
+            <ColorMapEntry color="#7B2382" label="72.7-80.5" opacity="1" quantity="44"/>
+            <ColorMapEntry color="#982D80" label="80.5-89" opacity="1" quantity="45"/>
+            <ColorMapEntry color="#B63679" label="89-98.5" opacity="1" quantity="46"/>
+            <ColorMapEntry color="#D3436E" label="98.5-108.9" opacity="1" quantity="47"/>
+            <ColorMapEntry color="#EB5760" label="108.9-120.5" opacity="1" quantity="48"/>
+            <ColorMapEntry color="#F8765C" label="120.5-133.3" opacity="1" quantity="49"/>
+            <ColorMapEntry color="#FD9969" label="133.3-147.4" opacity="1" quantity="50"/>
+            <ColorMapEntry color="#FEBA80" label="147.4-163" opacity="1" quantity="51"/>
+            <ColorMapEntry color="#FDDC9E" label="163-199.3" opacity="1" quantity="53"/>
+            <ColorMapEntry color="#FCFDBF" label="199.3-1800" opacity="1" quantity="55"/>
+            </ColorMap>
+            <ContrastEnhancement/>
+            </RasterSymbolizer> """
+        stdev_0_20 = """
+            <RasterSymbolizer>
+            <ColorMap type="ramp">
+            <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="5"/>
+            <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="9"/>
+            <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="10"/>
+            <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="12"/>
+            <ColorMapEntry color="#440154" label="high" opacity="1" quantity="14"/>
+            </ColorMap>
+            <ContrastEnhancement/>
+            </RasterSymbolizer> """
+        stdev_20_50 = """
+            <RasterSymbolizer>
+            <ColorMap type="ramp">
+            <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="5"/>
+            <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="9"/>
+            <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="10"/>
+            <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="12"/>
+            <ColorMapEntry color="#440154" label="high" opacity="1" quantity="14"/>
+            </ColorMap>
+            <ContrastEnhancement/>
+            </RasterSymbolizer> """
+        Map.setCenter(25, -3, 2)
+        raw = ee.Image("ISDASOIL/Africa/v1/aluminium_extractable")
+        Map.addLayer(
+        raw.select(0).sldStyle(mean_0_20), {},"Aluminium, extractable, mean visualization, 0-20 cm")
+        Map.addLayer(raw.select(1).sldStyle(mean_20_50), {},"Aluminium, extractable, mean visualization, 20-50 cm")
+        Map.addLayer(raw.select(2).sldStyle(stdev_0_20), {},"Aluminium, extractable, stdev visualization, 0-20 cm")
+        Map.addLayer(raw.select(3).sldStyle(stdev_20_50), {},"Aluminium, extractable, stdev visualization, 20-50 cm")
+        converted = raw.divide(10).exp().subtract(1)
+        Map.addLayer(converted.select(0), {"min": 0, "max": 100},"Aluminium, extractable, mean, 0-20 cm")
+
+    elif cod == "ISDASOIL/Africa/v1/bedrock_depth":
+        mean_0_200 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#00204D" label="0-13" opacity="1" quantity="13"/>
+        <ColorMapEntry color="#002D6C" label="13-26" opacity="1" quantity="26"/>
+        <ColorMapEntry color="#16396D" label="26-39" opacity="1" quantity="39"/>
+        <ColorMapEntry color="#36476B" label="39-52" opacity="1" quantity="52"/>
+        <ColorMapEntry color="#4B546C" label="52-65" opacity="1" quantity="65"/>
+        <ColorMapEntry color="#5C616E" label="65-78" opacity="1" quantity="78"/>
+        <ColorMapEntry color="#6C6E72" label="78-91" opacity="1" quantity="91"/>
+        <ColorMapEntry color="#7C7B78" label="91-104" opacity="1" quantity="104"/>
+        <ColorMapEntry color="#8E8A79" label="104-117" opacity="1" quantity="117"/>
+        <ColorMapEntry color="#A09877" label="117-130" opacity="1" quantity="130"/>
+        <ColorMapEntry color="#B3A772" label="130-143" opacity="1" quantity="143"/>
+        <ColorMapEntry color="#C6B66B" label="143-156" opacity="1" quantity="156"/>
+        <ColorMapEntry color="#DBC761" label="156-169" opacity="1" quantity="169"/>
+        <ColorMapEntry color="#F0D852" label="169-182" opacity="1" quantity="182"/>
+        <ColorMapEntry color="#FFEA46" label="182-200" opacity="1" quantity="195"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_0_200 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="14"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="18"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="21"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="22"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="25"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        raw = ee.Image("ISDASOIL/Africa/v1/bedrock_depth")
+        Map.addLayer(raw.select(0).sldStyle(mean_0_200), {},"Bedrock depth, mean visualization, 0-200 cm")
+        Map.addLayer(raw.select(1).sldStyle(stdev_0_200), {},"Bedrock depth, stdev visualization, 0-200 cm")
+        visualization = {"min": 27, "max": 200}
+        Map.setCenter(25, -3, 2)
+        Map.addLayer(raw.select(0), visualization, "Bedrock depth, mean, 0-200 cm")
+
+    elif cod == "ISDASOIL/Africa/v1/bulk_density":
+        mean_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#00204D" label="0.8-1.05" opacity="1" quantity="105"/>
+        <ColorMapEntry color="#002D6C" label="1.05-1.19" opacity="1" quantity="119"/>
+        <ColorMapEntry color="#16396D" label="1.19-1.23" opacity="1" quantity="123"/>
+        <ColorMapEntry color="#36476B" label="1.23-1.25" opacity="1" quantity="125"/>
+        <ColorMapEntry color="#4B546C" label="1.25-1.28" opacity="1" quantity="128"/>
+        <ColorMapEntry color="#5C616E" label="1.28-1.31" opacity="1" quantity="131"/>
+        <ColorMapEntry color="#6C6E72" label="1.31-1.34" opacity="1" quantity="134"/>
+        <ColorMapEntry color="#7C7B78" label="1.34-1.36" opacity="1" quantity="136"/>
+        <ColorMapEntry color="#8E8A79" label="1.36-1.38" opacity="1" quantity="138"/>
+        <ColorMapEntry color="#A09877" label="1.38-1.41" opacity="1" quantity="141"/>
+        <ColorMapEntry color="#B3A772" label="1.41-1.43" opacity="1" quantity="143"/>
+        <ColorMapEntry color="#C6B66B" label="1.43-1.45" opacity="1" quantity="145"/>
+        <ColorMapEntry color="#DBC761" label="1.45-1.48" opacity="1" quantity="148"/>
+        <ColorMapEntry color="#F0D852" label="1.48-1.51" opacity="1" quantity="151"/>
+        <ColorMapEntry color="#FFEA46" label="1.51-1.85" opacity="1" quantity="154"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        mean_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#00204D" label="0.8-1.05" opacity="1" quantity="105"/>
+        <ColorMapEntry color="#002D6C" label="1.05-1.19" opacity="1" quantity="119"/>
+        <ColorMapEntry color="#16396D" label="1.19-1.23" opacity="1" quantity="123"/>
+        <ColorMapEntry color="#36476B" label="1.23-1.25" opacity="1" quantity="125"/>
+        <ColorMapEntry color="#4B546C" label="1.25-1.28" opacity="1" quantity="128"/>
+        <ColorMapEntry color="#5C616E" label="1.28-1.31" opacity="1" quantity="131"/>
+        <ColorMapEntry color="#6C6E72" label="1.31-1.34" opacity="1" quantity="134"/>
+        <ColorMapEntry color="#7C7B78" label="1.34-1.36" opacity="1" quantity="136"/>
+        <ColorMapEntry color="#8E8A79" label="1.36-1.38" opacity="1" quantity="138"/>
+        <ColorMapEntry color="#A09877" label="1.38-1.41" opacity="1" quantity="141"/>
+        <ColorMapEntry color="#B3A772" label="1.41-1.43" opacity="1" quantity="143"/>
+        <ColorMapEntry color="#C6B66B" label="1.43-1.45" opacity="1" quantity="145"/>
+        <ColorMapEntry color="#DBC761" label="1.45-1.48" opacity="1" quantity="148"/>
+        <ColorMapEntry color="#F0D852" label="1.48-1.51" opacity="1" quantity="151"/>
+        <ColorMapEntry color="#FFEA46" label="1.51-1.85" opacity="1" quantity="154"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="2"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="5"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="7"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="9"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="2"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="5"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="7"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="9"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        raw = ee.Image("ISDASOIL/Africa/v1/bulk_density")
+        Map.addLayer(raw.select(0).sldStyle(mean_0_20), {},"Bulk density, mean visualization, 0-20 cm")
+        Map.addLayer(raw.select(1).sldStyle(mean_20_50), {},"Bulk density, mean visualization, 20-50 cm")
+        Map.addLayer(raw.select(2).sldStyle(stdev_0_20), {},"Bulk density, stdev visualization, 0-20 cm")
+        Map.addLayer(raw.select(3).sldStyle(stdev_20_50), {},"Bulk density, stdev visualization, 20-50 cm")
+        converted = raw.divide(100)
+        visualization = {"min": 1, "max": 1.5}
+        Map.setCenter(25, -3, 2)
+        Map.addLayer(converted.select(0), visualization, "Bulk density, mean, 0-20 cm")
+
+    elif cod == "ISDASOIL/Africa/v1/calcium_extractable":
+        mean_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#0D0887" label="0-65.7" opacity="1" quantity="42"/>
+        <ColorMapEntry color="#350498" label="65.7-120.5" opacity="1" quantity="48"/>
+        <ColorMapEntry color="#5402A3" label="120.5-163" opacity="1" quantity="51"/>
+        <ColorMapEntry color="#7000A8" label="163-199.3" opacity="1" quantity="53"/>
+        <ColorMapEntry color="#8B0AA5" label="199.3-269.4" opacity="1" quantity="56"/>
+        <ColorMapEntry color="#A31E9A" label="269.4-329.3" opacity="1" quantity="58"/>
+        <ColorMapEntry color="#B93289" label="329.3-402.4" opacity="1" quantity="60"/>
+        <ColorMapEntry color="#CC4678" label="402.4-491.7" opacity="1" quantity="62"/>
+        <ColorMapEntry color="#DB5C68" label="491.7-600.8" opacity="1" quantity="64"/>
+        <ColorMapEntry color="#E97158" label="600.8-664.1" opacity="1" quantity="65"/>
+        <ColorMapEntry color="#F48849" label="664.1-811.4" opacity="1" quantity="67"/>
+        <ColorMapEntry color="#FBA139" label="811.4-896.8" opacity="1" quantity="68"/>
+        <ColorMapEntry color="#FEBC2A" label="896.8-1095.6" opacity="1" quantity="70"/>
+        <ColorMapEntry color="#FADA24" label="1095.6-1479.3" opacity="1" quantity="73"/>
+        <ColorMapEntry color="#F0F921" label="1479.3-12000" opacity="1" quantity="77"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        mean_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#0D0887" label="0-65.7" opacity="1" quantity="42"/>
+        <ColorMapEntry color="#350498" label="65.7-120.5" opacity="1" quantity="48"/>
+        <ColorMapEntry color="#5402A3" label="120.5-163" opacity="1" quantity="51"/>
+        <ColorMapEntry color="#7000A8" label="163-199.3" opacity="1" quantity="53"/>
+        <ColorMapEntry color="#8B0AA5" label="199.3-269.4" opacity="1" quantity="56"/>
+        <ColorMapEntry color="#A31E9A" label="269.4-329.3" opacity="1" quantity="58"/>
+        <ColorMapEntry color="#B93289" label="329.3-402.4" opacity="1" quantity="60"/>
+        <ColorMapEntry color="#CC4678" label="402.4-491.7" opacity="1" quantity="62"/>
+        <ColorMapEntry color="#DB5C68" label="491.7-600.8" opacity="1" quantity="64"/>
+        <ColorMapEntry color="#E97158" label="600.8-664.1" opacity="1" quantity="65"/>
+        <ColorMapEntry color="#F48849" label="664.1-811.4" opacity="1" quantity="67"/>
+        <ColorMapEntry color="#FBA139" label="811.4-896.8" opacity="1" quantity="68"/>
+        <ColorMapEntry color="#FEBC2A" label="896.8-1095.6" opacity="1" quantity="70"/>
+        <ColorMapEntry color="#FADA24" label="1095.6-1479.3" opacity="1" quantity="73"/>
+        <ColorMapEntry color="#F0F921" label="1479.3-12000" opacity="1" quantity="77"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="2"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="5"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="2"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="5"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        raw = ee.Image("ISDASOIL/Africa/v1/calcium_extractable")
+        Map.addLayer(raw.select(0).sldStyle(mean_0_20), {},"Calcium, extractable, mean visualization, 0-20 cm")
+        Map.addLayer(raw.select(1).sldStyle(mean_20_50), {},"Calcium, extractable, mean visualization, 20-50 cm")
+        Map.addLayer(raw.select(2).sldStyle(stdev_0_20), {},"Calcium, extractable, stdev visualization, 0-20 cm")
+        Map.addLayer(raw.select(3).sldStyle(stdev_20_50), {},"Calcium, extractable, stdev visualization, 20-50 cm")
+        converted = raw.divide(10).exp().subtract(1)
+        visualization = {"min": 100, "max": 2000}
+        Map.setCenter(25, -3, 2)
+        Map.addLayer(converted.select(0), visualization, "Calcium, extractable, mean, 0-20 cm")
+
+    elif cod == "ISDASOIL/Africa/v1/carbon_organic":
+        mean_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#000004" label="0-2.3" opacity="1" quantity="12"/>
+        <ColorMapEntry color="#0C0927" label="2.3-3.5" opacity="1" quantity="15"/>
+        <ColorMapEntry color="#231151" label="3.5-4" opacity="1" quantity="16"/>
+        <ColorMapEntry color="#410F75" label="4-4.5" opacity="1" quantity="17"/>
+        <ColorMapEntry color="#5F187F" label="4.5-5" opacity="1" quantity="18"/>
+        <ColorMapEntry color="#7B2382" label="5-5.7" opacity="1" quantity="19"/>
+        <ColorMapEntry color="#982D80" label="5.7-6.4" opacity="1" quantity="20"/>
+        <ColorMapEntry color="#B63679" label="6.4-7.2" opacity="1" quantity="21"/>
+        <ColorMapEntry color="#D3436E" label="7.2-8" opacity="1" quantity="22"/>
+        <ColorMapEntry color="#EB5760" label="8-9" opacity="1" quantity="23"/>
+        <ColorMapEntry color="#F8765C" label="9-10" opacity="1" quantity="24"/>
+        <ColorMapEntry color="#FD9969" label="10-11.2" opacity="1" quantity="25"/>
+        <ColorMapEntry color="#FEBA80" label="11.2-12.5" opacity="1" quantity="26"/>
+        <ColorMapEntry color="#FDDC9E" label="12.5-13.9" opacity="1" quantity="27"/>
+        <ColorMapEntry color="#FCFDBF" label="13.9-40" opacity="1" quantity="28"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        mean_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#000004" label="0-2.3" opacity="1" quantity="12"/>
+        <ColorMapEntry color="#0C0927" label="2.3-3.5" opacity="1" quantity="15"/>
+        <ColorMapEntry color="#231151" label="3.5-4" opacity="1" quantity="16"/>
+        <ColorMapEntry color="#410F75" label="4-4.5" opacity="1" quantity="17"/>
+        <ColorMapEntry color="#5F187F" label="4.5-5" opacity="1" quantity="18"/>
+        <ColorMapEntry color="#7B2382" label="5-5.7" opacity="1" quantity="19"/>
+        <ColorMapEntry color="#982D80" label="5.7-6.4" opacity="1" quantity="20"/>
+        <ColorMapEntry color="#B63679" label="6.4-7.2" opacity="1" quantity="21"/>
+        <ColorMapEntry color="#D3436E" label="7.2-8" opacity="1" quantity="22"/>
+        <ColorMapEntry color="#EB5760" label="8-9" opacity="1" quantity="23"/>
+        <ColorMapEntry color="#F8765C" label="9-10" opacity="1" quantity="24"/>
+        <ColorMapEntry color="#FD9969" label="10-11.2" opacity="1" quantity="25"/>
+        <ColorMapEntry color="#FEBA80" label="11.2-12.5" opacity="1" quantity="26"/>
+        <ColorMapEntry color="#FDDC9E" label="12.5-13.9" opacity="1" quantity="27"/>
+        <ColorMapEntry color="#FCFDBF" label="13.9-40" opacity="1" quantity="28"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="2"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="5"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="2"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="5"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        raw = ee.Image("ISDASOIL/Africa/v1/carbon_organic")
+        Map.addLayer(raw.select(0).sldStyle(mean_0_20), {},"Carbon, organic, mean visualization, 0-20 cm")
+        Map.addLayer(raw.select(1).sldStyle(mean_20_50), {},"Carbon, organic, mean visualization, 20-50 cm")
+        Map.addLayer(raw.select(2).sldStyle(stdev_0_20), {},"Carbon, organic, stdev visualization, 0-20 cm")
+        Map.addLayer(raw.select(3).sldStyle(stdev_20_50), {},"Carbon, organic, stdev visualization, 20-50 cm")
+        converted = raw.divide(10).exp().subtract(1)
+        visualization = {"min": 0, "max": 20}
+        Map.setCenter(25, -3, 2)
+        Map.addLayer(converted.select(0), visualization, "Carbon, organic, mean, 0-20 cm")
+
+    elif cod == "ISDASOIL/Africa/v1/carbon_total":
+        mean_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#000004" label="0-2" opacity="1" quantity="11"/>
+        <ColorMapEntry color="#0C0927" label="2-5.7" opacity="1" quantity="19"/>
+        <ColorMapEntry color="#231151" label="5.7-10" opacity="1" quantity="24"/>
+        <ColorMapEntry color="#410F75" label="10-12.5" opacity="1" quantity="26"/>
