09 split map

Split-panel map¶

The split-panel map requires two layers: left_layer and right_layer. The layer instance can be a string representing a basemap, or an HTTP URL to a Cloud Optimized GeoTIFF (COG), or a folium TileLayer instance.

Uncomment and execute the following code block to install geemap if needed.

In [1]:

# !pip install geemap

# !pip install geemap

In [2]:

import ee
import geemap.foliumap as geemap

import ee import geemap.foliumap as geemap

In [3]:

Map = geemap.Map(height=600)
Map.split_map(left_layer='HYBRID', right_layer='TERRAIN')
Map

Map = geemap.Map(height=600) Map.split_map(left_layer='HYBRID', right_layer='TERRAIN') Map

Out[3]:

Save the map as an HTML webpage.

In [4]:

Map.to_html('split-map.html')

Map.to_html('split-map.html')

Use folium.WmsTileLayer instance.

In [5]:

Map = geemap.Map(center=(40, -100), zoom=4, height=600)
Map.split_map(
    left_layer='NLCD 2001 CONUS Land Cover', right_layer='NLCD 2019 CONUS Land Cover'
)
Map.add_legend(builtin_legend='NLCD')
Map

Map = geemap.Map(center=(40, -100), zoom=4, height=600) Map.split_map( left_layer='NLCD 2001 CONUS Land Cover', right_layer='NLCD 2019 CONUS Land Cover' ) Map.add_legend(builtin_legend='NLCD') Map

Out[5]:

Use Earth Engine layers.

In [6]:

Map = geemap.Map(center=(40, -100), zoom=4, height=600)

nlcd_2001 = ee.Image('USGS/NLCD_RELEASES/2019_REL/NLCD/2001').select('landcover')
nlcd_2019 = ee.Image('USGS/NLCD_RELEASES/2019_REL/NLCD/2019').select('landcover')

left_layer = geemap.ee_tile_layer(nlcd_2001, {}, 'NLCD 2001')
right_layer = geemap.ee_tile_layer(nlcd_2019, {}, 'NLCD 2019')

Map.split_map(left_layer, right_layer)
Map

Map = geemap.Map(center=(40, -100), zoom=4, height=600) nlcd_2001 = ee.Image('USGS/NLCD_RELEASES/2019_REL/NLCD/2001').select('landcover') nlcd_2019 = ee.Image('USGS/NLCD_RELEASES/2019_REL/NLCD/2019').select('landcover') left_layer = geemap.ee_tile_layer(nlcd_2001, {}, 'NLCD 2001') right_layer = geemap.ee_tile_layer(nlcd_2019, {}, 'NLCD 2019') Map.split_map(left_layer, right_layer) Map

Out[6]:

In [7]:

Map.to_html("NLCD.html")

Map.to_html("NLCD.html")

Linked maps¶

In [8]:

import geemap

import geemap

In [9]:

image = (
    ee.ImageCollection('COPERNICUS/S2')
    .filterDate('2018-09-01', '2018-09-30')
    .map(lambda img: img.divide(10000))
    .median()
)

vis_params = [
    {'bands': ['B4', 'B3', 'B2'], 'min': 0, 'max': 0.3, 'gamma': 1.3},
    {'bands': ['B8', 'B11', 'B4'], 'min': 0, 'max': 0.3, 'gamma': 1.3},
    {'bands': ['B8', 'B4', 'B3'], 'min': 0, 'max': 0.3, 'gamma': 1.3},
    {'bands': ['B12', 'B12', 'B4'], 'min': 0, 'max': 0.3, 'gamma': 1.3},
]

labels = [
    'Natural Color (B4/B3/B2)',
    'Land/Water (B8/B11/B4)',
    'Color Infrared (B8/B4/B3)',
    'Vegetation (B12/B11/B4)',
]

geemap.linked_maps(
    rows=2,
    cols=2,
    height="400px",
    center=[38.4151, 21.2712],
    zoom=12,
    ee_objects=[image],
    vis_params=vis_params,
    labels=labels,
    label_position="topright",
)

image = ( ee.ImageCollection('COPERNICUS/S2') .filterDate('2018-09-01', '2018-09-30') .map(lambda img: img.divide(10000)) .median() ) vis_params = [ {'bands': ['B4', 'B3', 'B2'], 'min': 0, 'max': 0.3, 'gamma': 1.3}, {'bands': ['B8', 'B11', 'B4'], 'min': 0, 'max': 0.3, 'gamma': 1.3}, {'bands': ['B8', 'B4', 'B3'], 'min': 0, 'max': 0.3, 'gamma': 1.3}, {'bands': ['B12', 'B12', 'B4'], 'min': 0, 'max': 0.3, 'gamma': 1.3}, ] labels = [ 'Natural Color (B4/B3/B2)', 'Land/Water (B8/B11/B4)', 'Color Infrared (B8/B4/B3)', 'Vegetation (B12/B11/B4)', ] geemap.linked_maps( rows=2, cols=2, height="400px", center=[38.4151, 21.2712], zoom=12, ee_objects=[image], vis_params=vis_params, labels=labels, label_position="topright", )

The folium plotting backend does not support this function.

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Last update: 2022-03-25