I have managed to solve my problem, see worked example below, leaving this question in case it's helpful for anyone. Though, as a new user I would be interested if anyone has any advice of a more efficient way of doing this:

I'm calculating the potential for carbon accumulation from forest regrowth in Key Biodiversity Areas within a specific spatial polygon (of migratory bird flyways). My goal is to have a CSV of the area of potential carbon accumulation from forest regrowth of all features in the feature collection.

I have used reduceRegion() on a single image (carbon) to successfully identify the area of a single feature, and now I want to use this over a feature collection of 4,256 features (kba_EA) and store the results in a dictionary including Area and SitRecID (unique KBA identifier).

My code: (https://code.earthengine.google.com/6f3aaa9266954ddc79f636436b2a70c2?asset=projects%2Fee-priority-landscapes%2Fassets%2FKBAsGlobal_09_2022)

// // // // //////////////////////////////////////////////////////////////////////////////////////////////////////////

// Convert kba area into m2 from hectares
var kbam2 = kba.map(function(f) {
    var Area_m2 = ee.Number(f.get("GISArea")).multiply(10000);
    return f.set({"SitRecID": f.get("SitRecID"),
                     "Area_m2": Area_m2});

// Limit kba area to EA polygon
var kba_EA = ee.FeatureCollection(kbam2).filterBounds(EA);

// Limit carbon image to EA polygon
var carbon_EA = ee.Image(carbon).clip(EA).select('b1');

// // // // /////////////////////////////////////////////// // // // // 

// Test using a single feature
var kba_EA_1 = kba_EA.limit(1);

// Calculate the pixel area in square kilometer
var area_carbon = carbon_EA.multiply(ee.Image.pixelArea()).divide(1000*1000);

// Sum the area of potential carbon accumulation in a single kba
var area = area_carbon.reduceRegion({
  reducer: ee.Reducer.sum(),
  geometry: kba_EA_1,
  crsTransform: carbon_EA.projection().getInfo().transform

// // // // /////////////////////////////////////////////// // // // // 

I then converted the image into an image collection and mapped the function across the feature collection, see code below which is a worked example for 3 features. 'Carbon Area', as the potential for carbon accumulation from forest regrowth in km2 is now saved as a property within each feature

// // // // /////////////////////////////////////////////// // // // // 

// Example using three features
var kba_EA_3 = kba_EA.limit(3);

// Function to convert pixel values to area in m2
var pixel_areas = function(image) {
  return image.multiply(ee.Image.pixelArea());

// Turn carbon image into an image collection
var carbon_stack = ee.ImageCollection([carbon_EA]);

// Map function across the crop_stack image collection
var carbon_stack_area = carbon_stack.map(pixel_areas);

//// Calculate total area of potential carbon accumulation for each kba in the feature collection
var results = carbon_stack_area.map(function(image) {
  return image.reduceRegions({
    collection: kba_EA_3,
    reducer: ee.Reducer.sum(),
  }).map(function(f) {
    var carbon_sum = ee.Number(f.get("sum")).divide(1000000);
    return f.set({"SitRecID": f.get("SitRecID"), "Carbon_Area": carbon_sum});

// Flatten the results
var carbon_results = ee.FeatureCollection(results).flatten();

// Function to remove geometry from features 
var remove_geometry = function(feature) {
  return feature.setGeometry(null)};

// Map function to remove geomety from features over the whole feature collection
var carbon_results_table = carbon_results.map(remove_geometry);


I'm a new user so I'm sure there is a better way to do this and I would be very interested to learn how to do so!

1 Answer 1


For avoiding following error message:

List (Error) User memory limit exceeded.

you can export your Feature Collection directly to Drive as CSV as follows:

var getAreaId = kba_EA.toList(kba_EA.size()).map(function (ele) {
  var area = area_carbon.reduceRegion({
    reducer: ee.Reducer.sum(),
    geometry: ee.Feature(ele).geometry(),
  return ee.Feature(null).set('SitRecID', ee.Feature(ele).get('SitRecID'))
                         .set('area', area.get('b1')); 

// Export features, specifying corresponding names.
  collection: ee.FeatureCollection(getAreaId),
  folder: "GEE_Folder", //my export folder
  description: 'getAreaId',  //file name
  fileFormat: "CSV"}); 

Complete code can be accessed here.

After running it in GEE code editor, I got a CSV of following picture with 4257 records in only 3 minutes.

enter image description here


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