+        <ColorMapEntry color="#5F187F" label="12.5-13.9" opacity="1" quantity="27"/>
+        <ColorMapEntry color="#7B2382" label="13.9-15.4" opacity="1" quantity="28"/>
+        <ColorMapEntry color="#982D80" label="15.4-17.2" opacity="1" quantity="29"/>
+        <ColorMapEntry color="#B63679" label="17.2-19.1" opacity="1" quantity="30"/>
+        <ColorMapEntry color="#D3436E" label="19.1-21.2" opacity="1" quantity="31"/>
+        <ColorMapEntry color="#EB5760" label="21.2-23.5" opacity="1" quantity="32"/>
+        <ColorMapEntry color="#F8765C" label="23.5-26.1" opacity="1" quantity="33"/>
+        <ColorMapEntry color="#FD9969" label="26.1-29" opacity="1" quantity="34"/>
+        <ColorMapEntry color="#FEBA80" label="29-32.1" opacity="1" quantity="35"/>
+        <ColorMapEntry color="#FDDC9E" label="32.1-35.6" opacity="1" quantity="36"/>
+        <ColorMapEntry color="#FCFDBF" label="35.6-40" opacity="1" quantity="39"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        mean_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#000004" label="0-2" opacity="1" quantity="11"/>
+        <ColorMapEntry color="#0C0927" label="2-5.7" opacity="1" quantity="19"/>
+        <ColorMapEntry color="#231151" label="5.7-10" opacity="1" quantity="24"/>
+        <ColorMapEntry color="#410F75" label="10-12.5" opacity="1" quantity="26"/>
+        <ColorMapEntry color="#5F187F" label="12.5-13.9" opacity="1" quantity="27"/>
+        <ColorMapEntry color="#7B2382" label="13.9-15.4" opacity="1" quantity="28"/>
+        <ColorMapEntry color="#982D80" label="15.4-17.2" opacity="1" quantity="29"/>
+        <ColorMapEntry color="#B63679" label="17.2-19.1" opacity="1" quantity="30"/>
+        <ColorMapEntry color="#D3436E" label="19.1-21.2" opacity="1" quantity="31"/>
+        <ColorMapEntry color="#EB5760" label="21.2-23.5" opacity="1" quantity="32"/>
+        <ColorMapEntry color="#F8765C" label="23.5-26.1" opacity="1" quantity="33"/>
+        <ColorMapEntry color="#FD9969" label="26.1-29" opacity="1" quantity="34"/>
+        <ColorMapEntry color="#FEBA80" label="29-32.1" opacity="1" quantity="35"/>
+        <ColorMapEntry color="#FDDC9E" label="32.1-35.6" opacity="1" quantity="36"/>
+        <ColorMapEntry color="#FCFDBF" label="35.6-40" opacity="1" quantity="39"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="5"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="6"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="5"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="6"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        raw = ee.Image("ISDASOIL/Africa/v1/carbon_total")
+        Map.addLayer(raw.select(0).sldStyle(mean_0_20), {},"Carbon, total, mean visualization, 0-20 cm")
+        Map.addLayer(raw.select(1).sldStyle(mean_20_50), {},"Carbon, total, mean visualization, 20-50 cm")
+        Map.addLayer(raw.select(2).sldStyle(stdev_0_20), {},"Carbon, total, stdev visualization, 0-20 cm")
+        Map.addLayer(raw.select(3).sldStyle(stdev_20_50), {},"Carbon, total, stdev visualization, 20-50 cm")
+        converted = raw.divide(10).exp().subtract(1)
+        visualization = {"min": 0, "max": 60}
+        Map.setCenter(25, -3, 2)
+        Map.addLayer(converted.select(0), visualization, "Carbon, total, mean, 0-20 cm")
+
+    elif cod == "ISDASOIL/Africa/v1/cation_exchange_capacity":
+        mean_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#000004" label="0-3.5" opacity="1" quantity="15"/>
+        <ColorMapEntry color="#0C0927" label="3.5-4.5" opacity="1" quantity="17"/>
+        <ColorMapEntry color="#231151" label="4.5-5" opacity="1" quantity="18"/>
+        <ColorMapEntry color="#410F75" label="5-6.4" opacity="1" quantity="20"/>
+        <ColorMapEntry color="#5F187F" label="6.4-7.2" opacity="1" quantity="21"/>
+        <ColorMapEntry color="#7B2382" label="7.2-8" opacity="1" quantity="22"/>
+        <ColorMapEntry color="#982D80" label="8-9" opacity="1" quantity="23"/>
+        <ColorMapEntry color="#B63679" label="9-10" opacity="1" quantity="24"/>
+        <ColorMapEntry color="#D3436E" label="10-11.2" opacity="1" quantity="25"/>
+        <ColorMapEntry color="#EB5760" label="11.2-12.5" opacity="1" quantity="26"/>
+        <ColorMapEntry color="#F8765C" label="12.5-13.9" opacity="1" quantity="27"/>
+        <ColorMapEntry color="#FD9969" label="13.9-15.4" opacity="1" quantity="28"/>
+        <ColorMapEntry color="#FEBA80" label="15.4-17.2" opacity="1" quantity="29"/>
+        <ColorMapEntry color="#FDDC9E" label="17.2-19.1" opacity="1" quantity="30"/>
+        <ColorMapEntry color="#FCFDBF" label="19.1-130" opacity="1" quantity="31"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        mean_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#000004" label="0-3.5" opacity="1" quantity="15"/>
+        <ColorMapEntry color="#0C0927" label="3.5-4.5" opacity="1" quantity="17"/>
+        <ColorMapEntry color="#231151" label="4.5-5" opacity="1" quantity="18"/>
+        <ColorMapEntry color="#410F75" label="5-6.4" opacity="1" quantity="20"/>
+        <ColorMapEntry color="#5F187F" label="6.4-7.2" opacity="1" quantity="21"/>
+        <ColorMapEntry color="#7B2382" label="7.2-8" opacity="1" quantity="22"/>
+        <ColorMapEntry color="#982D80" label="8-9" opacity="1" quantity="23"/>
+        <ColorMapEntry color="#B63679" label="9-10" opacity="1" quantity="24"/>
+        <ColorMapEntry color="#D3436E" label="10-11.2" opacity="1" quantity="25"/>
+        <ColorMapEntry color="#EB5760" label="11.2-12.5" opacity="1" quantity="26"/>
+        <ColorMapEntry color="#F8765C" label="12.5-13.9" opacity="1" quantity="27"/>
+        <ColorMapEntry color="#FD9969" label="13.9-15.4" opacity="1" quantity="28"/>
+        <ColorMapEntry color="#FEBA80" label="15.4-17.2" opacity="1" quantity="29"/>
+        <ColorMapEntry color="#FDDC9E" label="17.2-19.1" opacity="1" quantity="30"/>
+        <ColorMapEntry color="#FCFDBF" label="19.1-130" opacity="1" quantity="31"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="2"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="5"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="2"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="5"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        raw = ee.Image("ISDASOIL/Africa/v1/cation_exchange_capacity")
+        Map.addLayer(raw.select(0).sldStyle(mean_0_20), {},"Cation exchange capacity, mean visualization, 0-20 cm")
+        Map.addLayer(raw.select(1).sldStyle(mean_20_50), {},"Cation exchange capacity, mean visualization, 20-50 cm")
+        Map.addLayer(raw.select(2).sldStyle(stdev_0_20), {},"Cation exchange capacity, stdev visualization, 0-20 cm")
+        Map.addLayer(raw.select(3).sldStyle(stdev_20_50), {},"Cation exchange capacity, stdev visualization, 20-50 cm")
+        converted = raw.divide(10).exp().subtract(1)
+        visualization = {"min": 0, "max": 25}
+        Map.setCenter(25, -3, 2)
+        Map.addLayer(converted.select(0), visualization, "Cation exchange capacity, mean, 0-20 cm")
+
+    elif cod == "ISDASOIL/Africa/v1/clay_content":
+        mean_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#00204D" label="0-8" opacity="1" quantity="8"/>
+        <ColorMapEntry color="#002D6C" label="8-14" opacity="1" quantity="14"/>
+        <ColorMapEntry color="#16396D" label="14-17" opacity="1" quantity="17"/>
+        <ColorMapEntry color="#36476B" label="17-19" opacity="1" quantity="19"/>
+        <ColorMapEntry color="#4B546C" label="19-21" opacity="1" quantity="21"/>
+        <ColorMapEntry color="#5C616E" label="21-22" opacity="1" quantity="22"/>
+        <ColorMapEntry color="#6C6E72" label="22-24" opacity="1" quantity="24"/>
+        <ColorMapEntry color="#7C7B78" label="24-25" opacity="1" quantity="25"/>
+        <ColorMapEntry color="#8E8A79" label="25-26" opacity="1" quantity="26"/>
+        <ColorMapEntry color="#A09877" label="26-28" opacity="1" quantity="28"/>
+        <ColorMapEntry color="#B3A772" label="28-30" opacity="1" quantity="30"/>
+        <ColorMapEntry color="#C6B66B" label="30-31" opacity="1" quantity="31"/>
+        <ColorMapEntry color="#DBC761" label="31-33" opacity="1" quantity="33"/>
+        <ColorMapEntry color="#F0D852" label="33-36" opacity="1" quantity="36"/>
+        <ColorMapEntry color="#FFEA46" label="36-70" opacity="1" quantity="40"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        mean_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#00204D" label="0-8" opacity="1" quantity="8"/>
+        <ColorMapEntry color="#002D6C" label="8-14" opacity="1" quantity="14"/>
+        <ColorMapEntry color="#16396D" label="14-17" opacity="1" quantity="17"/>
+        <ColorMapEntry color="#36476B" label="17-19" opacity="1" quantity="19"/>
+        <ColorMapEntry color="#4B546C" label="19-21" opacity="1" quantity="21"/>
+        <ColorMapEntry color="#5C616E" label="21-22" opacity="1" quantity="22"/>
+        <ColorMapEntry color="#6C6E72" label="22-24" opacity="1" quantity="24"/>
+        <ColorMapEntry color="#7C7B78" label="24-25" opacity="1" quantity="25"/>
+        <ColorMapEntry color="#8E8A79" label="25-26" opacity="1" quantity="26"/>
+        <ColorMapEntry color="#A09877" label="26-28" opacity="1" quantity="28"/>
+        <ColorMapEntry color="#B3A772" label="28-30" opacity="1" quantity="30"/>
+        <ColorMapEntry color="#C6B66B" label="30-31" opacity="1" quantity="31"/>
+        <ColorMapEntry color="#DBC761" label="31-33" opacity="1" quantity="33"/>
+        <ColorMapEntry color="#F0D852" label="33-36" opacity="1" quantity="36"/>
+        <ColorMapEntry color="#FFEA46" label="36-70" opacity="1" quantity="40"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="2"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="6"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="2"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="6"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        raw = ee.Image("ISDASOIL/Africa/v1/clay_content")
+        Map.addLayer(raw.select(0).sldStyle(mean_0_20), {},"Clay content, mean visualization, 0-20 cm")
+        Map.addLayer(raw.select(1).sldStyle(mean_20_50), {},"Clay content, mean visualization, 20-50 cm")
+        Map.addLayer(raw.select(2).sldStyle(stdev_0_20), {},"Clay content, stdev visualization, 0-20 cm")
+        Map.addLayer(raw.select(3).sldStyle(stdev_20_50), {},"Clay content, stdev visualization, 20-50 cm")
+        converted = raw.divide(10).exp().subtract(1)
+        visualization = {"min": 0, "max": 50}
+        Map.setCenter(25, -3, 2)
+        Map.addLayer(converted.select(0), visualization, "Clay content, mean, 0-20 cm")
+
+    elif cod == "ISDASOIL/Africa/v1/fcc":
+        raw = ee.Image("ISDASOIL/Africa/v1/fcc").select(0)
+        converted = ee.Image(raw.mod(3000).copyProperties(raw))
+        Map.setCenter(25, -3, 2)
+        Map.addLayer(converted, {}, "Fertility Capability Classification")
+
+    elif cod == "ISDASOIL/Africa/v1/iron_extractable":
+        mean_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#0D0887" label="0-6.4" opacity="1" quantity="20"/>
+        <ColorMapEntry color="#350498" label="6.4-13.9" opacity="1" quantity="27"/>
+        <ColorMapEntry color="#5402A3" label="13.9-29" opacity="1" quantity="34"/>
+        <ColorMapEntry color="#7000A8" label="29-35.6" opacity="1" quantity="36"/>
+        <ColorMapEntry color="#8B0AA5" label="35.6-43.7" opacity="1" quantity="38"/>
+        <ColorMapEntry color="#A31E9A" label="43.7-48.4" opacity="1" quantity="39"/>
+        <ColorMapEntry color="#B93289" label="48.4-53.6" opacity="1" quantity="40"/>
+        <ColorMapEntry color="#CC4678" label="53.6-59.3" opacity="1" quantity="41"/>
+        <ColorMapEntry color="#DB5C68" label="59.3-65.7" opacity="1" quantity="42"/>
+        <ColorMapEntry color="#E97158" label="65.7-72.7" opacity="1" quantity="43"/>
+        <ColorMapEntry color="#F48849" label="72.7-80.5" opacity="1" quantity="44"/>
+        <ColorMapEntry color="#FBA139" label="80.5-89" opacity="1" quantity="45"/>
+        <ColorMapEntry color="#FEBC2A" label="89-98.5" opacity="1" quantity="46"/>
+        <ColorMapEntry color="#FADA24" label="98.5-108.9" opacity="1" quantity="47"/>
+        <ColorMapEntry color="#F0F921" label="108.9-1200" opacity="1" quantity="48"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        mean_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#0D0887" label="0-6.4" opacity="1" quantity="20"/>
+        <ColorMapEntry color="#350498" label="6.4-13.9" opacity="1" quantity="27"/>
+        <ColorMapEntry color="#5402A3" label="13.9-29" opacity="1" quantity="34"/>
+        <ColorMapEntry color="#7000A8" label="29-35.6" opacity="1" quantity="36"/>
+        <ColorMapEntry color="#8B0AA5" label="35.6-43.7" opacity="1" quantity="38"/>
+        <ColorMapEntry color="#A31E9A" label="43.7-48.4" opacity="1" quantity="39"/>
+        <ColorMapEntry color="#B93289" label="48.4-53.6" opacity="1" quantity="40"/>
+        <ColorMapEntry color="#CC4678" label="53.6-59.3" opacity="1" quantity="41"/>
+        <ColorMapEntry color="#DB5C68" label="59.3-65.7" opacity="1" quantity="42"/>
+        <ColorMapEntry color="#E97158" label="65.7-72.7" opacity="1" quantity="43"/>
+        <ColorMapEntry color="#F48849" label="72.7-80.5" opacity="1" quantity="44"/>
+        <ColorMapEntry color="#FBA139" label="80.5-89" opacity="1" quantity="45"/>
+        <ColorMapEntry color="#FEBC2A" label="89-98.5" opacity="1" quantity="46"/>
+        <ColorMapEntry color="#FADA24" label="98.5-108.9" opacity="1" quantity="47"/>
+        <ColorMapEntry color="#F0F921" label="108.9-1200" opacity="1" quantity="48"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="2"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="6"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="2"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="6"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        raw = ee.Image("ISDASOIL/Africa/v1/iron_extractable")
+        Map.addLayer(raw.select(0).sldStyle(mean_0_20), {},"Iron, extractable, mean visualization, 0-20 cm")
+        Map.addLayer(raw.select(1).sldStyle(mean_20_50), {},"Iron, extractable, mean visualization, 20-50 cm")
+        Map.addLayer(raw.select(2).sldStyle(stdev_0_20), {},"Iron, extractable, stdev visualization, 0-20 cm")
+        Map.addLayer(raw.select(3).sldStyle(stdev_20_50), {},"Iron, extractable, stdev visualization, 20-50 cm")
+        converted = raw.divide(10).exp().subtract(1)
+        visualization = {"min": 0, "max": 140}
+        Map.setCenter(25, -3, 2)
+        Map.addLayer(converted.select(0), visualization, "Iron, extractable, mean, 0-20 cm")
+
+    elif cod == "ISDASOIL/Africa/v1/magnesium_extractable":
+        mean_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#0D0887" label="0-19.1" opacity="1" quantity="30"/>
+        <ColorMapEntry color="#350498" label="19.1-29" opacity="1" quantity="34"/>
+        <ColorMapEntry color="#5402A3" label="29-39.4" opacity="1" quantity="37"/>
+        <ColorMapEntry color="#7000A8" label="39.4-53.6" opacity="1" quantity="40"/>
+        <ColorMapEntry color="#8B0AA5" label="53.6-72.7" opacity="1" quantity="43"/>
+        <ColorMapEntry color="#A31E9A" label="72.7-89" opacity="1" quantity="45"/>
+        <ColorMapEntry color="#B93289" label="89-108.9" opacity="1" quantity="47"/>
+        <ColorMapEntry color="#CC4678" label="108.9-120.5" opacity="1" quantity="48"/>
+        <ColorMapEntry color="#DB5C68" label="120.5-133.3" opacity="1" quantity="49"/>
+        <ColorMapEntry color="#E97158" label="133.3-163" opacity="1" quantity="51"/>
+        <ColorMapEntry color="#F48849" label="163-180.3" opacity="1" quantity="52"/>
+        <ColorMapEntry color="#FBA139" label="180.3-220.4" opacity="1" quantity="54"/>
+        <ColorMapEntry color="#FEBC2A" label="220.4-243.7" opacity="1" quantity="55"/>
+        <ColorMapEntry color="#FADA24" label="243.7-297.9" opacity="1" quantity="57"/>
+        <ColorMapEntry color="#F0F921" label="243.7-1200" opacity="1" quantity="60"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        mean_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#0D0887" label="0-19.1" opacity="1" quantity="30"/>
+        <ColorMapEntry color="#350498" label="19.1-29" opacity="1" quantity="34"/>
+        <ColorMapEntry color="#5402A3" label="29-39.4" opacity="1" quantity="37"/>
+        <ColorMapEntry color="#7000A8" label="39.4-53.6" opacity="1" quantity="40"/>
+        <ColorMapEntry color="#8B0AA5" label="53.6-72.7" opacity="1" quantity="43"/>
+        <ColorMapEntry color="#A31E9A" label="72.7-89" opacity="1" quantity="45"/>
+        <ColorMapEntry color="#B93289" label="89-108.9" opacity="1" quantity="47"/>
+        <ColorMapEntry color="#CC4678" label="108.9-120.5" opacity="1" quantity="48"/>
+        <ColorMapEntry color="#DB5C68" label="120.5-133.3" opacity="1" quantity="49"/>
+        <ColorMapEntry color="#E97158" label="133.3-163" opacity="1" quantity="51"/>
