Classifier with SVM algorithm for sentinel 1A image

Question

I am classifying rice for the Red River Delta with 2 class: class 0: Rice class 1: Not rice

I used svm classifier algorithm. However, after running the code, the classifier operated for a long time without results. Here is my code : Link: https://code.earthengine.google.com/f70f6ae7d54a428829a84cbc9d27ea3b

Code:

//Load 1 shapefile red river delta
var dbsh_shape = ee.FeatureCollection('users/chungpd/DBSH_Shape');
Map.centerObject(dbsh_shape);
Map.addLayer(dbsh_shape);

// Use these bands for prediction.
var bands = ['VV', 'VH'];

// Load an imagecollection over a portion of Red river delta
var img1 = ee.ImageCollection('COPERNICUS/S1_GRD')
  .filterDate('2017-01-03', '2017-01-18')
  .filterBounds(dbsh_shape);

// Cut img1 according to "dbsh_shape" shapefile
var img2 = img1.map(function(image) {return image.clip(dbsh_shape);});

// Mosaic img2
var image = img2.mosaic();
print (image);

// Load training polygons from a Fusion Table.
// The 'class' property stores known class labels.
var polygons = ee.FeatureCollection('ft:1fxOJdG56CUWXy7MWi4KPeCAvKYC4YHFzMbRPU7S3');

// Get the values for all pixels in each polygon in the training.
var training = image.sampleRegions({
  // Get the sample from the polygons FeatureCollection.
  collection: polygons,
  // Keep this list of properties from the polygons.
  properties: ['class'],
  // Set the scale to get Landsat pixels in the polygons.
  scale: 10
});

// Create an SVM classifier with custom parameters.
var classifier = ee.Classifier.svm({
  kernelType: 'RBF',
  gamma: 0.5,
  cost: 10
});

// Train the classifier.
var trained = classifier.train(training, 'class', bands);

// Classify the image.
var classified = image.classify(trained);

// Create a palette to display the classes.
var palette =['00FF00', 'DD0000'];

// Display the classification result and the input image.
//Map.addLayer(image, {bands: ['VV', 'VH'], max: 0.5, gamma: 2});
//Map.addLayer(classified, {min: 0, max: 10, palette: palette}, 'Isrice');
Map.setCenter(105.96999, 20.90339, 7);
//Map.centerObject(image, 10);
Map.addLayer(image, {bands: ['VV', 'VH'], max: 0.4}, 'image');
Map.addLayer(classified, {min: 0, max: 1, palette: ['00FF00', 'DD0000']},
  'classification');

This is the error:

classification error: Layer error: Computation timed out.

Answer 1

Scale refers to the pixel resolution in meters.

So you have reduced the spatial resolution when you replaced scale 10 with 15 or 20.

I think it is why you got the result.