You'll have to add an image in the background and then display your red classified pixels on top of it. It seems like the image uses a DEM, you could for example pick the SRTM DEM in the GEE.

Play around with the visible parameters to get a nice visualization:

// define the background map variables
var srtmParams = {
  min: -13000,
  max: 15000,
  gamma: 1,
};

// Set the for south-america clipped SRTM image as background
var srtm = SRTM.clipToCollection(mask);
var srtmVis = srtm.visualize(srtmParams);
Map.addLayer(srtmVis)

Then use the blend() function to display your classified images on top of the background. Use the paint() function to display a featurecollection on top of an image.

// Create RGB visualization images for use as animation frames.
var rgbVis = col.map(function(img) {
  return srtmVis
        .paint(mask, srtmParams.max, 2) // max value will be presented in white
        .blend(img.visualize(visParams).clipToCollection(mask));
});

Link to the complete code

You'll have to add an image in the background and then display your red classified pixels on top of it. It seems like the image uses a DEM, you could for example pick the SRTM DEM in the GEE.

Play around with the visible parameters to get a nice visualization:

// define the background map variables
var srtmParams = {
  min: -13000,
  max: 15000,
  gamma: 1,
};

// Set the for south-america clipped SRTM image as background
var srtm = SRTM.clipToCollection(mask);
var srtmVis = srtm.visualize(srtmParams);
Map.addLayer(srtmVis)

Then use the blend() function to display your classified images on top of the background. Use the paint() function to display a featurecollection on top of an image.

// Create RGB visualization images for use as animation frames.
var rgbVis = col.map(function(img) {
  return srtmVis
        .paint(mask, srtmParams.max, 2) // max value will be presented in white
        .blend(img.visualize(visParams).clipToCollection(mask));
});

Link to the complete code

You'll have to add an image in the background and then display your red classified pixels on top of it. It seems like the image uses a DEM, you could for example pick the SRTM DEM in the GEE.

Play around with the visible parameters to get a nice visualization:

// define the background map variables
var srtmParams = {
  min: -13000,
  max: 15000,
  gamma: 1,
};

// Set the for south-america clipped SRTM image as background
var srtm = SRTM.clipToCollection(mask);
var srtmVis = srtm.visualize(srtmParams);
Map.addLayer(srtmVis)

Then use the blend() function to display your classified images on top of the background:

// Create RGB visualization images for use as animation frames.
var rgbVis = col.map(function(img) {
  return srtmVis.blend(img.visualize(visParams).clipToCollection(mask));
});

Link to the complete code

You'll have to add an image in the background and then display your red classified pixels on top of it. It seems like the image uses a DEM, you could for example pick the SRTM DEM in the GEE.

Play around with the visible parameters to get a nice visualization:

// define the background map variables
var srtmParams = {
  min: -13000,
  max: 15000,
  gamma: 1,
};

// Set the for south-america clipped SRTM image as background
var srtm = SRTM.clipToCollection(mask);
var srtmVis = srtm.visualize(srtmParams);
Map.addLayer(srtmVis)

Then use the blend() function to display your classified images on top of the background. Use the paint() function to display a featurecollection on top of an image.

// Create RGB visualization images for use as animation frames.
var rgbVis = col.map(function(img) {
  return srtmVis
        .paint(mask, srtmParams.max, 2) // max value will be presented in white
        .blend(img.visualize(visParams).clipToCollection(mask));
});

Link to the complete code