Saudia XYZ logo Code: split panel map
Main Source: Geemap
Edited by: Saudia.xyz"

In [25]:
# !pip install geemap
In [26]:
import geemap
In [27]:
Map = geemap.Map(center=(24, 45), zoom=5)
Map.split_map(left_layer='HYBRID', right_layer='ROADMAP')
Map
In [28]:
basemaps = geemap.basemaps.keys()
print(basemaps)
dict_keys(['ROADMAP', 'SATELLITE', 'TERRAIN', 'HYBRID', 'ESRI', 'Esri Ocean', 'Esri Satellite', 'Esri Standard', 'Esri Terrain', 'Esri Transportation', 'Esri Topo World', 'Esri National Geographic', 'Esri Shaded Relief', 'Esri Physical Map', 'FWS NWI Wetlands', 'FWS NWI Wetlands Raster', 'Google Maps', 'Google Satellite', 'Google Terrain', 'Google Satellite Hybrid', 'NLCD 2016 CONUS Land Cover', 'NLCD 2013 CONUS Land Cover', 'NLCD 2011 CONUS Land Cover', 'NLCD 2008 CONUS Land Cover', 'NLCD 2006 CONUS Land Cover', 'NLCD 2004 CONUS Land Cover', 'NLCD 2001 CONUS Land Cover', 'USGS NAIP Imagery', 'USGS Hydrography', 'USGS 3DEP Elevation', 'OpenStreetMap.Mapnik', 'OpenStreetMap.BlackAndWhite', 'OpenStreetMap.DE', 'OpenStreetMap.France', 'OpenStreetMap.HOT', 'Gaode.Normal', 'Gaode.Satellite', 'OpenTopoMap', 'Hydda.Full', 'Hydda.Base', 'Esri.WorldStreetMap', 'Esri.DeLorme', 'Esri.WorldTopoMap', 'Esri.WorldImagery', 'Esri.NatGeoWorldMap', 'HikeBike.HikeBike', 'MtbMap', 'CartoDB.Positron', 'CartoDB.DarkMatter', 'NASAGIBS.ModisTerraTrueColorCR', 'NASAGIBS.ModisTerraBands367CR', 'NASAGIBS.ModisTerraBands721CR', 'NASAGIBS.ModisAquaTrueColorCR', 'NASAGIBS.ModisAquaBands721CR', 'NASAGIBS.ViirsTrueColorCR', 'NASAGIBS.ViirsEarthAtNight2012', 'NASAGIBS.BlueMarble3413', 'NASAGIBS.BlueMarble3031', 'NASAGIBS.BlueMarble', 'Strava.All', 'Strava.Ride', 'Strava.Run', 'Strava.Water', 'Strava.Winter', 'Stamen.Terrain', 'Stamen.Toner', 'Stamen.Watercolor'])
In [29]:
for basemap in basemaps:
    print(basemap)
ROADMAP
SATELLITE
TERRAIN
HYBRID
ESRI
Esri Ocean
Esri Satellite
Esri Standard
Esri Terrain
Esri Transportation
Esri Topo World
Esri National Geographic
Esri Shaded Relief
Esri Physical Map
FWS NWI Wetlands
FWS NWI Wetlands Raster
Google Maps
Google Satellite
Google Terrain
Google Satellite Hybrid
NLCD 2016 CONUS Land Cover
NLCD 2013 CONUS Land Cover
NLCD 2011 CONUS Land Cover
NLCD 2008 CONUS Land Cover
NLCD 2006 CONUS Land Cover
NLCD 2004 CONUS Land Cover
NLCD 2001 CONUS Land Cover
USGS NAIP Imagery
USGS Hydrography
USGS 3DEP Elevation
OpenStreetMap.Mapnik
OpenStreetMap.BlackAndWhite
OpenStreetMap.DE
OpenStreetMap.France
OpenStreetMap.HOT
Gaode.Normal
Gaode.Satellite
OpenTopoMap
Hydda.Full
Hydda.Base
Esri.WorldStreetMap
Esri.DeLorme
Esri.WorldTopoMap
Esri.WorldImagery
Esri.NatGeoWorldMap
HikeBike.HikeBike
MtbMap
CartoDB.Positron
CartoDB.DarkMatter
NASAGIBS.ModisTerraTrueColorCR
NASAGIBS.ModisTerraBands367CR
NASAGIBS.ModisTerraBands721CR
NASAGIBS.ModisAquaTrueColorCR
NASAGIBS.ModisAquaBands721CR
NASAGIBS.ViirsTrueColorCR
NASAGIBS.ViirsEarthAtNight2012
NASAGIBS.BlueMarble3413
NASAGIBS.BlueMarble3031
NASAGIBS.BlueMarble
Strava.All
Strava.Ride
Strava.Run
Strava.Water
Strava.Winter
Stamen.Terrain
Stamen.Toner
Stamen.Watercolor
In [30]:
Map = geemap.Map(center=(24, 45), zoom=5)
Map.split_map(left_layer='NLCD 2016 CONUS Land Cover', right_layer='Esri Satellite')
Map
In [31]:
import ee
In [35]:
# https://developers.google.com/earth-engine/datasets/catalog/USGS_NLCD
collection = ee.ImageCollection("COPERNICUS/Landcover/100m/Proba-V-C3/Global")
print(collection.aggregate_array('system:id').getInfo())
['COPERNICUS/Landcover/100m/Proba-V-C3/Global/2015', 'COPERNICUS/Landcover/100m/Proba-V-C3/Global/2016', 'COPERNICUS/Landcover/100m/Proba-V-C3/Global/2017', 'COPERNICUS/Landcover/100m/Proba-V-C3/Global/2018', 'COPERNICUS/Landcover/100m/Proba-V-C3/Global/2019']
In [36]:
nlcd_2015 = ee.Image('COPERNICUS/Landcover/100m/Proba-V-C3/Global/2015').select('discrete_classification')
nlcd_2019 = ee.Image('COPERNICUS/Landcover/100m/Proba-V-C3/Global/2019').select('discrete_classification')

left_layer = geemap.ee_tile_layer(nlcd_2015, {}, 'Land Cover')
right_layer = geemap.ee_tile_layer(nlcd_2019, {}, 'Land Cover')

Map = geemap.Map(center=(24, 45), zoom=5)
Map.split_map(left_layer, right_layer)
Map