+        <ColorMapEntry color="#F48849" label="163-180.3" opacity="1" quantity="52"/>
+        <ColorMapEntry color="#FBA139" label="180.3-220.4" opacity="1" quantity="54"/>
+        <ColorMapEntry color="#FEBC2A" label="220.4-243.7" opacity="1" quantity="55"/>
+        <ColorMapEntry color="#FADA24" label="243.7-297.9" opacity="1" quantity="57"/>
+        <ColorMapEntry color="#F0F921" label="243.7-1200" opacity="1" quantity="60"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="2"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="5"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="2"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="5"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        raw = ee.Image("ISDASOIL/Africa/v1/magnesium_extractable")
+        Map.addLayer(raw.select(0).sldStyle(mean_0_20), {},"Magnesium, extractable, mean visualization, 0-20 cm")
+        Map.addLayer(raw.select(1).sldStyle(mean_20_50), {},"Magnesium, extractable, mean visualization, 20-50 cm")
+        Map.addLayer(raw.select(2).sldStyle(stdev_0_20), {},"Magnesium, extractable, stdev visualization, 0-20 cm")
+        Map.addLayer(raw.select(3).sldStyle(stdev_20_50), {},"Magnesium, extractable, stdev visualization, 20-50 cm")
+        converted = raw.divide(10).exp().subtract(1)
+        visualization = {"min": 0, "max": 500}
+        Map.setCenter(25, -3, 2)
+        Map.addLayer(converted.select(0), visualization, "Magnesium, extractable, mean, 0-20 cm")
+
+    elif cod == "ISDASOIL/Africa/v1/nitrogen_total":
+        mean_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#000004" label="0-0.2" opacity="1" quantity="20"/>
+        <ColorMapEntry color="#0C0927" label="0.2-0.3" opacity="1" quantity="30"/>
+        <ColorMapEntry color="#231151" label="0.3-0.4" opacity="1" quantity="36"/>
+        <ColorMapEntry color="#410F75" label="0.4-0.5" opacity="1" quantity="43"/>
+        <ColorMapEntry color="#5F187F" label="0.5-0.6" opacity="1" quantity="48"/>
+        <ColorMapEntry color="#7B2382" label="0.6-0.7" opacity="1" quantity="52"/>
+        <ColorMapEntry color="#982D80" label="0.7-0.8" opacity="1" quantity="58"/>
+        <ColorMapEntry color="#B63679" label="0.8-0.9" opacity="1" quantity="64"/>
+        <ColorMapEntry color="#D3436E" label="0.9-1" opacity="1" quantity="67"/>
+        <ColorMapEntry color="#EB5760" label="1-1.1" opacity="1" quantity="75"/>
+        <ColorMapEntry color="#F8765C" label="1.1-1.2" opacity="1" quantity="79"/>
+        <ColorMapEntry color="#FD9969" label="1.2-1.3" opacity="1" quantity="83"/>
+        <ColorMapEntry color="#FEBA80" label="1.3-1.4" opacity="1" quantity="89"/>
+        <ColorMapEntry color="#FDDC9E" label="1.4-1.5" opacity="1" quantity="93"/>
+        <ColorMapEntry color="#FCFDBF" label="1.5-10" opacity="1" quantity="99"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        mean_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#000004" label="0-0.2" opacity="1" quantity="20"/>
+        <ColorMapEntry color="#0C0927" label="0.2-0.3" opacity="1" quantity="30"/>
+        <ColorMapEntry color="#231151" label="0.3-0.4" opacity="1" quantity="36"/>
+        <ColorMapEntry color="#410F75" label="0.4-0.5" opacity="1" quantity="43"/>
+        <ColorMapEntry color="#5F187F" label="0.5-0.6" opacity="1" quantity="48"/>
+        <ColorMapEntry color="#7B2382" label="0.6-0.7" opacity="1" quantity="52"/>
+        <ColorMapEntry color="#982D80" label="0.7-0.8" opacity="1" quantity="58"/>
+        <ColorMapEntry color="#B63679" label="0.8-0.9" opacity="1" quantity="64"/>
+        <ColorMapEntry color="#D3436E" label="0.9-1" opacity="1" quantity="67"/>
+        <ColorMapEntry color="#EB5760" label="1-1.1" opacity="1" quantity="75"/>
+        <ColorMapEntry color="#F8765C" label="1.1-1.2" opacity="1" quantity="79"/>
+        <ColorMapEntry color="#FD9969" label="1.2-1.3" opacity="1" quantity="83"/>
+        <ColorMapEntry color="#FEBA80" label="1.3-1.4" opacity="1" quantity="89"/>
+        <ColorMapEntry color="#FDDC9E" label="1.4-1.5" opacity="1" quantity="93"/>
+        <ColorMapEntry color="#FCFDBF" label="1.5-10" opacity="1" quantity="99"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="8"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="10"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="14"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="60"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="8"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="10"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="14"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="60"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        raw = ee.Image("ISDASOIL/Africa/v1/nitrogen_total")
+        Map.addLayer(raw.select(0).sldStyle(mean_0_20), {},"Nitrogen, total, mean visualization, 0-20 cm")
+        Map.addLayer(raw.select(1).sldStyle(mean_20_50), {},"Nitrogen, total, mean visualization, 20-50 cm")
+        Map.addLayer(raw.select(2).sldStyle(stdev_0_20), {},"Nitrogen, total, stdev visualization, 0-20 cm")
+        Map.addLayer(raw.select(3).sldStyle(stdev_20_50), {},"Nitrogen, total, stdev visualization, 20-50 cm")
+        converted = raw.divide(100).exp().subtract(1)
+        visualization = {"min": 0, "max": 10000}
+        Map.setCenter(25, -3, 2)
+        Map.addLayer(converted.select(0), visualization, "Nitrogen, total, mean, 0-20 cm")
+
+    elif cod == "ISDASOIL/Africa/v1/ph":
+        mean_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#CC0000" label="3.5-4.6" opacity="1" quantity="46"/>
+        <ColorMapEntry color="#FF0000" label="4.6-4.9" opacity="1" quantity="49"/>
+        <ColorMapEntry color="#FF5500" label="4.9-5.2" opacity="1" quantity="52"/>
+        <ColorMapEntry color="#FFAA00" label="5.2-5.4" opacity="1" quantity="54"/>
+        <ColorMapEntry color="#FFFF00" label="5.4-5.5" opacity="1" quantity="55"/>
+        <ColorMapEntry color="#D4FF2B" label="5.5-5.6" opacity="1" quantity="56"/>
+        <ColorMapEntry color="#AAFF55" label="5.6-5.7" opacity="1" quantity="57"/>
+        <ColorMapEntry color="#80FF80" label="5.7-5.9" opacity="1" quantity="59"/>
+        <ColorMapEntry color="#55FFAA" label="5.9-6" opacity="1" quantity="60"/>
+        <ColorMapEntry color="#2BFFD5" label="6-6.2" opacity="1" quantity="62"/>
+        <ColorMapEntry color="#00FFFF" label="6.2-6.3" opacity="1" quantity="63"/>
+        <ColorMapEntry color="#00AAFF" label="6.3-6.6" opacity="1" quantity="66"/>
+        <ColorMapEntry color="#0055FF" label="6.6-6.8" opacity="1" quantity="68"/>
+        <ColorMapEntry color="#0000FF" label="6.8-7.1" opacity="1" quantity="71"/>
+        <ColorMapEntry color="#0000CC" label="7.1-10.5" opacity="1" quantity="76"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        mean_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#CC0000" label="3.5-4.6" opacity="1" quantity="46"/>
+        <ColorMapEntry color="#FF0000" label="4.6-4.9" opacity="1" quantity="49"/>
+        <ColorMapEntry color="#FF5500" label="4.9-5.2" opacity="1" quantity="52"/>
+        <ColorMapEntry color="#FFAA00" label="5.2-5.4" opacity="1" quantity="54"/>
+        <ColorMapEntry color="#FFFF00" label="5.4-5.5" opacity="1" quantity="55"/>
+        <ColorMapEntry color="#D4FF2B" label="5.5-5.6" opacity="1" quantity="56"/>
+        <ColorMapEntry color="#AAFF55" label="5.6-5.7" opacity="1" quantity="57"/>
+        <ColorMapEntry color="#80FF80" label="5.7-5.9" opacity="1" quantity="59"/>
+        <ColorMapEntry color="#55FFAA" label="5.9-6" opacity="1" quantity="60"/>
+        <ColorMapEntry color="#2BFFD5" label="6-6.2" opacity="1" quantity="62"/>
+        <ColorMapEntry color="#00FFFF" label="6.2-6.3" opacity="1" quantity="63"/>
+        <ColorMapEntry color="#00AAFF" label="6.3-6.6" opacity="1" quantity="66"/>
+        <ColorMapEntry color="#0055FF" label="6.6-6.8" opacity="1" quantity="68"/>
+        <ColorMapEntry color="#0000FF" label="6.8-7.1" opacity="1" quantity="71"/>
+        <ColorMapEntry color="#0000CC" label="7.1-10.5" opacity="1" quantity="76"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="2"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="5"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="2"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="5"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        raw = ee.Image("ISDASOIL/Africa/v1/ph")
+        Map.addLayer(raw.select(0).sldStyle(mean_0_20), {},"ph, mean visualization, 0-20 cm")
+        Map.addLayer(raw.select(1).sldStyle(mean_20_50), {},"ph, mean visualization, 20-50 cm")
+        Map.addLayer(raw.select(2).sldStyle(stdev_0_20), {},"ph, stdev visualization, 0-20 cm")
+        Map.addLayer(raw.select(3).sldStyle(stdev_20_50), {},"ph, stdev visualization, 20-50 cm")
+        converted = raw.divide(10)
+        visualization = {"min": 4, "max": 8}
+        Map.setCenter(25, -3, 2)
+        Map.addLayer(converted.select(0), visualization, "ph, mean, 0-20 cm")
+
+    elif cod == "ISDASOIL/Africa/v1/phosphorus_extractable":
+        mean_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#0D0887" label="0-2.7" opacity="1" quantity="13"/>
+        <ColorMapEntry color="#350498" label="2.7-3" opacity="1" quantity="14"/>
+        <ColorMapEntry color="#5402A3" label="3-3.5" opacity="1" quantity="15"/>
+        <ColorMapEntry color="#7000A8" label="3.5-4" opacity="1" quantity="16"/>
+        <ColorMapEntry color="#8B0AA5" label="4-4.5" opacity="1" quantity="17"/>
+        <ColorMapEntry color="#A31E9A" label="4.5-5" opacity="1" quantity="18"/>
+        <ColorMapEntry color="#B93289" label="5-5.7" opacity="1" quantity="19"/>
+        <ColorMapEntry color="#CC4678" label="5.7-6.4" opacity="1" quantity="20"/>
+        <ColorMapEntry color="#DB5C68" label="6.4-7.2" opacity="1" quantity="21"/>
+        <ColorMapEntry color="#E97158" label="7.2-8" opacity="1" quantity="22"/>
+        <ColorMapEntry color="#F48849" label="8-9" opacity="1" quantity="23"/>
+        <ColorMapEntry color="#FBA139" label="9-10" opacity="1" quantity="24"/>
+        <ColorMapEntry color="#FEBC2A" label="10-11.2" opacity="1" quantity="25"/>
+        <ColorMapEntry color="#FADA24" label="11.2-12.5" opacity="1" quantity="26"/>
+        <ColorMapEntry color="#F0F921" label="12.5-125" opacity="1" quantity="27"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        mean_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#0D0887" label="0-2.7" opacity="1" quantity="13"/>
+        <ColorMapEntry color="#350498" label="2.7-3" opacity="1" quantity="14"/>
+        <ColorMapEntry color="#5402A3" label="3-3.5" opacity="1" quantity="15"/>
+        <ColorMapEntry color="#7000A8" label="3.5-4" opacity="1" quantity="16"/>
+        <ColorMapEntry color="#8B0AA5" label="4-4.5" opacity="1" quantity="17"/>
+        <ColorMapEntry color="#A31E9A" label="4.5-5" opacity="1" quantity="18"/>
+        <ColorMapEntry color="#B93289" label="5-5.7" opacity="1" quantity="19"/>
+        <ColorMapEntry color="#CC4678" label="5.7-6.4" opacity="1" quantity="20"/>
+        <ColorMapEntry color="#DB5C68" label="6.4-7.2" opacity="1" quantity="21"/>
+        <ColorMapEntry color="#E97158" label="7.2-8" opacity="1" quantity="22"/>
+        <ColorMapEntry color="#F48849" label="8-9" opacity="1" quantity="23"/>
+        <ColorMapEntry color="#FBA139" label="9-10" opacity="1" quantity="24"/>
+        <ColorMapEntry color="#FEBC2A" label="10-11.2" opacity="1" quantity="25"/>
+        <ColorMapEntry color="#FADA24" label="11.2-12.5" opacity="1" quantity="26"/>
+        <ColorMapEntry color="#F0F921" label="12.5-125" opacity="1" quantity="27"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="2"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="5"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="2"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="5"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        raw = ee.Image("ISDASOIL/Africa/v1/phosphorus_extractable")
+        Map.addLayer(raw.select(0).sldStyle(mean_0_20), {},"Phosphorus extractable, mean visualization, 0-20 cm")
+        Map.addLayer(raw.select(1).sldStyle(mean_20_50), {},"Phosphorus extractable, mean visualization, 20-50 cm")
+        Map.addLayer(raw.select(2).sldStyle(stdev_0_20), {},"Phosphorus extractable, stdev visualization, 0-20 cm")
+        Map.addLayer(raw.select(3).sldStyle(stdev_20_50), {},"Phosphorus extractable, stdev visualization, 20-50 cm")
+        converted = raw.divide(10).exp().subtract(1)
+        visualization = {"min": 0, "max": 15}
+        Map.setCenter(25, -3, 2)
+        Map.addLayer(converted.select(0), visualization, "Phosphorus extractable, mean, 0-20 cm")
+
+    elif cod == "ISDASOIL/Africa/v1/potassium_extractable":
+        mean_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#0D0887" label="0-32.1" opacity="1" quantity="35"/>
+        <ColorMapEntry color="#350498" label="32.1-43.7" opacity="1" quantity="38"/>
+        <ColorMapEntry color="#5402A3" label="43.7-48.4" opacity="1" quantity="39"/>
+        <ColorMapEntry color="#7000A8" label="48.4-53.6" opacity="1" quantity="40"/>
+        <ColorMapEntry color="#8B0AA5" label="53.6-59.3" opacity="1" quantity="41"/>
+        <ColorMapEntry color="#A31E9A" label="59.3-65.7" opacity="1" quantity="42"/>
+        <ColorMapEntry color="#B93289" label="65.7-72.7" opacity="1" quantity="43"/>
+        <ColorMapEntry color="#CC4678" label="72.7-89" opacity="1" quantity="45"/>
+        <ColorMapEntry color="#DB5C68" label="89-98.5" opacity="1" quantity="46"/>
+        <ColorMapEntry color="#E97158" label="98.5-108.9" opacity="1" quantity="47"/>
+        <ColorMapEntry color="#F48849" label="108.9-120.5" opacity="1" quantity="48"/>
+        <ColorMapEntry color="#FBA139" label="120.5-133.3" opacity="1" quantity="49"/>
+        <ColorMapEntry color="#FEBC2A" label="133.3-163" opacity="1" quantity="51"/>
+        <ColorMapEntry color="#FADA24" label="163-199.3" opacity="1" quantity="53"/>
+        <ColorMapEntry color="#F0F921" label="163-1200" opacity="1" quantity="55"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        mean_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#0D0887" label="0-32.1" opacity="1" quantity="35"/>
+        <ColorMapEntry color="#350498" label="32.1-43.7" opacity="1" quantity="38"/>
+        <ColorMapEntry color="#5402A3" label="43.7-48.4" opacity="1" quantity="39"/>
+        <ColorMapEntry color="#7000A8" label="48.4-53.6" opacity="1" quantity="40"/>
+        <ColorMapEntry color="#8B0AA5" label="53.6-59.3" opacity="1" quantity="41"/>
+        <ColorMapEntry color="#A31E9A" label="59.3-65.7" opacity="1" quantity="42"/>
+        <ColorMapEntry color="#B93289" label="65.7-72.7" opacity="1" quantity="43"/>
+        <ColorMapEntry color="#CC4678" label="72.7-89" opacity="1" quantity="45"/>
+        <ColorMapEntry color="#DB5C68" label="89-98.5" opacity="1" quantity="46"/>
+        <ColorMapEntry color="#E97158" label="98.5-108.9" opacity="1" quantity="47"/>
+        <ColorMapEntry color="#F48849" label="108.9-120.5" opacity="1" quantity="48"/>
+        <ColorMapEntry color="#FBA139" label="120.5-133.3" opacity="1" quantity="49"/>
+        <ColorMapEntry color="#FEBC2A" label="133.3-163" opacity="1" quantity="51"/>
+        <ColorMapEntry color="#FADA24" label="163-199.3" opacity="1" quantity="53"/>
+        <ColorMapEntry color="#F0F921" label="163-1200" opacity="1" quantity="55"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="2"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="5"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="2"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="5"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        raw = ee.Image("ISDASOIL/Africa/v1/potassium_extractable")
+        Map.addLayer(raw.select(0).sldStyle(mean_0_20), {},"Potassium extractable, mean visualization, 0-20 cm")
+        Map.addLayer(raw.select(1).sldStyle(mean_20_50), {},"Potassium extractable, mean visualization, 20-50 cm")
+        Map.addLayer(raw.select(2).sldStyle(stdev_0_20), {},"Potassium extractable, stdev visualization, 0-20 cm")
+        Map.addLayer(raw.select(3).sldStyle(stdev_20_50), {},"Potassium extractable, stdev visualization, 20-50 cm")
+        converted = raw.divide(10).exp().subtract(1)
+        visualization = {"min": 0, "max": 250}
+        Map.setCenter(25, -3, 2)
+        Map.addLayer(converted.select(0), visualization, "Potassium extractable, mean, 0-20 cm")
+
+    elif cod == "ISDASOIL/Africa/v1/sand_content":
+        mean_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#00204D" label="0-31" opacity="1" quantity="31"/>
+        <ColorMapEntry color="#002D6C" label="31-39" opacity="1" quantity="39"/>
+        <ColorMapEntry color="#16396D" label="39-43" opacity="1" quantity="43"/>
+        <ColorMapEntry color="#36476B" label="43-46" opacity="1" quantity="46"/>
+        <ColorMapEntry color="#4B546C" label="46-49" opacity="1" quantity="49"/>
