google-earth-engine – How to Highlight Specific Pixels in an Image Using Masking

digital image processinggoogle-earth-engine

The two images below are the same.

In the images, the value of each pixel corresponds to a date in milliseconds.

In the top image, the pixels with the higher values – more recent date – are highlighted, while those with lower values are less highlighted.

The bottom image represents the raw mask of the image.

I imagine it is something to do with the masking of the image, but I am still figuring out what processing or operation was done to get this result.

Any ideas?

Code: https://code.earthengine.google.com/27a90e3abd360f7334ea41d0a4a9a9f6

Best Answer

Since you said that you tried clamp(), I'm assuming that you want the values reclassified.

var alerts = ee.ImageCollection('projects/radar-wur/raddalert/v1');
var geography = 'sa';

var latestAlert = ee.Image(
  alerts
    .filter(ee.Filter.eq('layer', 'alerts'))
    .filter(ee.Filter.eq('geography', geography))
    .sort('system:time_end', false)
    .first());

var confirmedAlertMask = latestAlert.select('Alert').eq(3);

var timeStart = ee.Date(latestAlert.get('system:time_start'));
var timeEnd = ee.Date(latestAlert.get('system:time_end'));
var differenceInDays = timeEnd.difference(timeStart, 'day');

// YYDOY (Year-Year-Day-of-Year).
var from = ee.List.sequence(0, differenceInDays).map(function(d) {
  return ee.Number.parse(
    timeStart.advance(d, 'day').format('yyDDD'))
    .subtract(1);
});

// Milliseconds.
var to = ee.List.sequence(0, differenceInDays)
  .map(function(d) {
    return timeStart.advance(d, 'day').millis();
  });

var alertInMillis = latestAlert
  .select('Date')
  // .updateMask(confirmedAlertMask)
  .remap(from, to)
  .rename('alertDate');

// Classifying, or reclassing the values.
var classValues = [0, 1, 2, 3];
var remapValues = ee.List.sequence({start:0, end:1, count:4});
var remapVal = ee.List.sequence({start: 0, end:1, count:3});
var label = 'lc';
var latestRmap = latestAlert.remap(classValues, remapValues).rename(label).toByte();

print(latestRmap, 'remap')

// Iago's original maps, alert in milliseconds
Map.addLayer(alertInMillis.updateMask(confirmedAlertMask.mask()), {}, 'Millis mask Raw');
Map.addLayer(alertInMillis.mask(), {}, 'Millis mask Smoothed');

// Iago's maps without ".mask()"
Map.addLayer(alertInMillis.updateMask(confirmedAlertMask), {}, 'Millis Raw');
Map.addLayer(alertInMillis, {}, 'Millis Smoothed');

// Alert in days, without a mask
Map.addLayer(latestAlert.updateMask(confirmedAlertMask), {}, 'No Mask Raw');
Map.addLayer(latestAlert, {}, 'No Mask Smoothed');

// Alert in days, with a mask
Map.addLayer(latestAlert.updateMask(confirmedAlertMask).mask(), {}, 'Mask Raw');
Map.addLayer(latestAlert.mask(), {}, 'Mask Smoothed');

// Original data, same as Alert in days without mask
Map.addLayer(latestAlert, {}, 'latest')

// Original data reclassed
Map.addLayer(latestRmap, {}, 'lc')
Map.setCenter(-65.81, -9.198, 8);

https://code.earthengine.google.com/5245cc7b6205254f99f3e888b785659c

Related Solutions

[GIS] Image Export fails in Google Earth Engine because “export region contains no valid (un-masked) pixels

1st: The exact code you posted (https://code.earthengine.google.com/ce1a151ce06497b20cf1793715cb0120) did export the image correctly. So the error cannot be reproduced. May be, you changed the 'ROI' to a place where the filtered collection had no images.

2nd: There are no images because you filtered by cloud percentage, and so, it found images that suited the condition only in the left part of the ROI. If you comment like:

//.filter(ee.Filter.lte('CLOUDY_PIXEL_PERCENTAGE', 5))

you'll see that there are more images and you get the whole ROI (of course you get a part of the image plenty of clouds).

3rd: if automated exporting is your goal, maybe you should migrate to Python, but if you don't mind clicking the run button over and over, this would be one approach to download images only if the filtered collection has images (don't blame me on the getInfo =):

//Define date range
var startDate = ee.Date.fromYMD(2017,7,1);
var endDate = ee.Date.fromYMD(2017,7,31);

//Load Sentinel-2 image collections
var coll_s2 = ee.ImageCollection("COPERNICUS/S2");

//Filter Sentinel-2 collection for ROI and cloud-coverage.
//Keep only images with less than 5% clouds
var coll_s2_filtered = coll_s2.filterDate(startDate, endDate)
                              .filter(ee.Filter.lte('CLOUDY_PIXEL_PERCENTAGE', 5))
                              .sort('system:time_start',false);

// Define the FeatureCollection!
var fc = ee.FeatureCollection(LIST_OF_POINT_FEATURES)

// Iterate over the FeatureCollection to create a List
// with images where there is data avialable
var listn = ee.List(fc.iterate(function(elem, ini){
  var rectangle = ee.Feature(elem.buffer(20000).bounds());
  var roi = rectangle.geometry();
  var col = coll_s2_filtered.filterBounds(roi);
  return ee.Algorithms.If(col.size(), 
            ee.List(ini).add(coll_s2_filtered.select(['B4','B3','B2']).mosaic().clip(roi)), 
            ee.List(ini))
}, ee.List([])))

listn = ee.List(listn)

print(listn)

// As Export is a Client-side function, you have to iterate the list
// in a client-side way

for (var n = 0; n<listn.size().getInfo(); n++) {
  var i = ee.Image(listn.get(n))
  Export.image.toDrive({
    image: i,
    description: 'image_'+n.toString(),
    scale: 10,
    folder: "tests",
    region: i.geometry()
    });
}

But if you want to change the filter regarding on whether it finds or not images, that would be different.

[GIS] Counting number of unmasked pixels per image in collection using Google Earth Engine

To get to your end goal of filtering your clipped image collection by 10% or less cloud cover, I would write a function that:

counts the number of unmasked pixels in the image
counts the number of pixels in the unmasked image
calculates the percentage of masked pixels and sets this as a metadata property

I would then map this onto your image collection and filter it by the added metadata property.

Note that I'm assuming that your images are only masked by a cloud mask.


function get_cloud_cover_roi(image){ 

  var Peyto_pixelscount = image.select('ALBEDO').reduceRegion({
    reducer: ee.Reducer.count(),
    geometry: image.geometry(),
    scale: 30,
    maxPixels: 1e9
  }).get('ALBEDO')

  var npix = image.select('ALBEDO').unmask().reduceRegion({
    reducer: ee.Reducer.count(),
    geometry: image.geometry(),
    scale: 30,
    maxPixels: 1e9
  }).get('ALBEDO')

  var cloud_cover_roi = ee.Number(1)
      .subtract(ee.Number(Peyto_pixelscount).divide(npix))
      .multiply(100)

  return image.set('cloud_cover_roi', cloud_cover_roi)

}

var Peytoclip_filtered = Peytoclip
    .map(get_cloud_cover_roi)
    .filterMetadata('cloud_cover_roi', 'less_than', 10)

Best Answer

Related Solutions

[GIS] Image Export fails in Google Earth Engine because “export region contains no valid (un-masked) pixels

[GIS] Counting number of unmasked pixels per image in collection using Google Earth Engine

Related Question