ee.Image.clipToCollection

  • Clips an image to the boundaries of a FeatureCollection, masking data outside the features.

  • Output image retains the original metadata and band structure of the input image.

  • clipToCollection() takes an image and a FeatureCollection as input, returning a clipped image.

  • Useful for focusing analysis on specific geographic regions defined by features.

 Clips an image to a FeatureCollection. The output bands correspond exactly the input bands, except data not covered by the geometry of at least one feature from the collection is masked. The output image retains the metadata of the input image.

UsageReturns
Image.clipToCollection(collection)Image
ArgumentTypeDetails
this: inputImageThe image to clip.
collectionObjectThe FeatureCollection to clip to.

Examples

Code Editor (JavaScript)

// A digital elevation model.
var dem = ee.Image('NASA/NASADEM_HGT/001');

// A FeatureCollection defining Southeast Asia boundary.
var fc = ee.FeatureCollection('USDOS/LSIB_SIMPLE/2017')
             .filter('wld_rgn == "SE Asia"');

// Clip the DEM by the Southeast Asia boundary FeatureCollection.
var demClip = dem.clipToCollection(fc);
print('Clipped image retains metadata and band names', demClip);

// Add layers to the map.
Map.setCenter(110.64, 9.16, 4);
Map.addLayer(dem, {bands: 'elevation', min: 0, max: 2500}, 'Original DEM');
Map.addLayer(fc, {color: 'blue'}, 'FeatureCollection');
Map.addLayer(demClip,
 {bands: 'elevation', min: 0, max: 2500, palette: ['green', 'yellow', 'brown']},
 'Clipped DEM');

Python setup

See the Python Environment page for information on the Python API and using geemap for interactive development.

import ee
import geemap.core as geemap

Colab (Python)

# A digital elevation model.
dem = ee.Image('NASA/NASADEM_HGT/001')

# A FeatureCollection defining Southeast Asia boundary.
fc = ee.FeatureCollection('USDOS/LSIB_SIMPLE/2017').filter(
    'wld_rgn == "SE Asia"'
)

# Clip the DEM by the Southeast Asia boundary FeatureCollection.
dem_clip = dem.clipToCollection(fc)
display('Clipped image retains metadata and band names', dem_clip)

# Add layers to the map.
m = geemap.Map()
m.set_center(110.64, 9.16, 4)
m.add_layer(dem, {'bands': 'elevation', 'min': 0, 'max': 2500}, 'Original DEM')
m.add_layer(fc, {'color': 'blue'}, 'FeatureCollection')
m.add_layer(
    dem_clip,
    {
        'bands': 'elevation',
        'min': 0,
        'max': 2500,
        'palette': ['green', 'yellow', 'brown'],
    },
    'Clipped DEM',
)
m