+        <ColorMapEntry color="#5C616E" label="49-52" opacity="1" quantity="52"/>
+        <ColorMapEntry color="#6C6E72" label="52-54" opacity="1" quantity="54"/>
+        <ColorMapEntry color="#7C7B78" label="54-56" opacity="1" quantity="56"/>
+        <ColorMapEntry color="#8E8A79" label="56-58" opacity="1" quantity="58"/>
+        <ColorMapEntry color="#A09877" label="58-60" opacity="1" quantity="60"/>
+        <ColorMapEntry color="#B3A772" label="60-63" opacity="1" quantity="63"/>
+        <ColorMapEntry color="#C6B66B" label="63-65" opacity="1" quantity="65"/>
+        <ColorMapEntry color="#DBC761" label="65-68" opacity="1" quantity="68"/>
+        <ColorMapEntry color="#F0D852" label="68-71" opacity="1" quantity="71"/>
+        <ColorMapEntry color="#FFEA46" label="71-100" opacity="1" quantity="75"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        mean_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#00204D" label="0-31" opacity="1" quantity="31"/>
+        <ColorMapEntry color="#002D6C" label="31-39" opacity="1" quantity="39"/>
+        <ColorMapEntry color="#16396D" label="39-43" opacity="1" quantity="43"/>
+        <ColorMapEntry color="#36476B" label="43-46" opacity="1" quantity="46"/>
+        <ColorMapEntry color="#4B546C" label="46-49" opacity="1" quantity="49"/>
+        <ColorMapEntry color="#5C616E" label="49-52" opacity="1" quantity="52"/>
+        <ColorMapEntry color="#6C6E72" label="52-54" opacity="1" quantity="54"/>
+        <ColorMapEntry color="#7C7B78" label="54-56" opacity="1" quantity="56"/>
+        <ColorMapEntry color="#8E8A79" label="56-58" opacity="1" quantity="58"/>
+        <ColorMapEntry color="#A09877" label="58-60" opacity="1" quantity="60"/>
+        <ColorMapEntry color="#B3A772" label="60-63" opacity="1" quantity="63"/>
+        <ColorMapEntry color="#C6B66B" label="63-65" opacity="1" quantity="65"/>
+        <ColorMapEntry color="#DBC761" label="65-68" opacity="1" quantity="68"/>
+        <ColorMapEntry color="#F0D852" label="68-71" opacity="1" quantity="71"/>
+        <ColorMapEntry color="#FFEA46" label="71-100" opacity="1" quantity="75"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="2"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="6"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="7"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="2"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="6"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="7"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        raw = ee.Image("ISDASOIL/Africa/v1/sand_content")
+        Map.addLayer(raw.select(0).sldStyle(mean_0_20), {},"Sand content, mean visualization, 0-20 cm")
+        Map.addLayer(raw.select(1).sldStyle(mean_20_50), {},"Sand content, mean visualization, 20-50 cm")
+        Map.addLayer(raw.select(2).sldStyle(stdev_0_20), {},"Sand content, stdev visualization, 0-20 cm")
+        Map.addLayer(raw.select(3).sldStyle(stdev_20_50), {},"Sand content, stdev visualization, 20-50 cm")
+        converted = raw.divide(10).exp().subtract(1)
+        visualization = {"min": 0, "max": 3000}
+        Map.setCenter(25, -3, 2)
+        Map.addLayer(converted.select(0), visualization, "Sand content, mean, 0-20 cm")
+
+    elif cod == "ISDASOIL/Africa/v1/silt_content":
+        mean_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#00204D" label="0-7" opacity="1" quantity="7"/>
+        <ColorMapEntry color="#002D6C" label="7-9" opacity="1" quantity="9"/>
+        <ColorMapEntry color="#16396D" label="9-10" opacity="1" quantity="10"/>
+        <ColorMapEntry color="#36476B" label="10-11" opacity="1" quantity="11"/>
+        <ColorMapEntry color="#4B546C" label="11-12" opacity="1" quantity="12"/>
+        <ColorMapEntry color="#5C616E" label="12-13" opacity="1" quantity="13"/>
+        <ColorMapEntry color="#6C6E72" label="13-14" opacity="1" quantity="14"/>
+        <ColorMapEntry color="#7C7B78" label="14-15" opacity="1" quantity="15"/>
+        <ColorMapEntry color="#8E8A79" label="15-16" opacity="1" quantity="16"/>
+        <ColorMapEntry color="#A09877" label="16-17" opacity="1" quantity="17"/>
+        <ColorMapEntry color="#B3A772" label="17-18" opacity="1" quantity="18"/>
+        <ColorMapEntry color="#C6B66B" label="18-19" opacity="1" quantity="19"/>
+        <ColorMapEntry color="#DBC761" label="19-20" opacity="1" quantity="20"/>
+        <ColorMapEntry color="#F0D852" label="20-22" opacity="1" quantity="22"/>
+        <ColorMapEntry color="#FFEA46" label="22-70" opacity="1" quantity="24"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        mean_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#00204D" label="0-7" opacity="1" quantity="7"/>
+        <ColorMapEntry color="#002D6C" label="7-9" opacity="1" quantity="9"/>
+        <ColorMapEntry color="#16396D" label="9-10" opacity="1" quantity="10"/>
+        <ColorMapEntry color="#36476B" label="10-11" opacity="1" quantity="11"/>
+        <ColorMapEntry color="#4B546C" label="11-12" opacity="1" quantity="12"/>
+        <ColorMapEntry color="#5C616E" label="12-13" opacity="1" quantity="13"/>
+        <ColorMapEntry color="#6C6E72" label="13-14" opacity="1" quantity="14"/>
+        <ColorMapEntry color="#7C7B78" label="14-15" opacity="1" quantity="15"/>
+        <ColorMapEntry color="#8E8A79" label="15-16" opacity="1" quantity="16"/>
+        <ColorMapEntry color="#A09877" label="16-17" opacity="1" quantity="17"/>
+        <ColorMapEntry color="#B3A772" label="17-18" opacity="1" quantity="18"/>
+        <ColorMapEntry color="#C6B66B" label="18-19" opacity="1" quantity="19"/>
+        <ColorMapEntry color="#DBC761" label="19-20" opacity="1" quantity="20"/>
+        <ColorMapEntry color="#F0D852" label="20-22" opacity="1" quantity="22"/>
+        <ColorMapEntry color="#FFEA46" label="22-70" opacity="1" quantity="24"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="2"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="4.19000000000005"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="2"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="4.19000000000005"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        raw = ee.Image("ISDASOIL/Africa/v1/silt_content")
+        Map.addLayer(raw.select(0).sldStyle(mean_0_20), {},"Silt content, mean visualization, 0-20 cm")
+        Map.addLayer(raw.select(1).sldStyle(mean_20_50), {},"Silt content, mean visualization, 20-50 cm")
+        Map.addLayer(raw.select(2).sldStyle(stdev_0_20), {},"Silt content, stdev visualization, 0-20 cm")
+        Map.addLayer(raw.select(3).sldStyle(stdev_20_50), {},"Silt content, stdev visualization, 20-50 cm")
+        converted = raw.divide(10).exp().subtract(1)
+        visualization = {"min": 0, "max": 15}
+        Map.setCenter(25, -3, 2)
+        Map.addLayer(converted.select(0), visualization, "Silt content, mean, 0-20 cm")
+
+    elif cod == "ISDASOIL/Africa/v1/stone_content":
+        mean_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#00204D" label="0-0.1" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#002D6C" label="0.1-0.3" opacity="1" quantity="3"/>
+        <ColorMapEntry color="#16396D" label="0.3-0.5" opacity="1" quantity="4"/>
+        <ColorMapEntry color="#36476B" label="0.5-0.6" opacity="1" quantity="5"/>
+        <ColorMapEntry color="#4B546C" label="0.6-0.8" opacity="1" quantity="6"/>
+        <ColorMapEntry color="#5C616E" label="0.8-1" opacity="1" quantity="7"/>
+        <ColorMapEntry color="#6C6E72" label="1-1.2" opacity="1" quantity="8"/>
+        <ColorMapEntry color="#7C7B78" label="1.2-1.5" opacity="1" quantity="9"/>
+        <ColorMapEntry color="#8E8A79" label="1.5-1.7" opacity="1" quantity="10"/>
+        <ColorMapEntry color="#A09877" label="1.7-2" opacity="1" quantity="11"/>
+        <ColorMapEntry color="#B3A772" label="2-2.3" opacity="1" quantity="12"/>
+        <ColorMapEntry color="#C6B66B" label="2.3-2.7" opacity="1" quantity="13"/>
+        <ColorMapEntry color="#DBC761" label="2.7-3.1" opacity="1" quantity="14"/>
+        <ColorMapEntry color="#F0D852" label="3.1-3.5" opacity="1" quantity="15"/>
+        <ColorMapEntry color="#FFEA46" label="3.5-80" opacity="1" quantity="16"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        mean_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#00204D" label="0-0.1" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#002D6C" label="0.1-0.3" opacity="1" quantity="3"/>
+        <ColorMapEntry color="#16396D" label="0.3-0.5" opacity="1" quantity="4"/>
+        <ColorMapEntry color="#36476B" label="0.5-0.6" opacity="1" quantity="5"/>
+        <ColorMapEntry color="#4B546C" label="0.6-0.8" opacity="1" quantity="6"/>
+        <ColorMapEntry color="#5C616E" label="0.8-1" opacity="1" quantity="7"/>
+        <ColorMapEntry color="#6C6E72" label="1-1.2" opacity="1" quantity="8"/>
+        <ColorMapEntry color="#7C7B78" label="1.2-1.5" opacity="1" quantity="9"/>
+        <ColorMapEntry color="#8E8A79" label="1.5-1.7" opacity="1" quantity="10"/>
+        <ColorMapEntry color="#A09877" label="1.7-2" opacity="1" quantity="11"/>
+        <ColorMapEntry color="#B3A772" label="2-2.3" opacity="1" quantity="12"/>
+        <ColorMapEntry color="#C6B66B" label="2.3-2.7" opacity="1" quantity="13"/>
+        <ColorMapEntry color="#DBC761" label="2.7-3.1" opacity="1" quantity="14"/>
+        <ColorMapEntry color="#F0D852" label="3.1-3.5" opacity="1" quantity="15"/>
+        <ColorMapEntry color="#FFEA46" label="3.5-80" opacity="1" quantity="16"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="2"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="5"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="2"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="5"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        raw = ee.Image("ISDASOIL/Africa/v1/stone_content")
+        Map.addLayer(raw.select(0).sldStyle(mean_0_20), {},"Stone content, mean visualization, 0-20 cm")
+        Map.addLayer(raw.select(1).sldStyle(mean_20_50), {},"Stone content, mean visualization, 20-50 cm")
+        Map.addLayer(raw.select(2).sldStyle(stdev_0_20), {},"Stone content, stdev visualization, 0-20 cm")
+        Map.addLayer(raw.select(3).sldStyle(stdev_20_50), {},"Stone content, stdev visualization, 20-50 cm")
+        converted = raw.divide(10).exp().subtract(1)
+        visualization = {"min": 0, "max": 6}
+        Map.setCenter(25, -3, 2)
+        Map.addLayer(converted.select(0), visualization, "Stone content, mean, 0-20 cm")
+
+    elif cod == "ISDASOIL/Africa/v1/sulphur_extractable":
+        mean_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#0D0887" label="0-2.3" opacity="1" quantity="12"/>
+        <ColorMapEntry color="#350498" label="2.3-3.1" opacity="1" quantity="14"/>
+        <ColorMapEntry color="#5402A3" label="3.1-3.5" opacity="1" quantity="15"/>
+        <ColorMapEntry color="#7000A8" label="3.5-4" opacity="1" quantity="16"/>
+        <ColorMapEntry color="#8B0AA5" label="4-5" opacity="1" quantity="18"/>
+        <ColorMapEntry color="#A31E9A" label="5-5.7" opacity="1" quantity="19"/>
+        <ColorMapEntry color="#B93289" label="5.7-6.4" opacity="1" quantity="20"/>
+        <ColorMapEntry color="#CC4678" label="6.4-7.2" opacity="1" quantity="21"/>
+        <ColorMapEntry color="#DB5C68" label="7.2-8" opacity="1" quantity="22"/>
+        <ColorMapEntry color="#E97158" label="8-9" opacity="1" quantity="23"/>
+        <ColorMapEntry color="#F48849" label="9-10" opacity="1" quantity="24"/>
+        <ColorMapEntry color="#FBA139" label="10-11.2" opacity="1" quantity="25"/>
+        <ColorMapEntry color="#FEBC2A" label="11.2-12.5" opacity="1" quantity="26"/>
+        <ColorMapEntry color="#FADA24" label="12.5-15.4" opacity="1" quantity="28"/>
+        <ColorMapEntry color="#F0F921" label="15.4-125" opacity="1" quantity="30"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        mean_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#0D0887" label="0-2.3" opacity="1" quantity="12"/>
+        <ColorMapEntry color="#350498" label="2.3-3.1" opacity="1" quantity="14"/>
+        <ColorMapEntry color="#5402A3" label="3.1-3.5" opacity="1" quantity="15"/>
+        <ColorMapEntry color="#7000A8" label="3.5-4" opacity="1" quantity="16"/>
+        <ColorMapEntry color="#8B0AA5" label="4-5" opacity="1" quantity="18"/>
+        <ColorMapEntry color="#A31E9A" label="5-5.7" opacity="1" quantity="19"/>
+        <ColorMapEntry color="#B93289" label="5.7-6.4" opacity="1" quantity="20"/>
+        <ColorMapEntry color="#CC4678" label="6.4-7.2" opacity="1" quantity="21"/>
+        <ColorMapEntry color="#DB5C68" label="7.2-8" opacity="1" quantity="22"/>
+        <ColorMapEntry color="#E97158" label="8-9" opacity="1" quantity="23"/>
+        <ColorMapEntry color="#F48849" label="9-10" opacity="1" quantity="24"/>
+        <ColorMapEntry color="#FBA139" label="10-11.2" opacity="1" quantity="25"/>
+        <ColorMapEntry color="#FEBC2A" label="11.2-12.5" opacity="1" quantity="26"/>
+        <ColorMapEntry color="#FADA24" label="12.5-15.4" opacity="1" quantity="28"/>
+        <ColorMapEntry color="#F0F921" label="15.4-125" opacity="1" quantity="30"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="6"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="14"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="6"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="14"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        raw = ee.Image("ISDASOIL/Africa/v1/sulphur_extractable")
+        Map.addLayer(raw.select(0).sldStyle(mean_0_20), {},"Sulphur extractable, mean visualization, 0-20 cm")
+        Map.addLayer(raw.select(1).sldStyle(mean_20_50), {},"Sulphur extractable, mean visualization, 20-50 cm")
+        Map.addLayer(raw.select(2).sldStyle(stdev_0_20), {},"Sulphur extractable, stdev visualization, 0-20 cm")
+        Map.addLayer(raw.select(3).sldStyle(stdev_20_50), {},"Sulphur extractable, stdev visualization, 20-50 cm")
+        converted = raw.divide(10).exp().subtract(1)
+        visualization = {"min": 0, "max": 20}
+        Map.setCenter(25, -3, 2)
+        Map.addLayer(converted.select(0), visualization, "Sulphur extractable, mean, 0-20 cm")
+
+
+
+    elif cod == "ISDASOIL/Africa/v1/texture_class":
+        raw = ee.Image("ISDASOIL/Africa/v1/texture_class")
+        Map.addLayer(raw.select(0), {}, "Texture class, 0-20 cm")
+        Map.addLayer(raw.select(1), {}, "Texture class, 20-50 cm")
+        Map.setCenter(25, -3, 2)
+
+    elif cod == "ISDASOIL/Africa/v1/zinc_extractable":
+        mean_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#0D0887" label="0-0.6" opacity="1" quantity="5"/>
+        <ColorMapEntry color="#350498" label="0.6-0.8" opacity="1" quantity="6"/>
+        <ColorMapEntry color="#5402A3" label="0.8-1" opacity="1" quantity="7"/>
+        <ColorMapEntry color="#7000A8" label="1-1.2" opacity="1" quantity="8"/>
+        <ColorMapEntry color="#8B0AA5" label="1.2-1.5" opacity="1" quantity="9"/>
+        <ColorMapEntry color="#A31E9A" label="1.5-1.7" opacity="1" quantity="10"/>
+        <ColorMapEntry color="#B93289" label="1.7-2" opacity="1" quantity="11"/>
+        <ColorMapEntry color="#CC4678" label="2-2.3" opacity="1" quantity="12"/>
+        <ColorMapEntry color="#DB5C68" label="2.3-2.7" opacity="1" quantity="13"/>
+        <ColorMapEntry color="#E97158" label="2.7-3.1" opacity="1" quantity="14"/>
+        <ColorMapEntry color="#F48849" label="3.1-3.5" opacity="1" quantity="15"/>
+        <ColorMapEntry color="#FBA139" label="3.5-4" opacity="1" quantity="16"/>
+        <ColorMapEntry color="#FEBC2A" label="4-4.5" opacity="1" quantity="17"/>
+        <ColorMapEntry color="#FADA24" label="4.5-5" opacity="1" quantity="18"/>
+        <ColorMapEntry color="#F0F921" label="5-125" opacity="1" quantity="19"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        mean_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#0D0887" label="0-0.6" opacity="1" quantity="5"/>
+        <ColorMapEntry color="#350498" label="0.6-0.8" opacity="1" quantity="6"/>
+        <ColorMapEntry color="#5402A3" label="0.8-1" opacity="1" quantity="7"/>
+        <ColorMapEntry color="#7000A8" label="1-1.2" opacity="1" quantity="8"/>
+        <ColorMapEntry color="#8B0AA5" label="1.2-1.5" opacity="1" quantity="9"/>
+        <ColorMapEntry color="#A31E9A" label="1.5-1.7" opacity="1" quantity="10"/>
+        <ColorMapEntry color="#B93289" label="1.7-2" opacity="1" quantity="11"/>
+        <ColorMapEntry color="#CC4678" label="2-2.3" opacity="1" quantity="12"/>
+        <ColorMapEntry color="#DB5C68" label="2.3-2.7" opacity="1" quantity="13"/>
+        <ColorMapEntry color="#E97158" label="2.7-3.1" opacity="1" quantity="14"/>
+        <ColorMapEntry color="#F48849" label="3.1-3.5" opacity="1" quantity="15"/>
+        <ColorMapEntry color="#FBA139" label="3.5-4" opacity="1" quantity="16"/>
+        <ColorMapEntry color="#FEBC2A" label="4-4.5" opacity="1" quantity="17"/>
+        <ColorMapEntry color="#FADA24" label="4.5-5" opacity="1" quantity="18"/>
