Getting geometry of a feature for reduceRegion function in GEE

Question

I would like to do an analysis for a few countries. I want to write a loop that calculates the loss for a given slope for each country. I have a problem with geometry in reduceRegion function. It doesn't accept the geometry I provide. I already did the same analysis for a country(with peru.geometry()), and it worked. But now, I am getting the following error when I call countries from a list by .get(), List (Error) Image.reduceRegion, argument 'geometry': Invalid type. Expected type: Geometry. Actual type: Feature.

How can I get the geometry of a feature in GEE? and How can I add this geometry to the code? here is the link for my script: https://code.earthengine.google.com/3a7d3053935e83b15e216dbef2056522

Answer 1

You have to cast the ee.Feature() to a ee.Geometry(). From get(), the GEE does not now what kind of object is returned. Cast is to an ee.Feature() and then get the geometry from that feature using .geometry()

var loss =  function(d) {
    var loss1 = arealossinForest.addBands(lossyearinforest)
                  .updateMask(slclasses.get(1))
                  .reduceRegion({
                     reducer: ee.Reducer.sum().group({
                      groupField: 1
                        }),
                        geometry: ee.Feature(countries.get(d)).geometry(),
                        maxPixels: 1e9,
                        bestEffort: true});
             return loss1 };

A second option would be to make the variable countries an ee.FeatureCollection and use .reduceRegions():

var countries = ee.FeatureCollection([argentina, vietnam]);

var loss =  function(d) {
    var loss1 = arealossinForest.addBands(lossyearinforest)
                  .updateMask(slclasses.get(1))
                  .reduceRegions({
                     reducer: ee.Reducer.sum().group({
                      groupField: 1
                        }),
                        collection: countries,
                        tileScale: 8}); // higher number will speed up calculation
             return loss1 };

As you do not have the arguments bestEffort and maxPixels, it might not be preferred for your situation.