Land Degradation Mapping with NDVI Trends and DeepSeek

// Define region of interest (North Morocco).
var geometry = ee.Geometry.Rectangle([-6, 32, -2, 35]);

// Function to calculate NDVI.
var addNDVI = function(image) {
  var ndvi = image.normalizedDifference(['B5', 'B4']).rename('NDVI');
  return image.addBands(ndvi);
};

// Load Landsat 8 data and filter by date and location.
var collection = ee.ImageCollection('LANDSAT/LC08/C01/T1_SR')
    .filterDate('2015-01-01', '2023-12-31')
    .filterBounds(geometry)
    .map(addNDVI);

// Function to mask clouds using the pixel_qa band.
var maskClouds = function(image) {
  var qa = image.select('pixel_qa');
  var cloudShadowBitMask = 1 << 3;
  var cloudsBitMask = 1 << 5;
  var mask = qa.bitwiseAnd(cloudShadowBitMask).eq(0)
      .and(qa.bitwiseAnd(cloudsBitMask).eq(0));
  return image.updateMask(mask);
};

collection = collection.map(maskClouds);

// Create a time series of NDVI.
var ndviTimeSeries = collection.select('NDVI').toBands();

// Calculate a linear trend.
var trend = collection.select(['NDVI', 'system:time_start'])
  .reduce(ee.Reducer.linearFit());

// Get the slope of the trend (NDVI change per unit of time).
var slope = trend.select('scale').rename('NDVI_trend');

// Get the p-value of the trend.
var pValue = trend.select('p');

// Mask out insignificant trends (p > 0.05).
var significantTrend = slope.updateMask(pValue.lte(0.05));

// Display the trend.
Map.addLayer(significantTrend, {min: -0.1, max: 0.1, palette: 'red, white, green'}, 'NDVI Trend');

// Export the NDVI trend image to Google Drive.
Export.image.toDrive({
  image: slope,
  description: 'NDVI_trend_North_Morocco',
  folder: 'GEE_Exports',
  scale: 30,
  region: geometry,
  maxPixels: 1e13
});