Generate random points within masked area Google Earth Engine

Question

I'm trying to generate 1000 random points in areas of low tree cover across Africa and then get NDVI data for those points. I can successfully load the Global Forest Change dataset and use a mask to only show areas with 5% or less tree cover. Following suggestions from other post on here I tried to use stratifiedsample to generate my points, however I get various error messages each time I try to run it. I think this may be because the geometry of the masked area is just too complex and large to sample but I'm really not sure.

I also tried using randomPoints to generate the 1000 points across Africa but I'm not clear how I can filter this to get only points in the masked region (end result would have less then 1000 but I could always up the number of initial points generated)

The end result I would like is a FeatureCollection of 1000 points in areas of low tree cover.

Here is my code:

///Import africa boundary layer
var boundary = ee.FeatureCollection("USDOS/LSIB_SIMPLE/2017");
var africa = boundary.filter(ee.Filter.eq('wld_rgn', 'Africa'));
///Import Hansen Globel Forest Change dataset 
var gfc = ee.Image('UMD/hansen/global_forest_change_2021_v1_9').clip(africa);
var treeCover = gfc.select(['treecover2000']);
var lessthan5 = treeCover.lte(5);  // get areas with less than 5% tree cover
var treeCover_lessthan5 = treeCover.updateMask(lessthan5);
Map.addLayer(treeCover_lessthan5);
///Generating points
var samples = treeCover_lessthan5.stratifiedSample({
    region:africa,
    scale:30,
    numPoints:1000,
   geometries:true});
print(samples);
Map.addLayer(samples);
var points = ee.FeatureCollection.randomPoints(
    {region: africa, points: 1000, seed: 0, maxError: 1});
print(points);
Map.addLayer(points);

https://code.earthengine.google.com/0896d784ed501dd8800ae858bab684a6

Answer 1

One solution can be use ee.Image.sample instead of stratifiedSample. But before, will be better convert your masked area in a geometry, see the code:

///Import africa boundary layer
var boundary = ee.FeatureCollection("USDOS/LSIB_SIMPLE/2017");
var africa = boundary.filter(ee.Filter.eq('wld_rgn', 'Africa'));
///Import Hansen Globel Forest Change dataset 
var gfc = ee.Image('UMD/hansen/global_forest_change_2021_v1_9').clip(africa);
var treeCover = gfc.select(['treecover2000']);
var lessthan5 = treeCover.lte(5);  // get areas with less than 5% tree cover
var treeCover_lessthan5 = treeCover.updateMask(lessthan5);

Map.addLayer(treeCover_lessthan5);

//masked area to geometry
var vectors = treeCover_lessthan5.reduceToVectors({
  geometry: africa,
  crs: treeCover_lessthan5.projection(),
  scale: 50000,//I used  big number to reduce the effort
  maxPixels: 1e13,
  bestEffort:true,
  eightConnected: false,
});

//Map.addLayer(vectors);

///Generating points
var samples = treeCover_lessthan5.sample({
    region:vectors,
    scale:30,
    numPixels:1000,
    geometries:true});

print(samples);

Map.addLayer(samples).setShown(1);

check the code