I need help in Google Earth engine

[luannpedro]

Dear members of the community, I need to cut 96 areas with altimetry from 500 meters within an SRTM, later, I need to overlay these areas with other rasters of environmental variables from the soilgrid and worldclim. Within the cropped areas you need to select 30 random points within each area and extract the pixel values per layer of variables and per area. I would like to perform this task in Earth Engine. Would there be a script to perform this task?

[aradfarahani]

// Load the SRTM dataset
var srtm = ee.Image('CGIAR/SRTM90_V4');

// Define the area of interest (AOI)
var aoi = ee.Geometry.Rectangle([xmin, ymin, xmax, ymax]);

// Generate 96 random points within the AOI
var randomPoints = ee.FeatureCollection.randomPoints(aoi, 96);

// Buffer each point to create 500m areas
var areas = randomPoints.map(function(point) {
  return point.buffer(500);
});

// Load SoilGrids and WorldClim datasets
var soilGrids = ee.ImageCollection('SoilGrids/soilgrids250m');
var worldClim = ee.ImageCollection('WORLDCLIM/V1');

// Function to sample points within each area
var samplePoints = function(area) {
  var points = ee.FeatureCollection.randomPoints(area.geometry(), 30);
  var sampled = points.map(function(point) {
    var values = srtm.sample(point).first()
      .combine(soilGrids.sample(point).first())
      .combine(worldClim.sample(point).first());
    return point.set(values);
  });
  return sampled;
};

// Apply the sampling function to each area
var sampledAreas = areas.map(samplePoints).flatten();

// Print the result
print(sampledAreas);

// Export the result to a CSV file
Export.table.toDrive({
  collection: sampledAreas,
  description: 'SampledAreas',
  fileFormat: 'CSV'
});

Explanation:

1. Load the SRTM dataset: We load the SRTM dataset using ee.Image.
2. Define the AOI: Replace [xmin, ymin, xmax, ymax] with the coordinates of your area of interest.
3. Generate 96 random points: We generate 96 random points within the AOI.
4. Buffer each point: Each point is buffered to create a 500m area.
5. Load SoilGrids and WorldClim datasets: We load the SoilGrids and WorldClim datasets.
6. Sample points within each area: For each area, we generate 30 random points and sample the pixel values from the SRTM, SoilGrids, and WorldClim datasets.
7. Export the result: The sampled data is exported to a CSV file.