+        <ColorMapEntry color="#F0F921" label="5-125" opacity="1" quantity="19"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_0_20 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="2"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="5"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        stdev_20_50 = """
+        <RasterSymbolizer>
+        <ColorMap type="ramp">
+        <ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>
+        <ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="2"/>
+        <ColorMapEntry color="#20908d" label=" " opacity="1" quantity="3"/>
+        <ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="4"/>
+        <ColorMapEntry color="#440154" label="high" opacity="1" quantity="5"/>
+        </ColorMap>
+        <ContrastEnhancement/>
+        </RasterSymbolizer> """
+        raw = ee.Image("ISDASOIL/Africa/v1/zinc_extractable")
+        Map.addLayer(raw.select(0).sldStyle(mean_0_20), {},"Zinc, extractable, mean visualization, 0-20 cm")
+        Map.addLayer(raw.select(1).sldStyle(mean_20_50), {},"Zinc, extractable, mean visualization, 20-50 cm")
+        Map.addLayer(raw.select(2).sldStyle(stdev_0_20), {},"Zinc, extractable, stdev visualization, 0-20 cm")
+        Map.addLayer(raw.select(3).sldStyle(stdev_20_50), {},"Zinc, extractable, stdev visualization, 20-50 cm")
+        converted = raw.divide(10).exp().subtract(1)
+        visualization = {"min": 0, "max": 10}
+        Map.setCenter(25, -3, 2)
+        Map.addLayer(converted.select(0), visualization, "Zinc, extractable, mean, 0-20 cm")
+        
+    elif cod == "JAXA/ALOS/AVNIR-2/ORI":
+        dataset = ee.ImageCollection("JAXA/ALOS/AVNIR-2/ORI").filter(ee.Filter.date("2011-01-01", "2011-04-01"))
+        avnir2OriRgb = dataset.select(["B3", "B2", "B1"])
+        avnir2OriRgbVis = {
+        "min": 0.0,
+        "max": 255.0,
+        }
+        Map.setCenter(138.7302, 35.3641, 12)
+        Map.addLayer(avnir2OriRgb, avnir2OriRgbVis, "AVNIR-2 ORI RGB")
+
+    elif cod == "JAXA/ALOS/AW3D30/V3_2":
+        dataset = ee.ImageCollection("JAXA/ALOS/AW3D30/V3_2")
+        elevation = dataset.select("DSM")
+        elevationVis = {
+        "min": 0,
+        "max": 5000,
+        "palette": ["0000ff", "00ffff", "ffff00", "ff0000", "ffffff"]
+        }
+        Map.setCenter(138.73, 35.36, 11)
+        Map.addLayer(elevation, elevationVis, "Elevation")
+        proj = elevation.first().select(0).projection()
+        slopeReprojected = ee.Terrain.slope(elevation.mosaic().setDefaultProjection(proj))
+        Map.addLayer(slopeReprojected, {"min": 0, "max": 45}, "Slope")
+
+    elif cod == "JAXA/ALOS/PALSAR-2/Level2_2/ScanSAR":
+        collection = ee.ImageCollection("JAXA/ALOS/PALSAR-2/Level2_2/ScanSAR").filterBounds(ee.Geometry.Point(143, -5))
+        image = collection.first()
+        Map.addLayer(image.select(["HH"]), {"min": 0, "max": 8000}, "HH polarization")
+        Map.centerObject(image)
+
+    elif cod =="JAXA/ALOS/PALSAR/YEARLY/FNF":
+        dataset = ee.ImageCollection("JAXA/ALOS/PALSAR/YEARLY/FNF").filterDate("2017-01-01", "2017-12-31")
+        forestNonForest = dataset.select("fnf")
+        forestNonForestVis = {
+        "min": 1.0,
+        "max": 3.0,
+        "palette": ["006400", "FEFF99", "0000FF"],
+        }
+        Map.setCenter(136.85, 37.37, 4)
+        Map.addLayer(forestNonForest, forestNonForestVis, "Forest/Non-Forest")
+
+    elif cod == "JAXA/ALOS/PALSAR/YEARLY/FNF4":
+        dataset = ee.ImageCollection("JAXA/ALOS/PALSAR/YEARLY/FNF4").filterDate("2018-01-01", "2018-12-31")
+        forestNonForest = dataset.select("fnf")
+        forestNonForestVis = {
+        "min": 1.0,
+        "max": 4.0,
+        "palette": ["00B200","83EF62","FFFF99","0000FF"],
+        }
+        Map.setCenter(136.85, 37.37, 4)
+        Map.addLayer(forestNonForest, forestNonForestVis, "Forest/Non-Forest")
+
+    elif cod == "JAXA/ALOS/PALSAR/YEARLY/SAR":
+        dataset = ee.ImageCollection("JAXA/ALOS/PALSAR/YEARLY/SAR").filter(ee.Filter.date("2017-01-01", "2018-01-01"))
+        sarHh = dataset.select("HH")
+        sarHhVis = {
+        "min": 0.0,
+        "max": 10000.0,
+        }
+        Map.setCenter(136.85, 37.37, 4)
+        Map.addLayer(sarHh, sarHhVis, "SAR HH")
+
+    elif cod == "JAXA/ALOS/PALSAR/YEARLY/SAR_EPOCH":
+        dataset = ee.ImageCollection("JAXA/ALOS/PALSAR/YEARLY/SAR_EPOCH").filter(ee.Filter.date("2017-01-01", "2018-01-01"))
+        sarHh = dataset.select("HH")
+        sarHhVis = {
+        "min": 0.0,
+        "max": 10000.0,
+        }
+        Map.setCenter(136.85, 37.37, 4)
+        Map.addLayer(sarHh, sarHhVis, "SAR HH")
+
+    elif cod == "JAXA/GCOM-C/L3/LAND/LAI/V1":
+        dataset = ee.ImageCollection("JAXA/GCOM-C/L3/LAND/LAI/V1").filterDate("2020-01-01", "2020-02-01").filter(ee.Filter.eq("SATELLITE_DIRECTION", "D"))
+        dataset = dataset.mean().multiply(0.001)
+        visualization = {
+        "bands": ["LAI_AVE"],
+        "min": -7,
+        "max": 7,
+        "palette": [
+        "040274","040281","0502a3","0502b8","0502ce","0502e6",
+        "0602ff","235cb1","307ef3","269db1","30c8e2","32d3ef",
+        "3be285","3ff38f","86e26f","3ae237","b5e22e","d6e21f",
+        "fff705","ffd611","ffb613","ff8b13","ff6e08","ff500d",
+        "ff0000","de0101","c21301","a71001","911003",
+        ]
+        }
+        Map.setCenter(128.45, 33.33, 5)
+        Map.addLayer(dataset, visualization, "Leaf Area Index")
+
+    elif cod == "JAXA/GCOM-C/L3/LAND/LAI/V2":
+        dataset = ee.ImageCollection("JAXA/GCOM-C/L3/LAND/LAI/V2").filterDate("2020-01-01", "2020-02-01").filter(ee.Filter.eq("SATELLITE_DIRECTION", "D"))
+        dataset = dataset.mean().multiply(0.001)
+        visualization = {
+        "bands": ["LAI_AVE"],
+        "min": -7,
+        "max": 7,
+        "palette": [
+        "040274","040281","0502a3","0502b8","0502ce","0502e6",
+        "0602ff","235cb1","307ef3","269db1","30c8e2","32d3ef",
+        "3be285","3ff38f","86e26f","3ae237","b5e22e","d6e21f",
+        "fff705","ffd611","ffb613","ff8b13","ff6e08","ff500d",
+        "ff0000","de0101","c21301","a71001","911003",
+        ]
+        }
+        Map.setCenter(128.45, 33.33, 5)
+        Map.addLayer(dataset, visualization, "Leaf Area Index")
+
+    elif cod == "JAXA/GCOM-C/L3/LAND/LAI/V3":
+        dataset = ee.ImageCollection("JAXA/GCOM-C/L3/LAND/LAI/V3").filterDate("2021-12-01", "2022-01-01").filter(ee.Filter.eq("SATELLITE_DIRECTION", "D"))
+        dataset = dataset.mean().multiply(0.001)
+        visualization = {
+        "bands": ["LAI_AVE"],
+        "min": -7,
+        "max": 7,
+        "palette": [
+        "040274","040281","0502a3","0502b8","0502ce","0502e6",
+        "0602ff","235cb1","307ef3","269db1","30c8e2","32d3ef",
+        "3be285","3ff38f","86e26f","3ae237","b5e22e","d6e21f",
+        "fff705","ffd611","ffb613","ff8b13","ff6e08","ff500d",
+        "ff0000","de0101","c21301","a71001","911003",
+        ]
+        }
+        Map.setCenter(128.45, 33.33, 5)
+        Map.addLayer(dataset, visualization, "Leaf Area Index")
+
+    elif cod == "JAXA/GCOM-C/L3/LAND/LST/V1":
+        dataset = ee.ImageCollection("JAXA/GCOM-C/L3/LAND/LST/V1").filterDate("2020-01-01", "2020-02-01").filter(ee.Filter.eq("SATELLITE_DIRECTION", "D"))
+        dataset = dataset.mean().multiply(0.02)
+        visualization = {
+        "bands": ["LST_AVE"],
+        "min": 250,
+        "max": 316,
+        "palette": [
+        "040274","040281","0502a3","0502b8","0502ce","0502e6",
+        "0602ff","235cb1","307ef3","269db1","30c8e2","32d3ef",
+        "3be285","3ff38f","86e26f","3ae237","b5e22e","d6e21f",
+        "fff705","ffd611","ffb613","ff8b13","ff6e08","ff500d",
+        "ff0000","de0101","c21301","a71001","911003",
+        ]
+        }
+        Map.setCenter(128.45, 33.33, 5)
+        Map.addLayer(dataset, visualization, "Land Surface Temperature")
+
+    elif cod == "JAXA/GCOM-C/L3/LAND/LST/V2":
+        dataset = ee.ImageCollection("JAXA/GCOM-C/L3/LAND/LST/V2").filterDate("2020-01-01", "2020-02-01").filter(ee.Filter.eq("SATELLITE_DIRECTION", "D"))
+        dataset = dataset.mean().multiply(0.02)
+        visualization = {
+        "bands": ["LST_AVE"],
+        "min": 250,
+        "max": 316,
+        "palette": [
+        "040274","040281","0502a3","0502b8","0502ce","0502e6",
+        "0602ff","235cb1","307ef3","269db1","30c8e2","32d3ef",
+        "3be285","3ff38f","86e26f","3ae237","b5e22e","d6e21f",
+        "fff705","ffd611","ffb613","ff8b13","ff6e08","ff500d",
+        "ff0000","de0101","c21301","a71001","911003",
+        ]
+        }
+        Map.setCenter(128.45, 33.33, 5)
+        Map.addLayer(dataset, visualization, "Land Surface Temperature")
+
+    elif cod == "JAXA/GCOM-C/L3/LAND/LST/V3":
+        dataset = ee.ImageCollection("JAXA/GCOM-C/L3/LAND/LST/V3").filterDate("2021-12-01", "2022-01-01").filter(ee.Filter.eq("SATELLITE_DIRECTION", "D"))
+        dataset = dataset.mean().multiply(0.02)
+        visualization = {
+        "bands": ["LST_AVE"],
+        "min": 250,
+        "max": 316,
+        "palette": [
+        "040274","040281","0502a3","0502b8","0502ce","0502e6",
+        "0602ff","235cb1","307ef3","269db1","30c8e2","32d3ef",
+        "3be285","3ff38f","86e26f","3ae237","b5e22e","d6e21f",
+        "fff705","ffd611","ffb613","ff8b13","ff6e08","ff500d",
+        "ff0000","de0101","c21301","a71001","911003",
+        ]
+        }
+        Map.setCenter(128.45, 33.33, 5)
+        Map.addLayer(dataset, visualization, "Land Surface Temperature")
+
+    elif cod == "JAXA/GCOM-C/L3/OCEAN/CHLA/V1":
+        dataset = ee.ImageCollection("JAXA/GCOM-C/L3/OCEAN/CHLA/V1").filterDate("2020-01-01", "2020-02-01").filter(ee.Filter.eq("SATELLITE_DIRECTION", "D"))
+        image = dataset.mean().multiply(0.0016).log10()
+        vis = {
+        "bands": ["CHLA_AVE"],
+        "min": -2,
+        "max": 2,
+        "palette": [
+        "3500a8","0800ba","003fd6",
+        "00aca9","77f800","ff8800",
+        "b30000","920000","880000"
+        ]
+        }
+        Map.addLayer(image, vis, "Chlorophyll-a concentration")
+        Map.setCenter(128.45, 33.33, 5)
+
+    elif cod == "JAXA/GCOM-C/L3/OCEAN/CHLA/V2":
+        dataset = ee.ImageCollection("JAXA/GCOM-C/L3/OCEAN/CHLA/V2").filterDate("2020-01-01", "2020-02-01").filter(ee.Filter.eq("SATELLITE_DIRECTION", "D"))
+        image = dataset.mean().multiply(0.0016).log10()
+        vis = {
+        "bands": ["CHLA_AVE"],
+        "min": -2,
+        "max": 2,
+        "palette": [
+        "3500a8","0800ba","003fd6",
+        "00aca9","77f800","ff8800",
+        "b30000","920000","880000"
+        ]
+        }
+        Map.addLayer(image, vis, "Chlorophyll-a concentration")
+        Map.setCenter(128.45, 33.33, 5)
+
+    elif cod == "JAXA/GCOM-C/L3/OCEAN/CHLA/V3":
+        dataset = ee.ImageCollection("JAXA/GCOM-C/L3/OCEAN/CHLA/V3").filterDate("2021-12-01", "2022-01-01").filter(ee.Filter.eq("SATELLITE_DIRECTION", "D"))
+        image = dataset.mean().multiply(0.0016).log10()
+        vis = {
+        "bands": ["CHLA_AVE"],
+        "min": -2,
+        "max": 2,
+        "palette": [
+        "3500a8","0800ba","003fd6",
+        "00aca9","77f800","ff8800",
+        "b30000","920000","880000"
+        ]
+        }
+        Map.addLayer(image, vis, "Chlorophyll-a concentration")
+        Map.setCenter(128.45, 33.33, 5)
+
+    elif cod == "JAXA/GCOM-C/L3/OCEAN/SST/V1":
+        dataset = ee.ImageCollection("JAXA/GCOM-C/L3/OCEAN/SST/V1").filterDate("2020-01-01", "2020-02-01").filter(ee.Filter.eq("SATELLITE_DIRECTION", "D"))
+        dataset = dataset.mean().multiply(0.0012).add(-10)
+        vis = {
+        "bands": ["SST_AVE"],
+        "min": 0,
+        "max": 30,
+        "palette": ["000000", "005aff", "43c8c8", "fff700", "ff0000"],
+        }
+        Map.setCenter(128.45, 33.33, 5)
+        Map.addLayer(dataset, vis, "Sea Surface Temperature")
+
+    elif cod == "JAXA/GCOM-C/L3/OCEAN/SST/V2":
+        dataset = ee.ImageCollection("JAXA/GCOM-C/L3/OCEAN/SST/V2").filterDate("2020-01-01", "2020-02-01").filter(ee.Filter.eq("SATELLITE_DIRECTION", "D"))
+        dataset = dataset.mean().multiply(0.0012).add(-10)
+        vis = {
+        "bands": ["SST_AVE"],
+        "min": 0,
+        "max": 30,
+        "palette": ["000000", "005aff", "43c8c8", "fff700", "ff0000"],
+        }
+        Map.setCenter(128.45, 33.33, 5)
+        Map.addLayer(dataset, vis, "Sea Surface Temperature")
+
+    elif cod == "JAXA/GCOM-C/L3/OCEAN/SST/V3":
+        dataset = ee.ImageCollection("JAXA/GCOM-C/L3/OCEAN/SST/V3").filterDate("2021-12-01", "2022-01-01").filter(ee.Filter.eq("SATELLITE_DIRECTION", "D"))
+        dataset = dataset.mean().multiply(0.0012).add(-10)
+        vis = {
+        "bands": ["SST_AVE"],
+        "min": 0,
+        "max": 30,
+        "palette": ["000000", "005aff", "43c8c8", "fff700", "ff0000"],
+        }
+        Map.setCenter(128.45, 33.33, 5)
+        Map.addLayer(dataset, vis, "Sea Surface Temperature")
+
+    elif cod == "JAXA/GPM_L3/GSMaP/v6/operational":
+        dataset = ee.ImageCollection("JAXA/GPM_L3/GSMaP/v6/operational").filter(ee.Filter.date("2018-08-06", "2018-08-07"))
+        precipitation = dataset.select("hourlyPrecipRate")
+        precipitationVis = {
+        "min": 0.0,
+        "max": 30.0,
+        "palette":
+        ["1621a2", "ffffff", "03ffff", "13ff03", "efff00", "ffb103", "ff2300"],
+        }
+        Map.setCenter(-90.7, 26.12, 2)
+        Map.addLayer(precipitation, precipitationVis, "Precipitation")
+
+    elif cod == "JAXA/GPM_L3/GSMaP/v6/reanalysis":
+        dataset = ee.ImageCollection("JAXA/GPM_L3/GSMaP/v6/reanalysis").filter(ee.Filter.date("2014-02-01", "2014-02-02"))
+        precipitation = dataset.select("hourlyPrecipRate")
+        precipitationVis = {
+        "min": 0.0,
+        "max": 30.0,
+        "palette":
+        ["1621a2", "ffffff", "03ffff", "13ff03", "efff00", "ffb103", "ff2300"],
+        }
+        Map.setCenter(-90.7, 26.12, 2)
+        Map.addLayer(precipitation, precipitationVis, "Precipitation")
+
+    elif cod == "JCU/Murray/GIC/global_tidal_wetland_change/2019":
+        dataset = ee.Image("JCU/Murray/GIC/global_tidal_wetland_change/2019")
+        Map.setCenter(103.7, 1.3, 12)
+        Map.setOptions("SATELLITE")
+        plasma = [
+        "0d0887", "3d049b", "6903a5", "8d0fa1", "ae2891", "cb4679", "df6363",
+        "f0844c", "faa638", "fbcc27", "f0f921"
+        ]
+        Map.addLayer(dataset.select("twprobabilityStart"), {"palette": plasma, "min": 0, "max": 100},"twprobabilityStart", False, 1)
+        Map.addLayer(dataset.select("twprobabilityEnd"), {"palette": plasma, "min": 0, "max": 100},"twprobabilityEnd", False, 1)
+        lossPalette = ["FE4A49"]
+        gainPalette = ["2AB7CA"]
+        Map.addLayer(dataset.select("loss"), {"palette": lossPalette, "min": 1, "max": 1},"Tidal wetland loss", True, 1)
+        Map.addLayer(dataset.select("gain"), {"palette": gainPalette, "min": 1, "max": 1},"Tidal wetland gain", True, 1)
+        viridis = ["440154", "414487", "2a788e", "22a884", "7ad151", "fde725"]
+        Map.addLayer(dataset.select("lossYear"), {"palette": viridis, "min": 4, "max": 19},"Year of loss", False, 0.9)
+        Map.addLayer(dataset.select("gainYear"), {"palette": viridis, "min": 4, "max": 19},"Year of gain", False, 0.9)
+        classPalette = ["9e9d9d", "ededed", "FF9900", "009966", "960000", "006699"]
+        classNames = ["None", "None", "Tidal flat", "Mangrove", "None", "Tidal marsh"]
+        Map.addLayer(dataset.select("lossType"), {"palette": classPalette, "min": 0, "max": 5}, "Loss type", False, 0.9)
+        Map.addLayer(dataset.select("gainType"), {"palette": classPalette, "min": 0, "max": 5}, "Gain type", False, 0.9)
+
+    elif cod == "JRC/D5/EUCROPMAP/V1":
+        image = ee.Image("JRC/D5/EUCROPMAP/V1/2018")
+        Map.addLayer(image, {}, "EUCROPMAP 2018")
+        Map.setCenter(10, 48, 4)
+
+    elif cod == "JRC/GHSL/P2016/BUILT_LDSMT_GLOBE_V1":
+        dataset = ee.Image("JRC/GHSL/P2016/BUILT_LDSMT_GLOBE_V1")
+        builtUpMultitemporal = dataset.select("built")
+        visParams = {
+        "min": 1.0,
+        "max": 6.0,
+        "palette": ["0c1d60", "000000", "448564", "70daa4", "83ffbf", "ffffff"],
+        }
+        Map.setCenter(8.9957, 45.5718, 12)
+        Map.addLayer(builtUpMultitemporal, visParams, "Built-Up Multitemporal")
+
+    elif cod == "JRC/GHSL/P2016/POP_GPW_GLOBE_V1":
+        dataset = ee.ImageCollection("JRC/GHSL/P2016/POP_GPW_GLOBE_V1").filter(ee.Filter.date("2015-01-01", "2015-12-31"))
+        populationCount = dataset.select("population_count")
+        populationCountVis = {
+        "min": 0.0,
+        "max": 200.0,
+        "palette": ["060606", "337663", "337663", "ffffff"],
+        }
+        Map.setCenter(78.22, 22.59, 3)
+        Map.addLayer(populationCount, populationCountVis, "Population Count")
+
+    elif cod == "JRC/GHSL/P2016/SMOD_POP_GLOBE_V1":
