/ Upsample MODIS landcover classification (250m) to Landsat
// resolution (30m) using a supervised classifier.

var geometry = /* color: #ffc82d */ee.FeatureCollection(
        [ee.Feature(
            ee.Geometry.Polygon(
                [[[29.9761962890625, 31.592573630393357],
                  [29.981689453125, 30.111869849235248],
                  [32.574462890625, 30.116621582819374],
                  [32.530517578125, 31.620643692450585]]]),
            {
              "system:index": "0"
            })]);

// Use the MCD12 land-cover as training data.
var modisLandcover = ee.Image('MODIS/006/MCD12Q1/2001_01_01')
  .select('LC_Type1	');

// A pallete to use for visualizing landcover images.
var landcoverPalette = [
    '05450a', // water
    '086a10',//grass
    '54a708', //shrublands'369b47', '30eb5b', '387242', // forest
    '78d203', //broadleaf'c3aa69', 'b76031', 'd9903d', '91af40',  // shrub, grass, savanah
    '009900', // savannas
    'c6b044', // envergreen
    'dcd159', // deciduous
    'dade48', // envergreen
    'fbff13',
    'b6ff05', // barren
    '27ff87', // tundra
    'c24f44',
    'a5a5a5',
    'ff6d4c','69fff8',
    'f9ffa4',
    '1c0dff',
];

// A set of visualization parameters using the landcover palette.
var landcoverVisualization = {palette: landcoverPalette, min: 1, max: 17, format: 'png'};
// Center over our region of interest.
Map.centerObject(geometry, 11);
// Draw the MODIS landcover image.
Map.addLayer(modisLandcover, landcoverVisualization, 'MODIS landcover');

// Load and filter Landsat data.
var l7 = ee.ImageCollection('LANDSAT/LE07/C01/T1')
    .filterBounds(geometry)
    .filterDate('2001-01-01', '2002-01-01');

// Draw the Landsat composite, visualizing true color bands.
var landsatComposite = ee.Algorithms.Landsat.simpleComposite({
  collection: l7,
  asFloat: true
});
Map.addLayer(landsatComposite, {min: 0, max: 0.3, bands: ['B3','B2','B1']}, 'Landsat composite');

// Make a training dataset by sampling the stacked images.
var training = modisLandcover.addBands(landsatComposite).sample({
  region: geometry,
  scale: 30,
  numPixels: 1000
});

// Train a classifier using the training data.
var classifier = ee.Classifier.cart().train({
  features: training,
  classProperty: 'Land_Cover_Type_1',
});

// Apply the classifier to the original composite.
var upsampled = landsatComposite.classify(classifier);

// Draw the upsampled landcover image.
Map.addLayer(upsampled, landcoverVisualization, 'Upsampled landcover');

// Show the training area.
Map.addLayer(ee.Image().paint(geometry, 1, 2), null, 'Training region');