[GIS] Image collection to Single Image in Google Earth Engine

google-earth-engineimagemodis

I'm stuck with an issue in google earth engine.

I'm working with MODIS Burned Area Monthly Global 500m, for a certain polygon area:

var MOD = ee.ImageCollection('MODIS/006/MCD64A1');
var MOD1 = MOD.filterDate('2005-06-21', '2005-09-31');
var MODlim1 = MOD.map(function(img) {return img.clip(lim)})

The problem is the image collection has three images (one for each month), and I need to convert this into a single image, which contains the burned area for three images in only one.
Anyone knows what function can be helpful in this situation?
I need to repeat this for every year (until 2018), so with a single image, it would be easier to analyze the data.

Best Answer

// UPDATE: The easiest way is now toBands().
var merged = MOD1.toBands();

// For completeness, this is the iterate() way:
var mergeBands = function(image, previous) {
  return ee.Image(previous).addBands(image);
};

var merged = MOD1.iterate(mergeBands, ee.Image([]));

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[GIS] Obtain monthly and yearly average values of EVI using MODIS data on Google Earth Engine

Ok, here's some code to solve your problem. Question 2 is addressed first with a 12-layer raster image being exported to your drive, then the second export is an example for a single year (example is with 2001).

Edit: wrong link. https://code.earthengine.google.com/5b44745d195c944c4c4de06ed68fe000

[GIS] Calculate NDWI from image collection and reclassify to land/water in Google Earth Engine

So, you are asking two question at once. You would like to use the Otsu threshold to calculate a water mask on a per-image basis. Besides, you would like a watermask in a similar way for the median image. In your code, you have mixed them up. For that reason, your code is not working.

You tried to filter by cloud cover, however, as you do it now you will remain the full collection and just rearrange the order of the images. To filter by cloudcover, use:

var sorted = temporalFiltered.filter(ee.Filter.lt('CLOUD_COVER', 10));

First, make a function to calculate NDWI for a random image:

// Create a function to calculate NDWI per image
function calcNDWI(image){
  return image.normalizedDifference(['B3', 'B5']).rename('NDWI');
}

Then, define the Otsu thresholding function of Nicolas Clinton inside your code (which I have done, see the link). To get the Otsu threshold and water mask for the full image collection, map over you imageCollection, which you named 'sorted':

var mappedCollection = sorted.map(function(image){
  var NDWI = calcNDWI(image);
  var histogram = ee.Dictionary(NDWI.reduceRegion({
    reducer: ee.Reducer.histogram(100),
    geometry: AOI_subset, 
    scale: 30,
    bestEffort: true
  }).get('NDWI'));
  var threshold = otsu(histogram);
  var waterMask = NDWI.lt(ee.Number(threshold)).rename('waterMask');
  return image.addBands([NDWI, waterMask]).set('OtsuThresh', threshold);
});

For the median, you can do that in a similar way. But, the median is a SINGLE image, so you cannot map over it (which gave the error):

var NDWImedian = calcNDWI(median);
var histogram = ee.Dictionary(NDWImedian.reduceRegion({
  reducer: ee.Reducer.histogram(100),
  geometry: AOI_subset, 
  scale: 30,
  bestEffort: true
}).get('NDWI'));
var threshold = otsu(histogram);
var waterMask = NDWImedian.lt(ee.Number(threshold)).rename('waterMask');
var median = median.addBands([NDWImedian, waterMask]).set('OtsuThresh', threshold);

Then visualize some stuff in the console and map. Note that inside a mapped function, occuring on the server-side, you cannot print something (e.g. the histogram), so I did that only for the median image:

// Print
print('size full collection', sorted.size());
print('The full collection', mappedCollection);
print('Histogram of the median', ui.Chart.image.histogram(median.select('NDWI'), AOI_subset, 30));
print('Otsu thresholds', mappedCollection.aggregate_array('OtsuThresh'));

// Make a variable of visualization parameters.
var visParams = {bands: ['B4', 'B3', 'B2'], min: 0, max: 0.35};
var ndwiViz = {min: 0.01, max: 0.75, palette: ['2ca25f', '0000FF'], bands: 'NDWI'};

Map.addLayer(median.updateMask(median.select('waterMask')), visParams, 'True color median water masked');
Map.addLayer(mappedCollection.first().updateMask(mappedCollection.first().select('waterMask')), visParams, 'True color first image water masked');

Link script

Best Answer

Related Solutions

[GIS] Obtain monthly and yearly average values of EVI using MODIS data on Google Earth Engine

[GIS] Calculate NDWI from image collection and reclassify to land/water in Google Earth Engine

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