+        dataset = ee.ImageCollection("JRC/GHSL/P2016/SMOD_POP_GLOBE_V1").filter(ee.Filter.date("2015-01-01", "2015-12-31"))
+        degreeOfUrbanization = dataset.select("smod_code")
+        visParams = {
+        "min": 0.0,
+        "max": 3.0,
+        "palette": ["000000", "448564", "70daa4", "ffffff"],
+        }
+        Map.setCenter(114.96, 31.13, 4)
+        Map.addLayer(degreeOfUrbanization, visParams, "Degree of Urbanization")
+
+    elif cod == "JRC/GSW1_4/GlobalSurfaceWater":
+        dataset = ee.Image("JRC/GSW1_4/GlobalSurfaceWater")
+        visualization = {
+        "bands": ["occurrence"],
+        "min": 0.0,
+        "max": 100.0,
+        "palette": ["ffffff", "ffbbbb", "0000ff"]
+        }
+        Map.setCenter(59.414, 45.182, 6)
+        Map.addLayer(dataset, visualization, "Occurrence")
+
+    elif cod == "JRC/GSW1_4/Metadata":
+        dataset = ee.Image("JRC/GSW1_4/Metadata")
+        visualization = {
+        "bands": ["detections", "valid_obs", "total_obs"],
+        "min": 100.0,
+        "max": 900.0,
+        }
+        Map.setCenter(71.72, 52.48, 0)
+        Map.addLayer(dataset, visualization, "Detections/Observations")
+
+    elif cod == "JRC/GSW1_4/MonthlyHistory":
+        dataset = ee.Image("JRC/GSW1_4/MonthlyHistory/2020_06")
+        visualization = {
+        "bands": ["water"],
+        "min": 0.0,
+        "max": 2.0,
+        "palette": ["ffffff", "fffcb8", "0905ff"]
+        }
+        Map.setCenter(-121.234, 38.109, 7)
+        Map.addLayer(dataset, visualization, "Water")
+
+    elif cod == "JRC/GSW1_4/MonthlyRecurrence":
+        dataset = ee.ImageCollection("JRC/GSW1_4/MonthlyRecurrence")
+        visualization = {
+        "bands": ["monthly_recurrence"],
+        "min": 0.0,
+        "max": 100.0,
+        "palette": ["ffffff", "ffbbbb", "0000ff"]
+        }
+        Map.setCenter(-51.482, -0.835, 6)
+        Map.addLayer(dataset, visualization, "Monthly Recurrence")
+
+    elif cod == "JRC/GSW1_4/YearlyHistory":
+        dataset = ee.ImageCollection("JRC/GSW1_4/YearlyHistory")
+        visualization = {
+        "bands": ["waterClass"],
+        "min": 0.0,
+        "max": 3.0,
+        "palette": ["cccccc", "ffffff", "99d9ea", "0000ff"]
+        }
+        Map.setCenter(59.414, 45.182, 7)
+        Map.addLayer(dataset, visualization, "Water Class")
+
+    elif cod == "JRC/GWIS/GlobFire/v2/DailyPerimeters":
+        folder = "JRC/GWIS/GlobFire/v2/DailyPerimeters"
+        def printAssetList(listAssetsOutput):
+            print("Asset list:", listAssetsOutput["assets"])
+            ee.data.listAssets(folder, {}, printAssetList)
+
+        tableName = "JRC/GWIS/GlobFire/v2/DailyPerimeters/2020"
+        computeArea = lambda f: f.set({"area": f.area()})
+        
+        features = ee.FeatureCollection(tableName).map(computeArea)
+        visParams = {
+        "palette": ["f5ff64", "b5ffb4", "beeaff", "ffc0e8", "8e8dff", "adadad"],
+        "min": 0.0,
+        "max": 600000000.0,
+        "opacity": 0.8,
+        }
+        image = ee.Image().float().paint(features, "area")
+        Map.addLayer(image, visParams, "GlobFire 2020")
+        Map.addLayer(features, None, "For Inspector", False)
+        Map.setCenter(-121.23, 39.7, 12)
+
+    elif cod == "JRC/GWIS/GlobFire/v2/FinalPerimeters":
+        dataset = ee.FeatureCollection("JRC/GWIS/GlobFire/v2/FinalPerimeters")
+        visParams = {
+        "palette": ["f5ff64", "b5ffb4", "beeaff", "ffc0e8", "8e8dff", "adadad"],
+        "min": 0.0,
+        "max": 600000000.0,
+        "opacity": 0.8,
+        }
+        image = ee.Image().float().paint(dataset, "area")
+        Map.addLayer(image, visParams, "GlobFire Final")
+        Map.addLayer(dataset, None, "for Inspector", False)
+        Map.setCenter(-122.121, 38.56, 12)
+
+    elif cod == "JRC/LUCAS_HARMO/COPERNICUS_POLYGONS/V1/2018":
+        dataset = ee.FeatureCollection("JRC/LUCAS_HARMO/COPERNICUS_POLYGONS/V1/2018")
+        visParams = {
+        "min": 35,
+        "max": 60
+        }
+        dataset2 = dataset.map(lambda f: ee.Feature(f.buffer(5000)))
+        image = ee.Image().float().paint(dataset2, "gps_lat").randomVisualizer()
+        Map.addLayer(ee.Image(1), {"min":0, "max":1}, "background")
+        Map.addLayer(image, visParams, "LUCAS Polygons")
+        Map.addLayer(dataset, None, "for Inspector", False)
+        Map.setCenter(19.514, 51.82, 8)
+
+    elif cod == "JRC/LUCAS_HARMO/THLOC/V1":
+        dataset = ee.FeatureCollection("JRC/LUCAS_HARMO/THLOC/V1")
+        Map.addLayer(dataset, {}, "LUCAS Points (data)", False)
+        dataset = dataset.style({
+        "color": "489734",
+        "pointSize": 3
+        })
+        Map.setCenter(-3.8233, 40.609, 10)
+        Map.addLayer(dataset, {}, "LUCAS Points (styled green)")
+
+    elif cod == "KNTU/LiDARLab/IranLandCover/V1":
+        dataset = ee.Image("KNTU/LiDARLab/IranLandCover/V1")
+        visualization = {
+        "bands": ["classification"]
+        }
+        Map.setCenter(54.0, 33.0, 5)
+        Map.addLayer(dataset, visualization, "Classification")
+
+    elif cod == "LANDFIRE/Fire/FRG/v1_2_0":
+        dataset = ee.ImageCollection("LANDFIRE/Fire/FRG/v1_2_0")
+        visualization = {
+        "bands": ["FRG"]
+        }
+        Map.setCenter(-121.671, 40.699, 5)
+        Map.addLayer(dataset, visualization, "FRG")
+
+    elif cod == "LANDFIRE/Fire/MFRI/v1_2_0":
+        dataset = ee.ImageCollection("LANDFIRE/Fire/MFRI/v1_2_0")
+        visualization = {
+        "bands": ["MFRI"]
+        }
+        Map.setCenter(-121.671, 40.699, 5)
+        Map.addLayer(dataset, visualization, "MFRI")
+
+    elif cod == "LANDFIRE/Fire/PLS/v1_2_0":
+        dataset = ee.ImageCollection("LANDFIRE/Fire/PLS/v1_2_0")
+        visualization = {
+        "bands": ["PLS"]
+        }
+        Map.setCenter(-121.671, 40.699, 5)
+        Map.addLayer(dataset, visualization, "PLS")
+
+    elif cod == "LANDFIRE/Fire/PMS/v1_2_0":
+        dataset = ee.ImageCollection("LANDFIRE/Fire/PMS/v1_2_0")
+        visualization = {
+        "bands": ["PMS"]
+        }
+        Map.setCenter(-121.671, 40.699, 5)
+        Map.addLayer(dataset, visualization, "PMS")
+
+    elif cod == "LANDFIRE/Fire/PRS/v1_2_0":
+        dataset = ee.ImageCollection("LANDFIRE/Fire/PRS/v1_2_0")
+        visualization = {
+        "bands": ["PRS"]
+        }
+        Map.setCenter(-121.671, 40.699, 5)
+        Map.addLayer(dataset, visualization, "PRS")
+
+    elif cod == "LANDFIRE/Fire/SClass/v1_4_0":
+        dataset = ee.ImageCollection("LANDFIRE/Fire/SClass/v1_4_0")
+        visualization = {
+        "bands": ["SClass"]
+        }
+        Map.setCenter(-121.671, 40.699, 5)
+        Map.addLayer(dataset, visualization, "SClass")
+
+    elif cod == "LANDFIRE/Fire/VCC/v1_4_0":
+        dataset = ee.ImageCollection("LANDFIRE/Fire/VCC/v1_4_0")
+        visualization = {
+        "bands": ["VCC"]
+        }
+        Map.setCenter(-121.671, 40.699, 5)
+        Map.addLayer(dataset, visualization, "VCC")
+
+    elif cod == "LANDFIRE/Fire/VDep/v1_4_0":
+        dataset = ee.ImageCollection("LANDFIRE/Fire/VDep/v1_4_0")
+        visualization = {
+        "bands": ["VDep"]
+        }
+        Map.setCenter(-121.671, 40.699, 5)
+        Map.addLayer(dataset, visualization, "VDep")
+
+    elif cod == "LANDFIRE/Vegetation/BPS/v1_4_0":
+        dataset = ee.ImageCollection("LANDFIRE/Vegetation/BPS/v1_4_0")
+        visualization = {
+            "bands": ["BPS"]
+        }
+        Map.setCenter(-121.671, 40.699, 5)
+        Map.addLayer(dataset, visualization, "BPS")
+
+    elif cod == "LANDFIRE/Vegetation/ESP/v1_2_0/AK":
+        dataset = ee.Image("LANDFIRE/Vegetation/ESP/v1_2_0/AK")
+        visualization = {
+            "bands": ["ESP"]
+        }
+        Map.setCenter(-151.011, 63.427, 8)
+        Map.addLayer(dataset, visualization, "ESP")
+
+    elif cod == "LANDFIRE/Vegetation/ESP/v1_2_0/CONUS":
+        dataset = ee.Image("LANDFIRE/Vegetation/ESP/v1_2_0/CONUS")
+        visualization = {
+            "bands": ["ESP"]
+        }
+        Map.setCenter(-121.671, 40.699, 5)
+        Map.addLayer(dataset, visualization, "ESP")
+
+    elif cod == "LANDFIRE/Vegetation/ESP/v1_2_0/HI":
+        dataset = ee.Image("LANDFIRE/Vegetation/ESP/v1_2_0/HI")
+        visualization = {
+            "bands": ["ESP"]
+        }
+        Map.setCenter(-155.3, 19.627, 8)
+        Map.addLayer(dataset, visualization, "ESP")
+
+    elif cod == "LANDFIRE/Vegetation/EVC/v1_4_0":
+        dataset = ee.ImageCollection("LANDFIRE/Vegetation/EVC/v1_4_0")
+        visualization = {
+            "bands": ["EVC"]
+        }
+        Map.setCenter(-121.671, 40.699, 5)
+        Map.addLayer(dataset, visualization, "EVC")
+
+    elif cod == "LANDFIRE/Vegetation/EVH/v1_4_0":
+        dataset = ee.ImageCollection("LANDFIRE/Vegetation/EVH/v1_4_0")
+        visualization = {
+            "bands": ["EVH"]
+        }
+        Map.setCenter(-121.671, 40.699, 5)
+        Map.addLayer(dataset, visualization, "EVH")
+
+    elif cod == "LANDFIRE/Vegetation/EVT/v1_4_0":
+        dataset = ee.ImageCollection("LANDFIRE/Vegetation/EVT/v1_4_0")
+        visualization = {
+            "bands": ["EVT"]
+        }
+        Map.setCenter(-121.671, 40.699, 5)
+        Map.addLayer(dataset, visualization, "EVT")
+
+    elif cod == "LANDSAT/GLS1975":
+        dataset = ee.ImageCollection("LANDSAT/GLS1975")
+        FalseColor = dataset.select(["30", "20", "10"])
+        FalseColorVis = {
+            "gamma": 1.6
+        }
+        Map.setCenter(44.517, 25.998, 5)
+        Map.addLayer(FalseColor, FalseColorVis, "False Color")
+
+    elif cod == "LANDSAT/GLS2005":
+        dataset = ee.ImageCollection("LANDSAT/GLS2005")
+        trueColor321 = dataset.select(["30", "20", "10"])
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(trueColor321, {}, "True Color (321)")
+
+    elif cod == "LANDSAT/GLS2005_L5":
+        dataset = ee.ImageCollection("LANDSAT/GLS2005_L5")
+        trueColor321 = dataset.select(["30", "20", "10"])
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(trueColor321, {}, "True Color (321)")
+
+    elif cod == "LANDSAT/GLS2005_L7":
+        dataset = ee.ImageCollection("LANDSAT/GLS2005_L7")
+        trueColor321 = dataset.select(["30", "20", "10"])
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(trueColor321, {}, "True Color (321)")
+
+    elif cod == "LANDSAT/LC08/C02/T1":
+        dataset = ee.ImageCollection("LANDSAT/LC08/C02/T1").filterDate("2017-01-01", "2017-12-31")
+        trueColor432 = dataset.select(["B4", "B3", "B2"])
+        trueColor432Vis = {
+        "min": 0.0,
+        "max": 30000.0
+        }
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(trueColor432, trueColor432Vis, "True Color (432)")
+
+    elif cod == "LANDSAT/LC08/C02/T1_L2":
+        dataset = ee.ImageCollection("LANDSAT/LC08/C02/T1_L2").filterDate("2021-05-01", "2021-06-01")
+        def applyScaleFactors(image):
+            opticalBands = image.select("SR_B.").multiply(0.0000275).add(-0.2)
+            thermalBands = image.select("ST_B.*").multiply(0.00341802).add(149.0)
+            return image.addBands(opticalBands, None, True).addBands(thermalBands, None, True)
+        dataset = dataset.map(applyScaleFactors)
+        visualization = {
+        "bands": ["SR_B4", "SR_B3", "SR_B2"],
+        "min": 0.0,
+        "max": 0.3
+        }
+        Map.setCenter(-114.2579, 38.9275, 8)
+        Map.addLayer(dataset, visualization, "True Color (432)")
+
+    elif cod == "LANDSAT/LC08/C02/T1_RT":
+        dataset = ee.ImageCollection("LANDSAT/LC08/C02/T1_RT").filterDate("2017-01-01", "2017-12-31")
+        trueColor432 = dataset.select(["B4", "B3", "B2"])
+        trueColor432Vis = {
+        "min": 0.0,
+        "max": 30000.0
+        }
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(trueColor432, trueColor432Vis, "True Color (432)")
+
+    elif cod == "LANDSAT/LC08/C02/T1_RT_TOA":
+        dataset = ee.ImageCollection("LANDSAT/LC08/C02/T1_RT_TOA").filterDate("2017-01-01", "2017-12-31")
+        trueColor432 = dataset.select(["B4", "B3", "B2"])
+        trueColor432Vis = {
+            "min": 0.0,
+            "max": 0.4
+            }
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(trueColor432, trueColor432Vis, "True Color (432)")
+
+    elif cod == "LANDSAT/LC08/C02/T1_TOA":
+        dataset = ee.ImageCollection("LANDSAT/LC08/C02/T1_TOA").filterDate("2017-01-01", "2017-12-31")
+        trueColor432 = dataset.select(["B4", "B3", "B2"])
+        trueColor432Vis = {
+            "min": 0.0,
+            "max": 0.4}
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(trueColor432, trueColor432Vis, "True Color (432)")
+
+    elif cod == "LANDSAT/LC08/C02/T2":
+        dataset = ee.ImageCollection("LANDSAT/LC08/C02/T2").filterDate("2017-01-01", "2017-12-31")
+        trueColor432 = dataset.select(["B4", "B3", "B2"])
+        trueColor432Vis = {
+            "min": 0.0,
+            "max": 30000.0
+            }
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(trueColor432, trueColor432Vis, "True Color (432)")
+
+    elif cod == "LANDSAT/LC08/C02/T2_L2":
+        dataset = ee.ImageCollection("LANDSAT/LC08/C02/T2_L2").filterDate("2021-05-01", "2021-06-01")
+        def applyScaleFactors(image):
+            opticalBands = image.select("SR_B.").multiply(0.0000275).add(-0.2)
+            thermalBands = image.select("ST_B.*").multiply(0.00341802).add(149.0)
+            return image.addBands(opticalBands, None, True) .addBands(thermalBands, None, True)
+        dataset = dataset.map(applyScaleFactors)
+        visualization = {
+            "bands": ["SR_B4", "SR_B3", "SR_B2"],
+            "min": 0.0,
+            "max": 0.3
+        }
+        Map.setCenter(-83, 24, 8)
+        Map.addLayer(dataset, visualization, "True Color (432)")
+
+    elif cod == "LANDSAT/LC08/C02/T2_TOA":
+        dataset = ee.ImageCollection("LANDSAT/LC08/C02/T2_TOA").filterDate("2017-01-01", "2017-12-31")
+        trueColor432 = dataset.select(["B4", "B3", "B2"])
+        trueColor432Vis = {
+            "min": 0.0,
+            "max": 0.4
+        }
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(trueColor432, trueColor432Vis, "True Color (432)")
+
+    elif cod == "LANDSAT/LC09/C02/T1":
+        dataset = ee.ImageCollection("LANDSAT/LC09/C02/T1").filterDate("2022-01-01", "2022-02-01")
+        trueColor432 = dataset.select(["B4", "B3", "B2"])
+        trueColor432Vis = {
+            "min": 0.0,
+            "max": 30000.0
+            }
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(trueColor432, trueColor432Vis, "True Color (432)")
+
+    elif cod == "LANDSAT/LC09/C02/T1_L2":
+        dataset = ee.ImageCollection("LANDSAT/LC09/C02/T1_L2").filterDate("2022-01-01", "2022-02-01")
+        def applyScaleFactors(image):
+            opticalBands = image.select("SR_B.").multiply(0.0000275).add(-0.2)
+            thermalBands = image.select("ST_B.*").multiply(0.00341802).add(149.0)
+            return image.addBands(opticalBands, None, True).addBands(thermalBands, None, True)
+        dataset = dataset.map(applyScaleFactors)
+        visualization = {
+            "bands": ["SR_B4", "SR_B3", "SR_B2"],
+            "min": 0.0,
+            "max": 0.3
+        }
+        Map.setCenter(-114.2579, 38.9275, 8)
+        Map.addLayer(dataset, visualization, "True Color (432)")
+
+    elif cod == "LANDSAT/LC09/C02/T1_TOA":
+        dataset = ee.ImageCollection("LANDSAT/LC09/C02/T1_TOA").filterDate("2022-01-01", "2022-02-01")
+        trueColor432 = dataset.select(["B4", "B3", "B2"])
+        trueColor432Vis = {
+            "min": 0.0,
+            "max": 0.4}
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(trueColor432, trueColor432Vis, "True Color (432)")
+
+    elif cod == "LANDSAT/LC09/C02/T2":
+        dataset = ee.ImageCollection("LANDSAT/LC09/C02/T2").filterDate("2022-01-01", "2022-02-01")
+        trueColor432 = dataset.select(["B4", "B3", "B2"])
+        trueColor432Vis = {
+            "min": 0.0,
+            "max": 30000.0}
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(trueColor432, trueColor432Vis, "True Color (432)")
+
+    elif cod == "LANDSAT/LC09/C02/T2_L2":
+        dataset = ee.ImageCollection("LANDSAT/LC09/C02/T2_L2").filterDate("2022-01-01", "2022-02-01")
+        def applyScaleFactors(image):
+            opticalBands = image.select("SR_B.").multiply(0.0000275).add(-0.2)
+            thermalBands = image.select("ST_B.*").multiply(0.00341802).add(149.0)
+            return image.addBands(opticalBands, None, True).addBands(thermalBands, None, True)
+        dataset = dataset.map(applyScaleFactors)
+        visualization = {
+            "bands": ["SR_B4", "SR_B3", "SR_B2"],
+            "min": 0.0,
+            "max": 0.3}
+        Map.setCenter(-83, 24, 8)
+        Map.addLayer(dataset, visualization, "True Color (432)")
+
+    elif cod == "LANDSAT/LC09/C02/T2_TOA":
+        dataset = ee.ImageCollection("LANDSAT/LC09/C02/T2_TOA").filterDate("2022-01-01", "2022-02-01")
