Google Earth Engine: Extract percentiles from raster by polygons

google-earth-engine

I have an image with land surface temperatures (LST) and polygons with administrative boundaries (adm3) and want to extract and export spatial statistics as a shapefile of said polyogns so that each feature contains the average raster value.

This works for the mean reducer

// Apply mean reducer 
 var means = LST.reduceRegions({
  collection: adm3,
  scale: 30,
  reducer: ee.Reducer.mean()
});

// Create empty feature
var feature = ee.Feature(null, means);

// Wrap the Feature in a FeatureCollection for export.
var featureCollection = ee.FeatureCollection([feature]);

// Export the FeatureCollection.
Export.table.toDrive({
  collection: featureCollection,
  folder: 'GEE_VN',
  description: 'adm3_LST_mean',
  fileFormat: 'SHP'
});

However, when I want to apply a percentile reducer (10 and 90 percent), the export fails

var p10 = LST.reduceRegions({
  collection: adm3,
  scale: 30,
  reducer: ee.Reducer.percentile([10]) 
});

This is the error message and I see that this is because the percentile reducer returns a dictionary, but I can't manage to address the 10p percentile correctly.

Error: Feature, argument 'metadata': Invalid type. Expected type: Dicationary<Object>. Actual type: FeatureCollection (Error code: 3)

Where do I have to convert the dictionary to a collection?

Best Answer

The output of reduceRegions with a percentile reduce ris already a featureCollection, so no need (and not possible) to define it as a feature and featureCollection. You can just export it directly:

Export.table.toDrive({
  collection: p10,
  folder: 'GEE_VN',
  description: 'adm3_LST_mean',
  fileFormat: 'SHP'
});

With a working example: https://code.earthengine.google.com/1a7916d16dff7991a52bb264e5150c0b

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[GIS] “Batch processing” data of multiple ROIs in Google Earth Engine

Here's an example that hopefully does something like what you want, but you'll need to modify it to meet your requirements for "manually selected marker points" and Sentinel 2.

In general, do NOT use for-loops or getInfo(). To be clear, DO NOT USE FOR LOOPS unless you have a very good reason to be doing so. If you don't know, use map() for all the reasons described here, here, here and here. (And check the same guides for why to NOT use getInfo() or convert to a list as I've done here.) The reason it's OK to do this here (necessary, in fact) is because Export is a client side function and you can't use a client function in map().

// Get some imagery to play with.
var landsat = ee.ImageCollection("LANDSAT/LC08/C01/T1")
    .filterDate('2016-01-01', '2017-01-01');

var composite = ee.Algorithms.Landsat.simpleComposite({
  collection: landsat,
  asFloat: true
});

var rgbVis = {bands: ["B4", "B3", "B2"], min:0, max: 0.3};
Map.addLayer(composite, rgbVis, "RGB");

// This is a hacky way to get a pixel grid at arbitrary resolution.
var pixels = ee.Image.random().multiply(10000000).toInt32()
    .reduceToVectors({
      reducer: ee.Reducer.countEvery(),
      geometry: Map.getBounds(true),
      geometryType: 'bb' ,
      eightConnected: false,
      scale: 20000,
      crs: 'EPSG:4326'
    });
Map.addLayer(pixels);

// Only do this is you have a few regions.  Not suitable for 
// large feature collections.
var pixelsList = pixels.toList(pixels.size());

// This is one of the few places in the EE API where you need 
// a for-loop and a getInfo() call.  Export is a client function.
for (var i=0; i<pixels.size().getInfo(); i++) {
  Export.image.toDrive({
    image: composite, 
    description: 'foo_' + i, 
    fileNamePrefix: 'foo_' + i, 
    region: ee.Feature(pixelsList.get(i)).geometry(), 
    scale: 30, 
  });
}

If you really need precise control over the export regions, you can make lists of coordinates and turn those into a collection of the ROIs you want to export. All that aside, you still need to click 'Run' on the exports. If you want it completely automated, use the Python API and ee.batch.Export followed by task.start().

[GIS] Exporting feature collection in Google Earth Engine

The second argument of ee.Feature must be

properties (Object, optional): A dictionary of metadata properties. If the first parameter is a Feature (instead of a geometry), this is unused.

but you are using a ee.Feature instead of an Object (dictionary). What I understand is that you want to get rid of the geometry and only export the properties. Otherwise you could just export area11.

For exporting the collection without the geometries you can do:

// Wrap the Feature in a FeatureCollection for export.
var featureCollection = area11.map(function(feat){
  var nullfeat = ee.Feature(null)
  return nullfeat.copyProperties(feat)
})

Best Answer

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