I have a problem in the supervised classification output. The classification itself is giving any problem, but when I try to print or display the image I obtain this error:

Image (Error) Unable to use a collection in an algorithm that requires a feature or image. This may happen when trying to use a collection of collections where a collection of features is expected; use flatten, or map a function to convert inner collections to features. Use clipToCollection (instead of clip) to clip an image to a collection.

Here is the code: https://code.earthengine.google.com/9dae0afc574251bd102e81e10850dd82

I'm pretty sure that the problem is from line 103 to 128. Here I created a polygon from a raster, and set it as a FeatureCollection in order to set a class WATER with value = 1. If I use polygons created by giving the coordinates of nodes, I don't have this problem in the classification. I'll attach another link where I use polygons and don't have any problem: https://code.earthengine.google.com/6b03174ebd1c75a9281944c4a17c78b3

The problem is that I need to use the polygon from the raster and I have no clue how to solve this problem.

1 Answer 1


I am not 100 % sure if I have solved the complete issue as the resulting classification still seems weird to me but at least I managed to get rid of the error message.

I think the issue was with the variable trainingSet. When I printed it, it was a featurecollection of: (1) a very weird looking MultiPolygon with many self-intersects and (2) a feature collection spread over the entire ROI.

Sampling the regions does not seem to work with this weird list of a Multipolygon and Feature collection but when I extract the second feature collection and only sample these regions, the code is working.

I hope this helps!

// creation of the training set
var trainingSet = classW.merge(classNoW);

trainingSet = trainingSet.toList(2);
var weirdPols = ee.Feature(trainingSet.get(1));
Map.addLayer(weirdPols, null, 'Weird Polygons');
trainingSet = ee.FeatureCollection(trainingSet.get(1));
Map.addLayer(trainingSet, null, 'TrainingSet');
  • unfortunately it doesn't solve the problem. The real difference between the two codes that I sent are in the feature ClassNoW. In the second one (the one that is working) the feature ClassNoW is derived by the transformation into a Feature Collection of a MultiPolygon created as the feature ClassW, so "a very weird looking MultiPolygon with many self-intersects". To transform it and set a label and a value for the classification I used this code: var classW = ee.FeatureCollection([ ee.Feature(multiPolyW, {'WATER': 1})]);. Jun 3, 2020 at 12:59
  • for the first code I used a polygon that is "a feature collection spread over the entire ROI". I transformed a raster layer into a vector layer obtaining a polygon. But when I try to transform it and create the label Water to give it a value of 1, using the same code of the previous comment it does not create any new label. So I used this one: var vSlope1 = vSlope.set('WATER', 1); var classNoW = ee.FeatureCollection([ ee.Feature(vSlope1, {'WATER': 1})]);. But I obtain the problem of the question. Jun 3, 2020 at 13:09

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