Exporting NDVI for multiPoint Geometry in Python API of Google Earth Engine

google-earth-enginendvipythonsentinel-2

I have a list of mine coordinates and I want to export the mean NDVI of the region 5 km around the mine area. I was able to plot the mines, the region of interest and calculation of NDVI on map, but when I tried exporting those regions, I only got a single value instead of mean NDVI for all the mines.

This is how my code currently looks like. Because I don't get any error in the code, I am unable to figure out where the logical error in the code lies.

mine_coordinates = [[77.3384, 28.6902], [74.5921, 28.7081], [72.0131, 24.6037], [86.5405, 25.0426], [82.7497, 22.3285]] #sample coordinates only
mine_area = ee.Geometry.MultiPoint(mine_coordinates).buffer(5000) #circular region of 5 kms radius around the point

def getNDVI(image):
    return image.normalizedDifference(['B8', 'B4'])

image_left = ee.ImageCollection('COPERNICUS/S2_SR').filterDate('2020-11-01', '2020-11-30').median().clip(mine_area)

ndvi_left = getNDVI(image_left) #input and output are images
ndviParams = {'min': 0,
               'max': 0.5,
               'palette': ['#d73027', '#f46d43', '#fdae61', '#fee08b', '#ffffbf', '#d9ef8b', '#a6d96a', '#66bd63', '#1a9850']}

mine_map = gm.Map(center = [24.922695, 77.531718], zoom = 6, lite_mode = True)
mine_map.addLayer(mine_area, {'color': 'red'})
mine_map.addLayer(ndvi_left, ndviParams, 'NDVI')
mine_map.addLayerControl()
mine_map

mineMeansFeatures = ndvi_left.reduceRegions(
    collection = mine_area,
    reducer = ee.Reducer.mean(),
    scale = 30,
)

ee.batch.Export.table.toDrive(collection = mineMeansFeatures, description = 'mineNDVI', fileFormat = 'CSV').start()

I get the following result after running this code.

But, in the output CSV I get a table with a single row like this
system:index mean .geo
0 0.2423464309 {"type":"MultiPolygon","coordinates":[multiple coordiantes here]}

What I am looking at is something like this

Location	Mean_NDVI
A	0.25
B	0.56
C	0.42

Best Answer

A Multipoint is considered a single geometry and you're reducing all the pixel in each geometry to a single value. Instead, you want multiple features, each with a single point in it.

locations = ee.List([[77.3384, 28.6902], [74.5921, 28.7081], [72.0131, 24.6037], [86.5405, 25.0426], [82.7497, 22.3285]])
    .map(lambda coords : ee.Feature(ee.Geometry.Point(coords).buffer(5000)))
mine_area = ee.FeatureCollection(locations)

Related Solutions

[GIS] Make a Loop for Monthly NDVI in Google Earth Engine

I think this should get you going. Inspiration in addition to copy/paste from a few sources including here and here. Your table isn't public so I used a random county from Maine instead.

var maineCounties = ee.FeatureCollection('TIGER/2016/Counties')
  .filter(ee.Filter.eq('NAME', 'Waldo'));
print(maineCounties);
var table = maineCounties;
Map.addLayer(table);

// Function to get image NDVI
var getNDVI = function(img){
  var NDVI = img
    .normalizedDifference(['Oa17_radiance','Oa08_radiance'])
    .rename("NDVI");
  return NDVI;
};

// Make start and end layers
var start = ee.Date.fromYMD(2018,01,01);
var months = ee.List.sequence(0, 11);
var startDates = months.map(function(d) {
  return start.advance(d, 'month');
});
print("Start dates",startDates);

// Collect imagery by month
var monthmap = function(m){
  var start = ee.Date(m);
  var end = ee.Date(m).advance(1,'month');
  var date_range = ee.DateRange(start,end);
  var S3Month = ee.ImageCollection('COPERNICUS/S3/OLCI')
    .filterDate(date_range)
    .filterBounds(table)
    .map(getNDVI)
    .map(function(img){return img.clip(table)});
  return(S3Month.max());
};
print("monthmap",monthmap);

var list_of_images = startDates.map(monthmap);
print('list_of_images', list_of_images);
var mt = ee.ImageCollection(list_of_images);
print("Monthly NDVI", mt);

Map.addLayer(mt,{},"NDVI");

mt should be a 12-layer object with each layer being NDVI for that month.

[GIS] Extracting NDVI values from Image using Google Earth Engine Python API

You currently have an image which has an NDVI value for each pixel in the original image. In order to get a single number, you need to reduce the image — to take the mean, median, maximum, minimum, or other such operation on pixels in the image, within a region of interest. Here is the documentation on reduceRegion, which is the way to do this.

Since you have an image collection and want a table, you also need to map over the image collection. Whenever you want a number or other value for each image in a collection, the way you do that is by adding a property to each image, using set(), or by producing new features that have only the data you want.

This example I wrote is in JavaScript since I wrote it in the Earth Engine Code Editor, but the differences with Python are fairly small so I hope you can follow along.

var meanNDVICollection = imgs.map(function (img) {
  // Your code.
  var nir = img.select('B5');
  var red = img.select('B4');
  var ndviImage = nir.subtract(red).divide(nir.add(red)).rename('NDVI');

  // Compute the mean of NDVI over the 'region'
  var ndviValue = ndviImage.reduceRegion({
    geometry: region,
    reducer: ee.Reducer.mean(),
  }).get('NDVI');  // result of reduceRegion is always a dictionary, so get the element we want

  // Add the value as a property to each image in the collection.
  // return img.set('NDVI', ndviValue);

  // Or, create a new feature with only the properties we want.
  return ee.Feature(null, {
    // Adding property we computed.
    'NDVI': ndviValue
  }).copyProperties(img, [
    // Picking properties from the original image.
    'system:time_start',
    'SUN_ELEVATION'
  ])
});

// Export, or you can use any other method for getting a table out of Earth Engine.
Export.table.toDrive({
  collection: meanNDVICollection
});

https://code.earthengine.google.com/580f2f06c9978caf43eac42b5dd0ff44

(Disclaimer: I do not have training in the scientific and statistical aspects of remote sensing. The choices of mean and scale: 20 in this script are for demonstration of Earth Engine only and should not be assumed to produce scientifically valid results.)

Best Answer

Related Solutions

[GIS] Make a Loop for Monthly NDVI in Google Earth Engine

[GIS] Extracting NDVI values from Image using Google Earth Engine Python API

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