AI-generated Key Takeaways
-
This function converts intersecting image pixels within given regions to a FeatureCollection.
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Each output feature includes properties from input image bands and optionally from the input feature.
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Geometries in the output will be aligned with pixel centers.
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The method returns a FeatureCollection.
Note that geometries will be snapped to pixel centers.
| Usage | Returns |
|---|---|
Image.
sampleRegions
(collection, properties
, scale
, projection
, tileScale
, geometries
)
|
FeatureCollection |
| Argument | Type | Details |
|---|---|---|
|
this:
image
|
Image | The image to sample. |
collection
|
FeatureCollection | The regions to sample over. |
properties
|
List, default: null | The list of properties to copy from each input feature. Defaults to all non-system properties. |
scale
|
Float, default: null | A nominal scale in meters of the projection to sample in. If unspecified, the scale of the image's first band is used. |
projection
|
Projection, default: null | The projection in which to sample. If unspecified, the projection of the image's first band is used. If specified in addition to scale, rescaled to the specified scale. |
tileScale
|
Float, default: 1 | A scaling factor used to reduce aggregation tile size; using a larger tileScale (e.g., 2 or 4) may enable computations that run out of memory with the default. |
geometries
|
Boolean, default: false | If true, the results will include a point geometry per sampled pixel. Otherwise, geometries will be omitted (saving memory). |
Examples
Code Editor (JavaScript)
// A Sentinel-2 surface reflectance image. var img = ee . Image ( 'COPERNICUS/S2_SR/20210109T185751_20210109T185931_T10SEG' ); Map . setCenter ( - 122.503881 , 37.765588 , 18 ); Map . addLayer ( img , { bands : [ 'B11' , 'B8' , 'B3' ], min : 100 , max : 4500 }, 'img' ); // A feature collection with two polygon regions each intersecting 36 // pixels at 10 m scale. var fcPolygon = ee . FeatureCollection ([ ee . Feature ( ee . Geometry . Rectangle ( - 122.50620929 , 37.76502806 , - 122.50552264 , 37.76556663 ), { id : 0 }), ee . Feature ( ee . Geometry . Rectangle ( - 122.50530270 , 37.76565568 , - 122.50460533 , 37.76619425 ), { id : 1 }) ]); Map . addLayer ( fcPolygon , { color : 'yellow' }, 'fcPolygon' ); var fcPolygonSamp = img . sampleRegions ({ collection : fcPolygon , scale : 10 , geometries : true }); // Note that 7 pixels are missing from the sample. If a pixel contains a masked // band value it will be excluded from the sample. In this case, the TCI_B band // is masked for each unsampled pixel. print ( 'A feature per pixel (at given scale) in each region' , fcPolygonSamp ); Map . addLayer ( fcPolygonSamp , { color : 'purple' }, 'fcPolygonSamp' ); // A feature collection with two points intersecting two different pixels. // This example is included to show the behavior for point geometries. In // practice, if the feature collection is all points, ee.Image.reduceRegions // should be used instead to save memory. var fcPoint = ee . FeatureCollection ([ ee . Feature ( ee . Geometry . Point ([ - 122.50309256 , 37.76605006 ]), { id : 0 }), ee . Feature ( ee . Geometry . Point ([ - 122.50344661 , 37.76560903 ]), { id : 1 }) ]); Map . addLayer ( fcPoint , { color : 'cyan' }, 'fcPoint' ); var fcPointSamp = img . sampleRegions ({ collection : fcPoint , scale : 10 }); print ( 'A feature per point' , fcPointSamp );
import ee import geemap.core as geemap
Colab (Python)
# A Sentinel-2 surface reflectance image. img = ee . Image ( 'COPERNICUS/S2_SR/20210109T185751_20210109T185931_T10SEG' ) m = geemap . Map () m . set_center ( - 122.503881 , 37.765588 , 18 ) m . add_layer ( img , { 'bands' : [ 'B11' , 'B8' , 'B3' ], 'min' : 100 , 'max' : 4500 }, 'img' ) display ( m ) # A feature collection with two polygon regions each intersecting 36 # pixels at 10 m scale. fc_polygon = ee . FeatureCollection ([ ee . Feature ( ee . Geometry . Rectangle ( - 122.50620929 , 37.76502806 , - 122.50552264 , 37.76556663 ), { 'id' : 0 }, ), ee . Feature ( ee . Geometry . Rectangle ( - 122.50530270 , 37.76565568 , - 122.50460533 , 37.76619425 ), { 'id' : 1 }, ), ]) m . add_layer ( fc_polygon , { 'color' : 'yellow' }, 'fc_polygon' ) fc_polygon_samp = img . sampleRegions ( collection = fc_polygon , scale = 10 , geometries = True ) # Note that 7 pixels are missing from the sample. If a pixel contains a masked # band value it will be excluded from the sample. In this case, the TCI_B band # is masked for each unsampled pixel. display ( 'A feature per pixel (at given scale) in each region' , fc_polygon_samp ) m . add_layer ( fc_polygon_samp , { 'color' : 'purple' }, 'fc_polygon_samp' ) # A feature collection with two points intersecting two different pixels. # This example is included to show the behavior for point geometries. In # practice, if the feature collection is all points, ee.Image.reduceRegions # should be used instead to save memory. fc_point = ee . FeatureCollection ([ ee . Feature ( ee . Geometry . Point ([ - 122.50309256 , 37.76605006 ]), { 'id' : 0 }), ee . Feature ( ee . Geometry . Point ([ - 122.50344661 , 37.76560903 ]), { 'id' : 1 }), ]) m . add_layer ( fc_point , { 'color' : 'cyan' }, 'fc_point' ) fc_point_samp = img . sampleRegions ( collection = fc_point , scale = 10 ) display ( 'A feature per point' , fc_point_samp )
