ee.Filter.bounds

AI-generated Key Takeaways

• ee.Filter.bounds creates a filter that passes if an object's geometry intersects the specified geometry.

• Providing a large or complex collection for the geometry argument can negatively impact performance.

• The ee.Filter.bounds method takes a geometry (which can be a ComputedObject, FeatureCollection, or Geometry) and an optional errorMargin argument.

Creates a filter that passes if the object's geometry intersects the given geometry.

Caution: providing a large or complex collection as the geometry argument can result in poor performance. Collating the geometry of collections does not scale well; use the smallest collection (or geometry) that is required to achieve the desired outcome.

Returns the constructed filter.

Usage	Returns
ee.Filter.bounds(geometry, errorMargin)	Filter

Argument	Type	Details
geometry	ComputedObject|FeatureCollection|Geometry	The geometry, feature or collection to intersect with.
errorMargin	ComputedObject|Number, optional	An optional error margin. If a number, interpreted as sphere surface meters.

Examples

Code Editor (JavaScript)

// collection.filterBounds() is preferred.
// A Sentinel-2 surface reflectance image collection for 3 months in 2021.
var ic = ee.ImageCollection('COPERNICUS/S2_SR')
             .filterDate('2021-07-01', '2021-10-01');

// A point geometry for the peak of Mount Shasta, California, USA.
var geom = ee.Geometry.Point(-122.196, 41.411);
print('Images intersecting point geometry',
      ic.filter(ee.Filter.bounds(geom)));

// A feature collection of point geometries for mountain peaks.
var fc = ee.FeatureCollection([
  ee.Feature(ee.Geometry.Point(-122.196, 41.411), {mountain: 'Mount Shasta'}),
  ee.Feature(ee.Geometry.Point(-121.697, 45.374), {mountain: 'Mount Hood'})
]);
print('Images intersecting feature collection',
      ic.filter(ee.Filter.bounds(fc)));

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)

# collection.filterBounds() is preferred.
# A Sentinel-2 surface reflectance image collection for 3 months in 2021.
ic = ee.ImageCollection('COPERNICUS/S2_SR').filterDate('2021-07-01',
                                                       '2021-10-01')

# A point geometry for the peak of Mount Shasta, California, USA.
geom = ee.Geometry.Point(-122.196, 41.411)
print('Images intersecting point geometry:',
      ic.filter(ee.Filter.bounds(geom)).getInfo())

# A feature collection of point geometries for mountain peaks.
fc = ee.FeatureCollection([
    ee.Feature(ee.Geometry.Point(-122.196, 41.411),
               {'mountain': 'Mount Shasta'}),
    ee.Feature(ee.Geometry.Point(-121.697, 45.374),
               {'mountain': 'Mount Hood'})
])
print('Images intersecting feature collection:',
      ic.filter(ee.Filter.bounds(fc)).getInfo())