Extract, plot and export as a table a vegetation index time series from multipoint feature collection in Earth Engine

Question

Reference is to a tread I posed years ago and was solved Extract pixel values from several bands of an image and export in a single table in Google Earth Engine The challenge now is to create S2 NDVI time series for each point location of a feature collection.

var listOfFeatures = [
  ee.Feature(ee.Geometry.Point(-62.54, -27.32), {key: 'val1'}),
  ee.Feature(ee.Geometry.Point(-69.18, -10.64), {key: 'val2'}),
  ee.Feature(ee.Geometry.Point(-45.98, -18.09), {key: 'val3'})
];
var listOfFeaturesFc = ee.FeatureCollection(listOfFeatures);
print('FeatureCollection from a list of features', listOfFeaturesFc);

var startDate = '2019-03-29'; // initial date of the image collection
var endDate = '2019-05-05'; //final date of the image collection

//Mask clouds
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));

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


// Function to calculate and add an NDVI band
var addNDVI = function(image) {
  var ndvi = image.normalizedDifference(['B8', 'B4']).rename('NDVI');
  return image.addBands(ndvi);
};

// Download the Sentinel-2 imagery collection
var sentinel2 = ee.ImageCollection('COPERNICUS/S2')
    .filterDate(startDate, endDate)
    .filterBounds(listOfFeatures)
    .map(maskS2clouds)
    .map(addNDVI);

var NDVI = ee.ImageCollection(sentinel2)
              .select(['NDVI']);

var chart =
    ui.Chart.image
        .series({
          imageCollection: NDVI,
          region: listOfFeatures,
          reducer: ee.Reducer.mean(),
          scale: 10,
          
        })
        .setSeriesNames(['NDVI'])
        .setOptions({
          title: 'NDVI time series',
          hAxis: {title: 'Date', titleTextStyle: {italic: false, bold: true}},
          vAxis: {
            title: 'NDVI',
            titleTextStyle: {italic: false, bold: true}
          },
          lineWidth: 5,
          colors: ['e37d05', '1d6b99'],
          curveType: 'function'
        });
print(chart);

At this point I get the following error: No features contain non-null values of "system:time_start"

Moreover I would also like to export a table (.csv) that associate at each point name the NDVI values of the time range, and the dates as column names. I guess this can be exported directly from the chart window, but since I could not get there I do not whether something else is missing.

Answer 1

I found a partial solution to this, please see below the working code:

var listOfFeatures = [
  ee.Feature(ee.Geometry.Point(-62.54, -27.32), {key: 'val1'}),
  ee.Feature(ee.Geometry.Point(-69.18, -10.64), {key: 'val2'}),
  ee.Feature(ee.Geometry.Point(-45.98, -18.09), {key: 'val3'})
];
var listOfFeaturesFc = ee.FeatureCollection(listOfFeatures);
print('FeatureCollection from a list of features', listOfFeaturesFc);

var startdate = '2019-01-01';
var enddate = '2019-04-30';



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));

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

var addNDVI = function(image) {
  var ndvi = image.normalizedDifference(['B8','B4']).rename('NDVI');
  return image.addBands(ndvi);
};



var S2_NDVI = ee.ImageCollection('COPERNICUS/S2_SR_HARMONIZED')
                  .filterDate(startdate, enddate)
                  .filterBounds(listOfFeatures)
                  // Pre-filter to get less cloudy granules.
                  .filter(ee.Filter.lt('CLOUDY_PIXEL_PERCENTAGE',20))
                  //.map(maskS2clouds)
                  .map(addNDVI)
                  .select('NDVI');

print (S2_NDVI);

var chart = ui.Chart.image.seriesByRegion({
  imageCollection: S2_NDVI,
  regions:listOfFeatures,
  reducer:ee.Reducer.mean(),
  scale:10,
  xProperty:'system:time_start',
  
})

As you can see I had to slash out the cloud masking at pixel level, since it was kind of reducing the collection to a single image, returning me the error: No features contain non-null values of "system:time_start" I partially overcome the problem by applying a filter for cloud coverage at scene level, but that is not optimal, since It does not exclude cloudy pixels from the time series. Do someone have suggestion for this?