Google Earth Engine – Reducing ImageCollection to a Single Band

google-earth-engine

I have an image collection that is a binary layer that indicates whether there is a burn or not in each pixel, for the specified time period by which I filtered the satellite images. This is calculated from the differences in the Normalized Burn ratio (dNBR), calculated for each image. A pixel has value 1 (which means it is burned) if the dNBR value is above the threshold value for a pixel, both when looking at the difference between NBR of day1 and day2, and looking at the difference between NBR of day1 and day3. Now I want to reduce the image collection to an image such that each pixel that burnt at any point of time (within the given time period) has a positive value and attach a timestamp as a band to the image, such that each burnt value pixel has a time of burn. The way I am implementing it is by adding a date band to the original filtered image collection, then finding the dNBR and then reducing the image collection by max() reducer. But the problem is the reducer is maximising even the time band and I am getting only one value as the time stamp. Is there a way to apply reduce to only one value and retain the value of the other band which the maximum value was part of? I have been breaking my head over it for quite some time. Please help

var vis = {"opacity":1,"bands":["B4","B3","B2"],"gamma":3.464},
sent = ee.ImageCollection("COPERNICUS/S2")

var land = sent2.filterBounds(geometry).filterDate("2019-01-01","2019-06-01")
.filterMetadata("MGRS_TILE","equals",'44RLT')
.filter(ee.Filter.lt("CLOUDY_PIXEL_PERCENTAGE",5));
var landsort = land.sort("system:time_start");
print(landsort);

var addDate = function(image){
  var doy = image.date().getRelative('day', 'year');
  var doyBand = ee.Image.constant(doy).uint16().rename('doy')
  doyBand = doyBand.updateMask(image.select('B8').mask())

  return image.addBands(doyBand);
};

var a = ee.ImageCollection(landsort.toList(landsort.size()));
var a = a.map(addDate)
var a = a.toList(a.size())
var b = function(image){
 var nbr3 = ee.Image(image).normalizedDifference(["B8","B12"]);
 var nbr2 = ee.Image(a.get(a.indexOf(image).subtract(1))).normalizedDifference(["B8","B12"]);
 var nbr1 = ee.Image(a.get(a.indexOf(image).subtract(2))).normalizedDifference(["B8","B12"]);

 var e = nbr1.subtract(nbr2).gt(0.3);
 var f = nbr1.subtract(nbr3).gt(0.3);
 var g = e.multiply(f);
 var h = g.addBands(ee.Image(a.get(a.indexOf(image).subtract(2)))
.metadata('system:time_start'));
 return h;
};
var dnrcollect = ee.ImageCollection(a.map(b)).max();
Map.addLayer(dnrcollect)

Best Answer

Use: col.reduce(ee.Reducer.max(nBands)) instead of col.max().

The ee.Reducer.max() reducer allows you to specify additional bands to be included in the resulting image whose pixel values correspond to whatever image had the max value (of first band) among constituents.

From your example:

ee.ImageCollection(a.map(b)).reduce(ee.Reducer.max(NEED TO SPECIFY NUMBER OF EXTRA BANDS))

A toy example - use the inspector and expand all of the layer info to verify (see image below):

/**
 * @license
 * Copyright 2019 Google LLC.
 * SPDX-License-Identifier: Apache-2.0
 */

// Make some images with a data band and a date band.
var img1 = ee.Image.random(10).addBands(ee.Image.constant(10)).float().rename('data', 'date');
var img2 = ee.Image.random(20).addBands(ee.Image.constant(20)).float().rename('data', 'date');

// Make an image collection from the images.
var col = ee.ImageCollection([img1, img2]);

// Reduce the collection by the max of the first band and retain corresponding bands.
var maxImg = col.reduce(ee.Reducer.max(col.first().bandNames().size()))
  .rename(['maxData', 'maxDate']);

// Show both datasets on the Map so that inspector can be used to verify.
Map.addLayer(col, null, 'col');
Map.addLayer(maxImg, null, 'max');

Code Editor script: https://code.earthengine.google.com/b62c98246369e784ecd93852a7a2476e

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[GIS] Adding band value as a property in Google Earth Engine

It is not completely clear what you want hear? It helps if you provide an working example, for example in your script what is the variable mean doing? And what is your reference collection suggesting? Would you like a per pixel mean value and subtract or you want a mean for the entire reference period and all pixels?

