Flattens collections of collections.
Usage Returns FeatureCollection. flatten ()
FeatureCollection
Argument Type Details this: collection
FeatureCollection The input collection of collections.
Examples
// Counties in New Mexico, USA.
var counties = ee . FeatureCollection ( 'TIGER/2018/Counties' )
. filter ( 'STATEFP == "35"' );
// Monthly climate and climatic water balance surfaces for January 2020.
var climate = ee . ImageCollection ( 'IDAHO_EPSCOR/TERRACLIMATE' )
. filterDate ( '2020-01' , '2020-02' );
// Calculate mean climate variables for each county per climate surface
// time step. The result is a FeatureCollection of FeatureCollections.
var countiesClimate = climate . map ( function ( image ) {
return image . reduceRegions ({
collection : counties ,
reducer : ee . Reducer . mean (),
scale : 5000 ,
crs : 'EPSG:4326'
});
});
// Note that a printed FeatureCollection of FeatureCollections is not
// recursively expanded, you cannot view metadata of the features within the
// nested collections until you isolate a single collection or flatten the
// collections.
print ( 'FeatureCollection of FeatureCollections' , countiesClimate );
print ( 'Flattened FeatureCollection of FeatureCollections' ,
countiesClimate . flatten ());
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
# Counties in New Mexico, USA.
counties = ee . FeatureCollection ( 'TIGER/2018/Counties' ) . filter ( 'STATEFP == "35"' )
# Monthly climate and climatic water balance surfaces for January 2020.
climate = ee . ImageCollection ( 'IDAHO_EPSCOR/TERRACLIMATE' ) . filterDate (
'2020-01' , '2020-02' )
# Calculate mean climate variables for each county per climate surface
# time step. The result is a FeatureCollection of FeatureCollections.
def reduce_mean ( image ):
return image . reduceRegions ( ** {
'collection' : counties ,
'reducer' : ee . Reducer . mean (),
'scale' : 5000 ,
'crs' : 'EPSG:4326'
})
counties_climate = climate . map ( reduce_mean )
# Note that a printed FeatureCollection of FeatureCollections is not
# recursively expanded, you cannot view metadata of the features within the
# nested collections until you isolate a single collection or flatten the
# collections.
print ( 'FeatureCollection of FeatureCollections:' , counties_climate . getInfo ())
print ( 'Flattened FeatureCollection of FeatureCollections:' ,
counties_climate . flatten () . getInfo ())