+        trueColor432 = dataset.select(["B4", "B3", "B2"])
+        trueColor432Vis = {
+            "min": 0.0,
+            "max": 0.4}
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(trueColor432, trueColor432Vis, "True Color (432)")
+
+    elif cod == "LANDSAT/LE07/C02/T1":
+        dataset = ee.ImageCollection("LANDSAT/LE07/C02/T1").filterDate("1999-01-01", "2002-12-31")
+        trueColor321 = dataset.select(["B3", "B2", "B1"])
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(trueColor321, {}, "True Color (321)")
+
+    elif cod == "LANDSAT/LE07/C02/T1_L2":
+        dataset = ee.ImageCollection("LANDSAT/LE07/C02/T1_L2").filterDate("2017-06-01", "2017-07-01")
+        def applyScaleFactors(image):
+            opticalBands = image.select("SR_B.").multiply(0.0000275).add(-0.2)
+            thermalBand = image.select("ST_B6").multiply(0.00341802).add(149.0)
+            return image.addBands(opticalBands, None, True).addBands(thermalBand, None, True)
+        dataset = dataset.map(applyScaleFactors)
+        visualization = {
+            "bands": ["SR_B3", "SR_B2", "SR_B1"],
+            "min": 0.0,
+            "max": 0.3}
+        Map.setCenter(-114.2579, 38.9275, 8)
+        Map.addLayer(dataset, visualization, "True Color (321)")
+
+    elif cod == "LANDSAT/LE07/C02/T1_RT":
+        dataset = ee.ImageCollection("LANDSAT/LE07/C02/T1_RT").filterDate("1999-01-01", "2002-12-31")
+        trueColor321 = dataset.select(["B3", "B2", "B1"])
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(trueColor321, {}, "True Color (321)")
+
+    elif cod == "LANDSAT/LE07/C02/T1_RT_TOA":
+        dataset = ee.ImageCollection("LANDSAT/LE07/C02/T1_RT_TOA").filterDate("1999-01-01", "2002-12-31")
+        trueColor321 = dataset.select(["B3", "B2", "B1"])
+        trueColor321Vis = {
+            "min": 0.0,
+            "max": 0.4,
+            "gamma": 1.2}
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(trueColor321, trueColor321Vis, "True Color (321)")
+
+    elif cod == "LANDSAT/LE07/C02/T1_TOA":
+        dataset = ee.ImageCollection("LANDSAT/LE07/C02/T1_TOA").filterDate("1999-01-01", "2002-12-31")
+        trueColor321 = dataset.select(["B3", "B2", "B1"])
+        trueColor321Vis = {
+            "min": 0.0,
+            "max": 0.4,
+            "gamma": 1.2}
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(trueColor321, trueColor321Vis, "True Color (321)")
+
+    elif cod == "LANDSAT/LE07/C02/T2":
+        dataset = ee.ImageCollection("LANDSAT/LE07/C02/T2").filterDate("1999-01-01", "2002-12-31")
+        trueColor321 = dataset.select(["B3", "B2", "B1"])
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(trueColor321, {}, "True Color (321)")
+
+    elif cod == "LANDSAT/LE07/C02/T2_L2":
+        dataset = ee.ImageCollection("LANDSAT/LE07/C02/T2_L2").filterDate("2017-06-01", "2017-07-01")
+        def applyScaleFactors(image):
+            opticalBands = image.select("SR_B.").multiply(0.0000275).add(-0.2)
+            thermalBand = image.select("ST_B6").multiply(0.00341802).add(149.0)
+            return image.addBands(opticalBands, None, True).addBands(thermalBand, None, True)
+        dataset = dataset.map(applyScaleFactors)
+        visualization = {
+            "bands": ["SR_B3", "SR_B2", "SR_B1"],
+            "min": 0.0,
+            "max": 0.3}
+        Map.setCenter(-83, 24, 8)
+        Map.addLayer(dataset, visualization, "True Color (321)")
+
+    elif cod == "LANDSAT/LE07/C02/T2_TOA":
+        dataset = ee.ImageCollection("LANDSAT/LE07/C02/T2_TOA").filterDate("1999-01-01", "2002-12-31")
+        trueColor321 = dataset.select(["B3", "B2", "B1"])
+        trueColor321Vis = {
+            "min": 0.0,
+            "max": 0.4,
+            "gamma": 1.2}
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(trueColor321, trueColor321Vis, "True Color (321)")
+
+    elif cod == "LANDSAT/LM01/C02/T1":
+        dataset = ee.ImageCollection("LANDSAT/LM01/C02/T1").filterDate("1974-01-01", "1978-12-31")
+        nearInfrared321 = dataset.select(["B6", "B5", "B4"])
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(nearInfrared321, {}, "Near Infrared (321)")
+
+    elif cod == "LANDSAT/LM01/C02/T2":
+        dataset = ee.ImageCollection("LANDSAT/LM01/C02/T2").filterDate("1974-01-01", "1978-12-31")
+        nearInfrared321 = dataset.select(["B6", "B5", "B4"])
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(nearInfrared321, {}, "Near Infrared (321)")
+
+    elif cod == "LANDSAT/LM02/C02/T1":
+        dataset = ee.ImageCollection("LANDSAT/LM02/C02/T1").filterDate("1978-01-01", "1980-12-31")
+        nearInfrared321 = dataset.select(["B6", "B5", "B4"])
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(nearInfrared321, {}, "Near Infrared (321)")
+
+    elif cod == "LANDSAT/LM02/C02/T2":
+        dataset = ee.ImageCollection("LANDSAT/LM02/C02/T2").filterDate("1978-01-01", "1980-12-31")
+        nearInfrared321 = dataset.select(["B6", "B5", "B4"])
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(nearInfrared321, {}, "Near Infrared (321)")
+
+    elif cod == "LANDSAT/LM03/C02/T1":
+        dataset = ee.ImageCollection("LANDSAT/LM03/C02/T1").filterDate("1978-01-01", "1980-12-31")
+        nearInfrared321 = dataset.select(["B6", "B5", "B4"])
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(nearInfrared321, {}, "Near Infrared (321)")
+
+    elif cod == "LANDSAT/LM03/C02/T2":
+        dataset = ee.ImageCollection("LANDSAT/LM03/C02/T2").filterDate("1978-01-01", "1980-12-31")
+        nearInfrared321 = dataset.select(["B6", "B5", "B4"])
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(nearInfrared321, {}, "Near Infrared (321)")
+
+    elif cod == "LANDSAT/LM04/C02/T1":
+        dataset = ee.ImageCollection("LANDSAT/LM04/C02/T1").filterDate("1989-01-01", "1992-12-31")
+        nearInfrared321 = dataset.select(["B3", "B2", "B1"])
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(nearInfrared321, {}, "Near Infrared (321)")
+
+    elif cod == "LANDSAT/LM04/C02/T2":
+        dataset = ee.ImageCollection("LANDSAT/LM04/C02/T2").filterDate("1989-01-01", "1992-12-31")
+        nearInfrared321 = dataset.select(["B3", "B2", "B1"])
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(nearInfrared321, {}, "Near Infrared (321)")
+
+    elif cod == "LANDSAT/LM05/C02/T1":
+        dataset = ee.ImageCollection("LANDSAT/LM05/C02/T1").filterDate("1985-01-01", "1989-12-31")
+        nearInfrared321 = dataset.select(["B3", "B2", "B1"])
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(nearInfrared321, {}, "Near Infrared (321)")
+
+    elif cod == "LANDSAT/LM05/C02/T2":
+        dataset = ee.ImageCollection("LANDSAT/LM05/C02/T2").filterDate("1985-01-01", "1989-12-31")
+        nearInfrared321 = dataset.select(["B3", "B2", "B1"])
+        nearInfrared321Vis = {}
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(nearInfrared321, nearInfrared321Vis, "Near Infrared (321)")
+
+    elif cod == "LANDSAT/LT04/C02/T1":
+        dataset = ee.ImageCollection("LANDSAT/LT04/C02/T1").filterDate("1989-01-01", "1992-12-31")
+        trueColor321 = dataset.select(["B3", "B2", "B1"])
+        trueColor321Vis = {}
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(trueColor321, trueColor321Vis, "True Color (321)")
+
+    elif cod == "LANDSAT/LT04/C02/T1_L2":
+        dataset = ee.ImageCollection("LANDSAT/LT04/C02/T1_L2").filterDate("1990-04-01", "1990-05-01")
+        def applyScaleFactors(image):
+                     opticalBands = image.select("SR_B.").multiply(0.0000275).add(-0.2)
+                     thermalBand = image.select("ST_B6").multiply(0.00341802).add(149.0)
+                     return image.addBands(opticalBands, None, True).addBands(thermalBand, None, True)
+        dataset = dataset.map(applyScaleFactors)
+        visualization = {
+        "bands": ["SR_B3", "SR_B2", "SR_B1"],
+        "min": 0.0,
+        "max": 0.3,
+        }
+        Map.setCenter(15, 53, 8)
+        Map.addLayer(dataset, visualization, "True Color (321)")
+
+    elif cod == "LANDSAT/LT04/C02/T1_TOA":
+        dataset = ee.ImageCollection("LANDSAT/LT04/C02/T1_TOA").filterDate("1989-01-01", "1992-12-31")
+        trueColor321 = dataset.select(["B3", "B2", "B1"])
+        trueColor321Vis = {
+        "min": 0.0,
+        "max": 0.4,
+        "gamma": 1.2,
+        }
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(trueColor321, trueColor321Vis, "True Color (321)")
+
+    elif cod == "LANDSAT/LT04/C02/T2":
+        dataset = ee.ImageCollection("LANDSAT/LT04/C02/T2").filterDate("1989-01-01", "1992-12-31")
+        trueColor321 = dataset.select(["B3", "B2", "B1"])
+        trueColor321Vis = {}
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(trueColor321, trueColor321Vis, "True Color (321)")
+
+    elif cod == "LANDSAT/LT04/C02/T2_L2":
+        dataset = ee.ImageCollection("LANDSAT/LT04/C02/T2_L2").filterDate("1990-04-01", "1990-05-01")
+        def applyScaleFactors(image):
+                     opticalBands = image.select("SR_B.").multiply(0.0000275).add(-0.2)
+                     thermalBand = image.select("ST_B6").multiply(0.00341802).add(149.0)
+                     return image.addBands(opticalBands, None, True).addBands(thermalBand, None, True)
+        dataset = dataset.map(applyScaleFactors)
+        visualization = {
+        "bands": ["SR_B3", "SR_B2", "SR_B1"],
+        "min": 0.0,
+        "max": 0.3,
+        }
+        Map.setCenter(-83, 24, 8)
+        Map.addLayer(dataset, visualization, "True Color (321)")
+
+    elif cod == "LANDSAT/LT04/C02/T2_TOA":
+        dataset = ee.ImageCollection("LANDSAT/LT04/C02/T2_TOA").filterDate("1989-01-01", "1992-12-31")
+        trueColor321 = dataset.select(["B3", "B2", "B1"])
+        trueColor321Vis = {
+        "min": 0.0,
+        "max": 0.4,
+        "gamma": 1.2,
+        }
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(trueColor321, trueColor321Vis, "True Color (321)")
+
+    elif cod == "LANDSAT/LT05/C02/T1":
+        dataset = ee.ImageCollection("LANDSAT/LT05/C02/T1").filterDate("2011-01-01", "2011-12-31")
+        trueColor321 = dataset.select(["B3", "B2", "B1"])
+        trueColor321Vis = {}
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(trueColor321, trueColor321Vis, "True Color (321)")
+
+    elif cod == "LANDSAT/LT05/C02/T1_L2":
+        dataset = ee.ImageCollection("LANDSAT/LT05/C02/T1_L2").filterDate("2000-06-01", "2000-07-01")
+        def applyScaleFactors(image):
+                     opticalBands = image.select("SR_B.").multiply(0.0000275).add(-0.2)
+                     thermalBand = image.select("ST_B6").multiply(0.00341802).add(149.0)
+                     return image.addBands(opticalBands, None, True).addBands(thermalBand, None, True)
+        dataset = dataset.map(applyScaleFactors)
+        visualization = {
+        "bands": ["SR_B3", "SR_B2", "SR_B1"],
+        "min": 0.0,
+        "max": 0.3,
+        }
+        Map.setCenter(-114.2579, 38.9275, 8)
+        Map.addLayer(dataset, visualization, "True Color (321)")
+
+    elif cod == "LANDSAT/LT05/C02/T1_TOA":
+        dataset = ee.ImageCollection("LANDSAT/LT05/C02/T1_TOA").filterDate("2011-01-01", "2011-12-31")
+        trueColor321 = dataset.select(["B3", "B2", "B1"])
+        trueColor321Vis = {
+        "min": 0.0,
+        "max": 0.4,
+        "gamma": 1.2,
+        }
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(trueColor321, trueColor321Vis, "True Color (321)")
+
+    elif cod == "LANDSAT/LT05/C02/T2":
+        dataset = ee.ImageCollection("LANDSAT/LT05/C02/T2").filterDate("2011-01-01", "2011-12-31")
+        trueColor321 = dataset.select(["B3", "B2", "B1"])
+        trueColor321Vis = {}
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(trueColor321, trueColor321Vis, "True Color (321)")
+
+    elif cod == "LANDSAT/LT05/C02/T2_L2":
+        dataset = ee.ImageCollection("LANDSAT/LT05/C02/T2_L2").filterDate("2000-06-01", "2000-07-01")
+        def applyScaleFactors(image):
+                     opticalBands = image.select("SR_B.").multiply(0.0000275).add(-0.2)
+                     thermalBand = image.select("ST_B6").multiply(0.00341802).add(149.0)
+                     return image.addBands(opticalBands, None, True).addBands(thermalBand, None, True)
+        dataset = dataset.map(applyScaleFactors)
+        visualization = {
+        "bands": ["SR_B3", "SR_B2", "SR_B1"],
+        "min": 0.0,
+        "max": 0.3,
+        }
+        Map.setCenter(-83, 24, 8)
+        Map.addLayer(dataset, visualization, "True Color (321)")
+
+    elif cod == "LANDSAT/LT05/C02/T2_TOA":
+        dataset = ee.ImageCollection("LANDSAT/LT05/C02/T2_TOA").filterDate("2011-01-01", "2011-12-31")
+        trueColor321 = dataset.select(["B3", "B2", "B1"])
+        trueColor321Vis = {
+        "min": 0.0,
+        "max": 0.4,
+        "gamma": 1.2,
+        }
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(trueColor321, trueColor321Vis, "True Color (321)")
+
+    elif cod == "LANDSAT/MANGROVE_FORESTS":
+        dataset = ee.ImageCollection("LANDSAT/MANGROVE_FORESTS")
+        mangrovesVis = {
+        "min": 0,
+        "max": 1.0,
+        "palette": ["d40115"],
+        }
+        Map.setCenter(-44.5626, -2.0164, 9)
+        Map.addLayer(dataset, mangrovesVis, "Mangroves")
+
+    elif cod == "LARSE/GEDI/GEDI02_A_002/GEDI02_A_2021244154857_O15413_04_T05622_02_003_02_V002":
+        dataset = ee.FeatureCollection("LARSE/GEDI/GEDI02_A_002/GEDI02_A_2021244154857_O15413_04_T05622_02_003_02_V002")
+        dataset = dataset.style({"color": "black", "pointSize": 1})
+        Map.setCenter(-64.88, -31.77, 15)
+        Map.addLayer(dataset)
+
+    elif cod == "LARSE/GEDI/GEDI02_A_002_INDEX":
+        rectangle = ee.Geometry.Rectangle([-111.22, 24.06, -6.54, 51.9])
+        filter_index = ee.FeatureCollection("LARSE/GEDI/GEDI02_A_002_INDEX").filter("time_start > 2020-10-10T15:57:18Z" & "time_end < 2020-10-11T01:20:45Z").filterBounds(rectangle)
+        Map.addLayer(filter_index)
+
+    elif cod == "LARSE/GEDI/GEDI02_A_002_MONTHLY":
+        qualityMask = lambda im: im.updateMask(im.select("quality_flag").eq(1)).updateMask(im.select("degrade_flag").eq(0))
+        dataset = ee.ImageCollection("LARSE/GEDI/GEDI02_A_002_MONTHLY").map(qualityMask).select("rh98")
+        gediVis = {
+        "min": 1,
+        "max": 60,
+        "palette": "darkred,red,orange,green,darkgreen",
+        }
+        Map.setCenter(-74.803466, -9.342209, 10)
+        Map.addLayer(dataset, gediVis, "rh98")
+
+    elif cod == "LARSE/GEDI/GEDI02_B_002/GEDI02_B_2021043114136_O12295_03_T07619_02_003_01_V002":
+        dataset = ee.FeatureCollection("LARSE/GEDI/GEDI02_B_002/GEDI02_B_2021043114136_O12295_03_T07619_02_003_01_V002")
+        Map.setCenter(12.60033, 51.01051, 14)
+        Map.addLayer(dataset)
+            
+    elif cod == "LARSE/GEDI/GEDI02_B_002_INDEX":
+        rectangle = ee.Geometry.Rectangle([-111.22, 24.06, -6.54, 51.9])
+        filter_index = ee.FeatureCollection("LARSE/GEDI/GEDI02_B_002_INDEX").filter("time_start > 2020-10-10T15:57:18Z" & "time_end < 2020-10-11T01:20:45Z").filterBounds(rectangle)
+        Map.addLayer(filter_index)
+
+    elif cod == "LARSE/GEDI/GEDI02_B_002_MONTHLY":
+        qualityMask = lambda im: im.updateMask(im.select("l2b_quality_flag").eq(1)).updateMask(im.select("degrade_flag").eq(0))
+        dataset = ee.ImageCollection("LARSE/GEDI/GEDI02_B_002_MONTHLY").map(qualityMask).select("solar_elevation")
+        gediVis = {
+        "min": 1,
+        "max": 60,
+        "palette": "red, green, blue",
+        }
+        Map.setCenter(12.60033, 51.01051, 12)
+        Map.addLayer(dataset, gediVis, "Solar Elevation")
+
+    elif cod == "LARSE/GEDI/GEDI04_A_002/GEDI04_A_2022157233128_O19728_03_T11129_02_003_01_V002":
+        dataset = ee.FeatureCollection("LARSE/GEDI/GEDI04_A_002/GEDI04_A_2022157233128_O19728_03_T11129_02_003_01_V002")
+        Map.setCenter(-94.77616, 38.9587, 14)
+        Map.addLayer(dataset)
+
+    elif cod == "LARSE/GEDI/GEDI04_A_002_INDEX":
+        rectangle = ee.Geometry.Rectangle([-111.22, 24.06, -6.54, 51.9])
+        filter_index = ee.FeatureCollection("LARSE/GEDI/GEDI04_A_002_INDEX").filter("time_start > 2020-10-10T15:57:18Z" & "time_end < 2020-10-11T01:20:45Z").filterBounds(rectangle)
+        Map.addLayer(filter_index)
+
+    elif cod == "LARSE/GEDI/GEDI04_A_002_MONTHLY":
+        qualityMask = lambda im : im.updateMask(im.select("l4_quality_flag").eq(1)).updateMask(im.select("degrade_flag").eq(0))
+        dataset = ee.ImageCollection("LARSE/GEDI/GEDI04_A_002_MONTHLY").map(qualityMask).select("solar_elevation")
+        gediVis = {
+        "min": 1,
+        "max": 60,
+        "palette": "red, green, blue",
+        }
+        Map.setCenter(5.0198, 51.7564, 12)
+        Map.addLayer(dataset, gediVis, "Solar Elevation")
+
+    elif cod == "LARSE/GEDI/GEDI04_B_002":
+        l4b = ee.Image("LARSE/GEDI/GEDI04_B_002")
+        Map.addLayer(