I would say the logic you are describing should work, but some details would help? Perhaps this gives an idea of how to implement your logic (be aware, due to reduceRegions on large collections this is probably not the most efficient way of approaching your problem):

// create collection
 var collection = ee.ImageCollection('NASA/OCEANDATA/MODIS-Aqua/L3SMI')
  .select('sst')
  .filterBounds(EEZ)
  .map(function(image){return image.clip(EEZ)});

print(collection.limit(10), 'collection')
// get mean value over ten years
var reference = collection.filterDate('2002-01-01', '2012-12-31')
    .sort('system:time_start', false);

var mean = ee.Image(reference.select('sst').reduce(ee.Reducer.mean()).select('sst_mean'));
print(mean, 'mean')
Map.addLayer(mean)



//calculate anomaly for 2018
 var series = collection.filterDate('2018-01-01', '2018-12-31').map(function(image) {

      // difference
      var dif = image.subtract(mean)
      // amount of pixels > 0
      var number = ee.Number(dif.gt(0).reduceRegion({
          reducer: ee.Reducer.count(),
          geometry: EEZ,    
        }).values().get(0));


      return image.subtract(mean) // what is mean?
        .set('system:time_start', image.get('system:time_start'))
        .set('dif', number)
 });

print(series, 'series')

Google Earth Engine – Understanding Image Expression in Google Earth Engine

Assuming your affirmation that the remote sensing reflectance has to divide by pi, it is preferable to have three functions for mapping original and followings ImageCollections. First of them, it prepares selected bands for correct use (dividing by pi and it is also necessary a scale factor). Second function calculates band max between B1 and B2 and includes it in a new collections as 'B12_max' and finally, your desired function. They were incorporated in following code and one value, for pixel in point (-15.857348155192721, 28.47817439021581), arbitrarily selected in the ocean, was tested with respective formulas in LibreOffice. They matched perfectly.

var pt = ee.Geometry.Point([-15.857348155192721, 28.47817439021581]);

function prepareImages(image) {
  var time = image.get('system:time_start');
  return image.divide(Math.PI*10000)
    .set('system:time_start', time);
}

var dataset = ee.ImageCollection('COPERNICUS/S2_SR')
                  .filterDate('2020-01-01', '2020-01-03')
                  .filterBounds(pt)
                  .select('B1', 'B2', 'B3', 'B4')
                  .map(prepareImages);

var collBandMax = dataset.map(function (image) {
  var img_B1 = image
    .select('B1');

  var img_B2 = image
    .select('B2');

  var img_max_B1_B2 = img_B1.max(img_B2)
    .rename('B12_max');
    
  image = image.addBands([img_max_B1_B2]);

  var time = image.get('system:time_start');

  return image.set('system:time_start', time);

});

print("Collection with Band Max", collBandMax);

var chl_oc2 = collBandMax.map(function(image){

  var x = image.expression(
    'log10 ( Bmax / B3 )', {
      'Bmax': image.select('B12_max'),
      'B3': image.select('B3'),
  }).rename('x');
  
  var chl_conc = image.expression('10**(0.2389-1.9369*x+1.7627*x**2-3.077*x**3-0.1054*x**4)',
                             {'x':x} ).rename('chl_conc');

  var time = image.get('system:time_start');

  return chl_conc.set('system:time_start', time); });

print(chl_oc2);

var visualization = {
  min: 0.0020371832715762603,
  max: 0.018589297353133374,
  bands: ['B4', 'B3', 'B2'],
};

Map.setCenter(-15.6871, 28.647, 20);

Map.addLayer(dataset.mean(), visualization, 'RGB');
Map.addLayer(chl_oc2, {}, 'chl_oc2');

//Image (3 bands)
//B1: 0.009963099437553
//B2: 0.016074649252282
//B3: 0.011681972822945

After running above code, I got result of following image for corroborating pixel value in that point.

In following image it can be observed that this value matched with obtained in LibreOffice spreadsheet.

Best Answer

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Google Earth Engine – Understanding Image Expression in Google Earth Engine

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