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I am trying to export images of MODIS landcover classifications and classified Landsat 7 images.

However, my codes only result in black images rather than what I see if I add the layers to the Map.

How do I correctly export those images to drive?

My current code is:

// Use the MCD12 land-cover as training data.
var modisLandcover = ee.Image('MODIS/051/MCD12Q1/2011_01_01')
  .select('Land_Cover_Type_1');

// A pallete to use for visualizing landcover images.
var landcoverPalette = [
    'aec3d4', // water
    '152106', '225129', '369b47', '30eb5b', '387242', // forest
    '6a2325', 'c3aa69', 'b76031', 'd9903d', '91af40',  // shrub, grass, savanah
    '111149', // wetlands
    '8dc33b', // croplands
    'cc0013', // urban
    '6ca80d', // crop mosaic
    'd7cdcc', // snow and ice
    'f7e084', // barren
    '6f6f6f'  // tundra
];

// A set of visualization parameters using the landcover palette.
var landcoverVisualization = {palette: landcoverPalette, min: 0, max: 17, format: 'png'};
// Center over our region of interest.
Map.centerObject(geometry, 9);
// 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('2011-01-01', '2012-01-01')
    .sort('CLOUD_COVER', false);            //sort by cloud cover ('false' indivcates descending )

// 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,
  seed: 0
});


// Train a classifier using the training data. USING CART() classifier
//var classifier = ee.Classifier.cart().train({
var classifier = ee.Classifier.randomForest(100).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, 'Classified Image');



///////////////////////////////
// EXPORT LANDCVER DATA AND CLASSIIED IMAGE


Export.image.toDrive({
  image: modisLandcover.select('Land_Cover_Type_1'),
  description: '2011_classifiedMODIS',
  folder: "Syria",
  scale: 30,
  region: geometry
  });


Export.image.toDrive({
  image: landsatComposite,
  description: '2011_classifiedL7',
  folder: "Syria",
  scale: 30,
  region: geometry
  });

Export.image.toDrive({
  image: upsampled.select("classification"),
  description: '2011_classified',
  folder: "Syria",
  scale: 30,
  region: geometry
  });

  Export.image.toAsset({
  image: landsatComposite,
  description: '2011_classifiedL7A',
  scale: 30,
  region: geometry
  })

  Export.image.toAsset({
  image: modisLandcover.select('Land_Cover_Type_1'),
  description: '2011_classifiedMODISA',
  scale: 30,
  region: geometry
  });

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