You can get statistics in each zone of an Image
or
FeatureCollection
by using reducer.group()
to group the output
of a reducer by the value of a specified input. For example, to compute the total
population and number of housing units in each state, this example groups the output of
a reduction of a census block FeatureCollection
as follows:
// Load a collection of US census blocks. var blocks = ee.FeatureCollection('TIGER/2010/Blocks'); // Compute sums of the specified properties, grouped by state code. var sums = blocks .filter(ee.Filter.and( ee.Filter.neq('pop10', null), ee.Filter.neq('housing10', null))) .reduceColumns({ selectors: ['pop10', 'housing10', 'statefp10'], reducer: ee.Reducer.sum().repeat(2).group({ groupField: 2, groupName: 'state-code', }) }); // Print the resultant Dictionary. print(sums);
The groupField
argument is the index of the input in the selectors array
that contains the codes by which to group, the groupName
argument specifies
the name of the property to store the value of the grouping variable. Since the reducer
is not automatically repeated for each input, the repeat(2)
call is needed.
To group output of image.reduceRegions()
you can specify a grouping band
that defines groups by integer pixel values. This type of computation is sometimes called
"zonal statistics" where the zones are specified as the grouping band and the statistic
is determined by the reducer. In the following example, change in nightlights in the
United States is grouped by land cover category:
// Load a region representing the United States var region = ee.FeatureCollection('USDOS/LSIB_SIMPLE/2017') .filter(ee.Filter.eq('country_na', 'United States')); // Load MODIS land cover categories in 2001. var landcover = ee.Image('MODIS/051/MCD12Q1/2001_01_01') // Select the IGBP classification band. .select('Land_Cover_Type_1'); // Load nightlights image inputs. var nl2001 = ee.Image('NOAA/DMSP-OLS/NIGHTTIME_LIGHTS/F152001') .select('stable_lights'); var nl2012 = ee.Image('NOAA/DMSP-OLS/NIGHTTIME_LIGHTS/F182012') .select('stable_lights'); // Compute the nightlights decadal difference, add land cover codes. var nlDiff = nl2012.subtract(nl2001).addBands(landcover); // Grouped a mean reducer: change of nightlights by land cover category. var means = nlDiff.reduceRegion({ reducer: ee.Reducer.mean().group({ groupField: 1, groupName: 'code', }), geometry: region.geometry(), scale: 1000, maxPixels: 1e8 }); // Print the resultant Dictionary. print(means);
Note that in this example, the groupField
is the index of the band
containing the zones by which to group the output. The first band is index 0, the second
is index 1, etc.