Research Note #26 - Filtering Data and Making Standard Deviation using Google Earth Engine

So, there are two main objectives of this script: display data based on a certain threshold value (in this case, reflectance < 1000) and make a standard deviation from the results. The Data used in this example was Sentinel-2 MSI Level 2A, in the period between November 1 - 15, 2019. Cloud masking was utilized at the beginning of the script to choose granules which were clear from clouds.

// Create a geometry representing the analysis region.

var daerah = ee.Geometry.Rectangle([72.611536, 28.354144, 78.807625, 32.630466]); 

/**

 * Function to mask clouds using the Sentinel-2 QA band

 * @param {ee.Image} image Sentinel-2 image

 * @return {ee.Image} cloud masked Sentinel-2 image

 */

function maskS2clouds(image) {

  var qa = image.select('QA60');

  // Bits 10 and 11 are clouds and cirrus, respectively.

  var cloudBitMask = 1 << 10;

  var cirrusBitMask = 1 << 11;

  // Both flags should be set to zero, indicating clear conditions.

  var mask = qa.bitwiseAnd(cloudBitMask).eq(0)

      .and(qa.bitwiseAnd(cirrusBitMask).eq(0)

 // Choose pixels with reflectance < 1000

      .and(image.lt(1000))

      );

  return image.updateMask(mask).divide(10000);

}

// Map the function over the analysis region and period

// Load Sentinel-2 TOA reflectance data.

var datasentinel = ee.ImageCollection('COPERNICUS/S2')

                  .filterDate('2019-11-01', '2019-11-15')

                  .filterBounds(daerah)

                  // Pre-filter to get less cloudy granules.

                  .filter(ee.Filter.lt('CLOUDY_PIXEL_PERCENTAGE', 20))

                  .map(maskS2clouds)

                  ;

// Get the standard Deviation.

var hasil = datasentinel.reduce(ee.Reducer.stdDev());

// Define the plot parameter, use the standard deviation of Band 4 only  

var stdevVis = {

  min: 0,

  max: 0.005,

  bands: ['B4_stdDev'],

  palette: ['0000FF', '00FFFF', '00FF00', 'FFFF00', 'FF0000']

};

// Add the plot layer on the map

Map.addLayer(hasil, stdevVis, 'Std Deviation');

Map.setCenter(75.7095805, 30.492305, 14);

And the result will be like this:

You may seen some pixels with very high standard deviation values (shown in red, cyan or anything else other than blue). To 'clean-up' these pixels, we can add another filter to the standard deviation results. For example to show the values no higher than 0.000001:

// Get the standard Deviation.

var hasil = datasentinel.reduce(ee.Reducer.stdDev());

var hi_stddev = hasil.lt(0.000001);

var hasil = hasil.updateMask(hi_stddev);

The result will be like this:

Finally, we can overlay the base Google Map using the result by choosing the Satellite map (button on the right corner of the map).