Initial commit with cleaned history

2024-09-01 18:09:25 +02:00
commit 208004e9d0
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+// Detailed information: https://docs.google.com/document/d/1mNIRB90jwLuASO1JYas1kuOXCLbOoy1Z4NlV1qIXM10/edit
+
+var imageCollection = ee.ImageCollection("LANDSAT/LC08/C02/T1_L2");
+    
+var roi = 
+    ee.Geometry.Polygon(
+        [[[120.34892531309845, 43.64119426062719],
+          [120.34892531309845, 43.618332108842225],
+          [120.39218398009064, 43.618332108842225],
+          [120.39218398009064, 43.64119426062719]]], null, false);
+
+Map.centerObject(roi, 12)
+
+
+var l8sr = imageCollection
+  .filterBounds(roi);
+
+// This field contains UNIX time in milliseconds.
+var timeField = 'system:time_start';
+
+function maskL8sr(image) {
+  // Bit 0 - Fill
+  // Bit 1 - Dilated Cloud
+  // Bit 2 - Cirrus
+  // Bit 3 - Cloud
+  // Bit 4 - Cloud Shadow
+  var qa = image.select('QA_PIXEL')
+  
+  var cloud = qa.bitwiseAnd(1 << 1)
+          .or(qa.bitwiseAnd(1 << 2))
+          .or(qa.bitwiseAnd(1 << 3))
+          .or(qa.bitwiseAnd(1 << 4))
+
+
+  // The flags should equal zero, indicating clear conditions.
+  var mask = cloud.eq(0);
+      //var ndwiMasked = ndwi.updateMask(ndwi.gte(0.4)); 
+  // Apply the scaling factors to the appropriate bands.
+  var opticalBands = image.select('SR_B.').multiply(0.0000275).add(-0.2);
+
+  // Replace the original bands with the scaled ones and apply the masks.
+  return image.addBands(opticalBands, null, true)
+      .updateMask(mask)
+      .copyProperties(image, ['system:time_start']);
+}
+
+// Use this function to add variables for NDVI, time and a constant
+// to Landsat 8 imagery.
+var addVariables = function(image) {
+  // Compute time in fractional years since the epoch.
+  var date = ee.Date(image.get(timeField));
+  var years = date.difference(ee.Date('1970-01-01'), 'year');
+  // Return the image with the added bands.
+  return image
+    // Add an NDVI band.
+    .addBands(image.normalizedDifference(['SR_B5', 'SR_B4']).rename('NDVI'))
+    // Add a time band.
+    .addBands(ee.Image(years).rename('t'))
+    .float()
+    // Add a constant band.
+    .addBands(ee.Image.constant(1));
+};
+
+// Remove clouds, add variables and filter to the area of interest.
+var filteredLandsat = l8sr
+  .filterBounds(roi)
+  .filter(ee.Filter.calendarRange(8,8, 'month'))
+  .map(maskL8sr)
+  .map(addVariables);
+
+
+// Plot a time series of NDVI at a single location.
+var l8Chart = ui.Chart.image.series(filteredLandsat.select('NDVI'), roi)
+    .setChartType('ScatterChart')
+    .setOptions({
+      title: 'Landsat 8 NDVI time series at ROI',
+      trendlines: {0: {
+        color: 'CC0000'
+      }},
+      lineWidth: 1,
+      pointSize: 3,
+    });
+print(l8Chart);
+
+// Display the overall mean NDVI of the time series
+Map.addLayer(filteredLandsat.select('NDVI').first(), {min: 0, max: 1}, "Mean NDVI")
+
+
+// List of the independent variable names
+var independents = ee.List(['constant', 't']);
+
+// Name of the dependent variable.
+var dependent = ee.String('NDVI');
+
+// Compute a linear trend.  This will have two bands: 'residuals' and 
+// a 2x1 band called coefficients (columns are for dependent variables).
+var trend = filteredLandsat.select(independents.add(dependent))
+    .reduce(ee.Reducer.linearRegression(independents.length(), 1));
+Map.addLayer(trend, {}, 'trend array image');
+
+// Flatten the coefficients into a 2-band image
+var coefficients = trend.select('coefficients')
+  .arrayProject([0])
+  .arrayFlatten([independents]);
+
+print(coefficients)
+
+
+Map.addLayer(coefficients.select('t'), {min: -0.05, max: 0.05}, "gain b")
+Map.addLayer(coefficients.select('constant'),{min: -0.1, max: 1}, "offset a")
+