+            l4b.select("MU"), {"min": 10, "max": 250, "palette": "440154,414387,2a788e,23a884,7ad151,fde725"}, "Mean Biomass"
+        )
+        Map.addLayer( l4b.select("SE"), {"min": 10, "max": 50, "palette": "000004,3b0f6f,8c2981,dd4a69,fe9f6d,fcfdbf"}, "Standard Error"
+                    )
+
+    elif cod == "MERIT/DEM/v1_0_3":
+        dataset = ee.Image("MERIT/DEM/v1_0_3")
+        visualization = {
+        "bands": ["dem"],
+        "min": -3,
+        "max": 18,
+        "palette": ["000000", "478FCD", "86C58E", "AFC35E", "8F7131",
+                    "B78D4F", "E2B8A6", "FFFFFF"]
+        }
+        Map.setCenter(90.301, 23.052, 10)
+        Map.addLayer(dataset, visualization, "Elevation")
+
+    elif cod == "MERIT/Hydro/v1_0_1":
+        dataset = ee.Image("MERIT/Hydro/v1_0_1")
+        visualization = {
+        "bands": ["viswth"],
+        }
+        Map.setCenter(90.301, 23.052, 10)
+        Map.addLayer(dataset, visualization, "River width")
+
+    elif cod == "MERIT/Hydro_reduced/v1_0_1":
+        dataset = ee.Image("MERIT/Hydro_reduced/v1_0_1")
+        visualization = {
+        "bands": "wth",
+        "min": 0,
+        "max": 400
+        }
+        Map.setCenter(90.301, 23.052, 10)
+        Map.addLayer(dataset, visualization, "River width")
+
+    elif cod == "MODIS/006/MCD19A2_GRANULES":
+        collection = ee.ImageCollection("MODIS/006/MCD19A2_GRANULES").select("Optical_Depth_047").filterDate("2019-01-01", "2019-01-15")
+        band_viz = {
+        "min": 0,
+        "max": 500,
+        "palette": ["black", "blue", "purple", "cyan", "green", "yellow", "red"]
+        }
+        Map.addLayer(collection.mean(), band_viz, "Optical Depth 047")
+        Map.setCenter(76, 13, 6)
+
+    elif cod == "MODIS/006/MOD10A1":
+        dataset = ee.ImageCollection("MODIS/006/MOD10A1").filter(ee.Filter.date("2018-01-01", "2018-05-01"))
+        snowCover = dataset.select("NDSI_Snow_Cover")
+        snowCoverVis = {
+        "min": 0.0,
+        "max": 100.0,
+        "palette": ["black", "0dffff", "0524ff", "ffffff"],
+        }
+        Map.setCenter(-41.13, 76.35, 2)
+        Map.addLayer(snowCover, snowCoverVis, "Snow Cover")
+
+    elif cod == "MODIS/006/MOD16A2":
+        dataset = ee.ImageCollection("MODIS/006/MOD16A2").filter(ee.Filter.date("2018-01-01", "2018-05-01"))
+        evapotranspiration = dataset.select("ET")
+        evapotranspirationVis = {
+        "min": 0.0,
+        "max": 300.0,
+        "palette": [
+            "ffffff", "fcd163", "99b718", "66a000", "3e8601", "207401", "056201",
+            "004c00", "011301"
+        ],
+        }
+        Map.setCenter(6.746, 46.529, 2)
+        Map.addLayer(evapotranspiration, evapotranspirationVis, "Evapotranspiration")
+
+    elif cod == "MODIS/006/MOD17A2H":
+        dataset = ee.ImageCollection("MODIS/006/MOD17A2H").filter(ee.Filter.date("2018-01-01", "2018-05-01"))
+        gpp = dataset.select("Gpp")
+        gppVis = {
+        "min": 0.0,
+        "max": 600.0,
+        "palette": ["bbe029", "0a9501", "074b03"],
+        }
+        Map.setCenter(6.746, 46.529, 2)
+        Map.addLayer(gpp, gppVis, "GPP")
+
+    elif cod == "MODIS/006/MOD44B":
+        dataset = ee.ImageCollection("MODIS/006/MOD44B")
+        visualization = {
+        "bands": ["Percent_Tree_Cover"],
+        "min": 0.0,
+        "max": 100.0,
+        "palette": ["bbe029", "0a9501", "074b03"]
+        }
+        Map.centerObject(dataset)
+        Map.addLayer(dataset, visualization, "Percent Tree Cover")
+
+    elif cod == "MODIS/006/MOD44W":
+        dataset = ee.ImageCollection("MODIS/006/MOD44W").filter(ee.Filter.date("2015-01-01", "2015-05-01"))
+        waterMask = dataset.select("water_mask")
+        waterMaskVis = {
+        "min": 0.0,
+        "max": 1.0,
+        "palette": ["bcba99", "2d0491"],
+        }
+        Map.setCenter(6.746, 46.529, 2)
+        Map.addLayer(waterMask, waterMaskVis, "Water Mask")
+
+    elif cod == "MODIS/006/MOD44W":
+        dataset = ee.ImageCollection("MODIS/006/MOD44W").filter(ee.Filter.date("2015-01-01", "2015-05-01"))
+        waterMask = dataset.select("water_mask")
+        waterMaskVis = {
+        "min": 0.0,
+        "max": 1.0,
+        "palette": ["bcba99", "2d0491"],
+        }
+        Map.setCenter(6.746, 46.529, 2)
+        Map.addLayer(waterMask, waterMaskVis, "Water Mask")
+
+    elif cod == "MODIS/006/MODOCGA":
+        dataset = ee.ImageCollection("MODIS/006/MODOCGA").filter(ee.Filter.date("2018-01-01", "2018-05-01"))
+        FalseColor = dataset.select(["sur_refl_b11", "sur_refl_b10", "sur_refl_b09"])
+        FalseColorVis = {
+        "min": 0.0,
+        "max": 2000.0}
+        Map.setCenter(6.746, 46.529, 2)
+        Map.addLayer(FalseColor, FalseColorVis, "False Color")
+
+    elif cod == "MODIS/006/MYD10A1":
+        dataset = ee.ImageCollection("MODIS/006/MYD10A1").filter(ee.Filter.date("2018-01-01", "2018-05-01"))
+        snowCover = dataset.select("NDSI_Snow_Cover")
+        snowCoverVis = {
+        "min": 0.0,
+        "max": 100.0,
+        "palette": ["black", "0dffff", "0524ff", "ffffff"],
+        }
+        Map.setCenter(-38.13, 40, 2)
+        Map.addLayer(snowCover, snowCoverVis, "Snow Cover")
+
+    elif cod == "MODIS/006/MYD17A2H":
+        dataset = ee.ImageCollection("MODIS/006/MYD17A2H").filter(ee.Filter.date("2018-01-01", "2018-05-01"))
+        gpp = dataset.select("Gpp")
+        gppVis = {
+        "min": 0.0,
+        "max": 600.0,
+        "palette": ["bbe029", "0a9501", "074b03"],
+        }
+        Map.setCenter(6.746, 46.529, 2)
+        Map.addLayer(gpp, gppVis, "GPP")
+
+    elif cod == "MODIS/006/MYDOCGA":
+        dataset = ee.ImageCollection("MODIS/006/MYDOCGA").filter(ee.Filter.date("2018-01-01", "2018-05-01"))
+        FalseColor = dataset.select(["sur_refl_b11", "sur_refl_b10", "sur_refl_b09"])
+        FalseColorVis = {
+        "min": 0.0,
+        "max": 2000.0,
+        }
+        Map.setCenter(6.746, 46.529, 2)
+        Map.addLayer(FalseColor, FalseColorVis, "False Color")
+
+    elif cod == "MODIS/061/MCD12Q1":
+        dataset = ee.ImageCollection("MODIS/061/MCD12Q1")
+        igbpLandCover = dataset.select("LC_Type1")
+        igbpLandCoverVis = {
+        "min": 1.0,
+        "max": 17.0,
+        "palette": [
+        "05450a", "086a10", "54a708", "78d203", "009900", "c6b044", "dcd159",
+        "dade48", "fbff13", "b6ff05", "27ff87", "c24f44", "a5a5a5", "ff6d4c",
+        "69fff8", "f9ffa4", "1c0dff"
+        ],
+        }
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(igbpLandCover, igbpLandCoverVis, "IGBP Land Cover")
+
+    elif cod == "MODIS/061/MCD12Q2":
+        dataset = ee.ImageCollection("MODIS/061/MCD12Q2").filter(ee.Filter.date("2001-01-01", "2002-01-01"))
+        vegetationPeak = dataset.select("Peak_1")
+        vegetationPeakVis = {
+        "min": 11400,
+        "max": 11868,
+        "palette": ["0f17ff", "b11406", "f1ff23"],
+        }
+        Map.setCenter(6.746, 46.529, 2)
+        Map.addLayer(vegetationPeak, vegetationPeakVis, "Vegetation Peak 2001")
+
+    elif cod == "MODIS/061/MCD15A3H":
+        dataset = ee.ImageCollection("MODIS/061/MCD15A3H")
+        defaultVisualization = dataset.first().select("Fpar")
+        defaultVisualizationVis = {
+        "min": 0.0,
+        "max": 100.0,
+        "palette": ["e1e4b4", "999d60", "2ec409", "0a4b06"],
+        }
+        Map.setCenter(6.746, 46.529, 6)
+        Map.addLayer(
+        defaultVisualization, defaultVisualizationVis, "Default visualization")
+
+    elif cod == "MODIS/061/MCD18C2":
+        dataset = ee.ImageCollection("MODIS/061/MCD18C2").filter(ee.Filter.date("2001-01-01", "2001-02-01"))
+        gmt_1200_par = dataset.select("GMT_1200_PAR")
+        gmt_1200_par_vis = {
+        "min": -236,
+        "max": 316,
+        "palette": ["0f17ff", "b11406", "f1ff23"],
+        }
+        Map.setCenter(6.746, 46.529, 2)
+        Map.addLayer(gmt_1200_par, gmt_1200_par_vis,"Total PAR at GMT 12:00")
+
+    elif cod == "COPERNICUS/CORINE/V20/100m":
+        dataset = ee.Image('COPERNICUS/CORINE/V20/100m/2012')
+        landCover = dataset.select('landcover')
+        Map.setCenter(16.436, 39.825, 6)
+        Map.addLayer(landCover, {}, 'Land Cover')
+    
+    elif cod == "LANDSAT/GLS1975_MOSAIC":
+        dataset = ee.ImageCollection('LANDSAT/GLS1975_MOSAIC')
+        falseColor = dataset.select(['30', '20', '10'])
+        falseColorVis = {
+        "gamma": 1.6,
+        }
+        Map.setCenter(-72.882406,5.181746, 5);
+        Map.addLayer(falseColor, falseColorVis, 'False Color')
+    
+    elif cod == "LANDSAT/LC08/C01/T1_8DAY_BAI":
+        dataset = ee.ImageCollection('LANDSAT/LC08/C01/T1_8DAY_BAI').filterDate('2017-01-01', '2017-12-31')
+        scaled = dataset.select('BAI')
+        scaledVis = {
+        "min": 0.0,
+        "max": 100.0,
+        }
+        Map.setCenter(-72.882406,5.181746, 6)
+        Map.addLayer(scaled, scaledVis, 'Scaled')
+    
+    elif cod == "LANDSAT/LC08/C01/T1_8DAY_EVI":
+        dataset = ee.ImageCollection('LANDSAT/LC08/C01/T1_8DAY_EVI').filterDate('2017-01-01', '2017-12-31')
+        colorized = dataset.select('EVI')
+        colorizedVis = {
+        "min": 0.0,
+        "max": 1.0,
+        "palette": [
+            'FFFFFF', 'CE7E45', 'DF923D', 'F1B555', 'FCD163', '99B718', '74A901',
+            '66A000', '529400', '3E8601', '207401', '056201', '004C00', '023B01',
+            '012E01', '011D01', '011301']
+        }
+        Map.setCenter(-72.882406,5.181746, 6)
+        Map.addLayer(colorized, colorizedVis, 'Colorized')
+    
+    elif cod == "LANDSAT/LC08/C01/T1_8DAY_NDSI":
+        dataset = ee.ImageCollection('LANDSAT/LC08/C01/T1_8DAY_NDSI').filterDate('2017-01-01', '2017-12-31')
+        colorized = dataset.select('NDSI')
+        colorizedVis = {
+        "palette": ['000088', '0000FF', '8888FF', 'FFFFFF'],
+        }
+        Map.setCenter(-72.882406,5.181746, 6);
+        Map.addLayer(colorized, colorizedVis, 'Colorized')
+    
+    elif cod == "LANDSAT/LC08/C01/T1_8DAY_NDVI":
+        dataset = ee.ImageCollection('LANDSAT/LC08/C01/T1_8DAY_NDVI').filterDate('2017-01-01', '2017-12-31')
+        colorized = dataset.select('NDVI')
+        colorizedVis = {
+        "min": 0.0,
+        "max": 1.0,
+        "palette": [
+            'FFFFFF', 'CE7E45', 'DF923D', 'F1B555', 'FCD163', '99B718', '74A901',
+            '66A000', '529400', '3E8601', '207401', '056201', '004C00', '023B01',
+            '012E01', '011D01', '011301']}
+        Map.setCenter(-72.882406,5.181746, 6)
+        Map.addLayer(colorized, colorizedVis, 'Colorized')
+    
+    elif cod == "LANDSAT/LC08/C01/T1_8DAY_NDWI":
+        dataset = ee.ImageCollection('LANDSAT/LC08/C01/T1_8DAY_NDWI').filterDate('2017-01-01', '2017-12-31')
+        colorized = dataset.select('NDWI')
+        colorizedVis = {
+        "min": 0.0,
+        "max": 1.0,
+        "palette": ['0000ff', '00ffff', 'ffff00', 'ff0000', 'ffffff'],
+        };
+        Map.setCenter(-72.882406,5.181746, 6)
+        Map.addLayer(colorized, colorizedVis, 'Colorized')
+    
+    elif cod == "LANDSAT/LC08/C01/T1_8DAY_RAW":
+        dataset = ee.ImageCollection('LANDSAT/LC08/C01/T1_8DAY_RAW').filterDate('2017-01-01', '2017-12-31')
+        visParams = {
+        "min": 0,
+        "max": 20000,
+        "gamma": 1.2,
+        "bands": ['B4', 'B3', 'B2'],
+        }
+        Map.setCenter(-72.882406,5.181746, 6)
+        Map.addLayer(dataset, visParams, 'LANDSAT/LC08/C01/T1_8DAY_RAW')
+    
+    elif cod == "LANDSAT/LC08/C01/T1_8DAY_TOA":
+        dataset = ee.ImageCollection('LANDSAT/LC08/C01/T1_8DAY_TOA').filterDate('2017-01-01', '2017-12-31')
+        trueColor = dataset.select(['B4', 'B3', 'B2'])
+        trueColorVis = {
+        "min": 0,
+        "max": 0.4,
+        "gamma": 1.2,
+        }
+        Map.setCenter(-72.882406,5.181746, 6)
+        Map.addLayer(trueColor, trueColorVis, 'True Color (432)')
+    
+    elif cod == "LANDSAT/LC08/C01/T1_32DAY_BAI":
+        dataset = ee.ImageCollection('LANDSAT/LC08/C01/T1_32DAY_BAI').filterDate('2017-01-01', '2017-12-31')
+        scaled = dataset.select('BAI')
+        scaledVis = {
+        "min": 0.0,
+        "max": 100.0,
+        }
+        Map.setCenter(-72.882406,5.181746, 6)
+        Map.addLayer(scaled, scaledVis, 'Scaled')
+    
+    elif cod == "LANDSAT/LC08/C01/T1_32DAY_EVI":
+        dataset = ee.ImageCollection('LANDSAT/LC08/C01/T1_32DAY_EVI').filterDate('2017-01-01', '2017-12-31')
+        colorized = dataset.select('EVI')
+        colorizedVis = {
+        "min": 0.0,
+        "max": 1.0,
+        "palette": [
+            'FFFFFF', 'CE7E45', 'DF923D', 'F1B555', 'FCD163', '99B718', '74A901',
+            '66A000', '529400', '3E8601', '207401', '056201', '004C00', '023B01',
+            '012E01', '011D01', '011301']
+        }
+        Map.setCenter(-72.882406,5.181746, 6)
+        Map.addLayer(colorized, colorizedVis, 'Colorized')
+    
+    elif cod == "LANDSAT/LC08/C01/T1_32DAY_NBRT":
+        dataset = ee.ImageCollection('LANDSAT/LC08/C01/T1_32DAY_NBRT').filterDate('2017-01-01', '2017-12-31')
+        colorized = dataset.select('NBRT')
+        colorizedVis = {
+        "min": 0.9,
+        "max": 1.0,
+        "palette": ['000000', 'FFFFFF'],
+        }
+        Map.setCenter(-72.882406,5.181746, 6)
+        Map.addLayer(colorized, colorizedVis, 'Colorized')
+    
+    elif cod == "LANDSAT/LC08/C01/T1_32DAY_NDSI":
+        dataset = ee.ImageCollection('LANDSAT/LC08/C01/T1_32DAY_NDSI').filterDate('2017-01-01', '2017-12-31')
+        colorized = dataset.select('NDSI')
+        colorizedVis = {
+        "palette": ['000088', '0000FF', '8888FF', 'FFFFFF'],
+        };
+        Map.setCenter(-72.882406,5.181746, 6)
+        Map.addLayer(colorized, colorizedVis, 'Colorized')
+    
+    elif cod == "LANDSAT/LC08/C01/T1_32DAY_NDVI":
+        dataset = ee.ImageCollection('LANDSAT/LC08/C01/T1_32DAY_NDVI').filterDate('2017-01-01', '2017-12-31')
+        colorized = dataset.select('NDVI')
+        colorizedVis = {
+        "min": 0.0,
+        "max": 1.0,
+        "palette": [
+            'FFFFFF', 'CE7E45', 'DF923D', 'F1B555', 'FCD163', '99B718', '74A901',
+            '66A000', '529400', '3E8601', '207401', '056201', '004C00', '023B01',
+            '012E01', '011D01', '011301']
+        }
+        Map.setCenter(-72.882406,5.181746, 6)
+        Map.addLayer(colorized, colorizedVis, 'Colorized')
+    
+    elif cod == "LANDSAT/LC08/C01/T1_32DAY_NDWI":
+        dataset = ee.ImageCollection('LANDSAT/LC08/C01/T1_32DAY_NDWI').filterDate('2017-01-01', '2017-12-31')        
+        colorized = dataset.select('NDWI');
+        colorizedVis = {
+        "min": 0.0,
+        "max": 1.0,
+        "palette": ['0000ff', '00ffff', 'ffff00', 'ff0000', 'ffffff']
+        }
+        Map.setCenter(-72.882406,5.181746, 6)
+        Map.addLayer(colorized, colorizedVis, 'Colorized')
+    
+    elif cod == "LANDSAT/LC08/C01/T1_32DAY_RAW":
+        dataset = ee.ImageCollection('LANDSAT/LC08/C01/T1_32DAY_RAW').filterDate('2017-01-01', '2017-12-31')
+        visParams = {
+        "min": 0,
+        "max": 20000,
+        "gamma": 1.2,
+        "bands": ['B4', 'B3', 'B2']
+        }
+        Map.setCenter(-72.882406,5.181746, 6)
+        Map.addLayer(dataset, visParams, 'LANDSAT/LC08/C01/T1_32DAY_RAW')
+    
+    elif cod == "LANDSAT/LC08/C01/T1_32DAY_TOA":
+        dataset = ee.ImageCollection('LANDSAT/LC08/C01/T1_32DAY_TOA').filterDate('2017-01-01', '2017-12-31')
+        trueColor = dataset.select(['B4', 'B3', 'B2'])
+        trueColorVis = {
+        "min": 0,
+        "max": 0.4,
+        "gamma": 1.2,
+        }
+        Map.setCenter(-72.882406,5.181746, 6)
+        Map.addLayer(trueColor, trueColorVis, 'True Color (432)')
+    
+    elif cod == "LANDSAT/LC08/C01/T1_ANNUAL_BAI":
+        dataset = ee.ImageCollection('LANDSAT/LC08/C01/T1_ANNUAL_BAI') \
+                  .filterDate('2017-01-01', '2017-12-31')
+        scaled = dataset.select('BAI')
+        scaledVis = {
+        "min": 0.0,
+        "max": 100.0,
+        }
+        Map.setCenter(-72.882406,5.181746, 6)
+        Map.addLayer(scaled, scaledVis, 'Scaled')
+
+    elif cod == "NOAA/DMSP-OLS/CALIBRATED_LIGHTS_V4":
+        dataset = ee.ImageCollection('NOAA/DMSP-OLS/CALIBRATED_LIGHTS_V4')\
+                  .filterDate('2010-01-01', '2010-12-31')
+        nighttimeLights = dataset.select('avg_vis')
+        nighttimeLightsVis = {
+        "min": 3.0,
+        "max": 60.0,
+        }
+        Map.setCenter(7.82, 49.1, 4)
+        Map.addLayer(nighttimeLights, nighttimeLightsVis, 'Nighttime Lights')
+
+    elif cod == "NOAA/VIIRS/DNB/MONTHLY_V1/VCMCFG":
+        dataset = ee.ImageCollection('NOAA/VIIRS/DNB/MONTHLY_V1/VCMCFG').filterDate('2022-01-01', '2023-12-31')
+        nighttime = dataset.select('avg_rad')
+        nighttimeVis = {
+            "min": 0.0,
+            "max": 60.0,
+        }
+        Map.setCenter(67.1056, 24.8904, 8)
+        Map.addLayer(nighttime, nighttimeVis, 'Nighttime')