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I am having difficulties with masks in Google Earth Engine (GEE).

I need to classify a sentinel image of the GEE. But I don't want the eucalyptus areas in my image to be classified. I have a shapefile that contains all the areas of eucalyptus planted and I would like the GEE to disregard the eucalyptus shapefile area during classification.

How can I do it?

var S2_1 = ee.ImageCollection("COPERNICUS/S2")
    .filterMetadata('MGRS_TILE', 'equals', '21KYT')
    .filterMetadata('CLOUDY_PIXEL_PERCENTAGE','less_than', 1) 
    .filterDate('2020-01-01','2020-07-31')
    .median();
  
//Classificação

var classnames = veg1.merge(past1).merge(past2).merge(agua).merge(past3).merge(veg2);
print(classnames);

var bands = ['B4', 'B3', 'B2'];

var training = S2_1.select(bands).sampleRegions({
  collection: classnames,
  properties:['classe'],
  scale: 10
});

print (training);

var cart = ee.Classifier.cart().train({
  features: training,
  classProperty: 'classe',
  inputProperties: bands
});

var cart_class = cart.select(bands).classify(cart)

1 Answer 1

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It's not entirely clear in the snippet provided which is the shapefile containing the eucalyptus, but masking is an easy task. You might want to transform your shapefile into a raster first where 1 is eucalyptus and everything else is 0. You can do it directly on GEE (https://developers.google.com/earth-engine/guides/reducers_reduce_to_image) or it's easy to do on ArcMap or Qgis. Once you have your shapefile as a raster applying the mask is very simple.

var mask = eucalyptusImage.eq(1); // Finding which pixels equal 1 thus indicating eucalyptus
var S2_2 = S2_1.updateMask(mask); // Masking the image with the predefined mask

Cheers.

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  • through your answer i managed to solve my problem. Convert my raster to ee.Image () // Upload my raster_mask var mask = ee.Image (raster_mask) .eq (0) // convert raster in ee.Image () var S2_2_mask = S2_2.updateMask (mask) //aply the mask in my study area Commented Dec 16, 2020 at 15:08
  • Great! Happy coding!
    – M. Nicolas
    Commented Dec 16, 2020 at 20:32

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