Charting values for multiple points on Google Earth Engine

Question

I tried to generate a chart for values of multiple points for AOD taking help of the very helpful video: https://www.youtube.com/watch?v=5bOO0PJJMf0. However, I'm unable to get GEE to recognize values of more than one point in a collection of 7.

Here's the code:

var maod = ee.ImageCollection("MODIS/006/MCD19A2_GRANULES"),
    kanpur = 
    /* color: #70d68e */
    /* shown: false */
    ee.FeatureCollection(
        [ee.Feature(
            ee.Geometry.Polygon(
                [[[78.5614794892115, 27.630292998342572],
                  [78.5614794892115, 25.170437036589544],
                  [81.840898434524, 25.170437036589544],
                  [81.840898434524, 27.630292998342572]]]),
            {
              "1": "Bound",
              "system:index": "0"
            })]),
    MultiPointAOD = /* color: #f70000 */ee.FeatureCollection(
        [ee.Feature(
            ee.Geometry.Point([80.4291552704615, 26.511722460604513]),
            {
              "system:index": "0"
            }),
        ee.Feature(
            ee.Geometry.Point([81.51954833686774, 27.087836554978104]),
            {
              "system:index": "1"
            }),
        ee.Feature(
            ee.Geometry.Point([81.21055785835212, 25.521349742082215]),
            {
              "system:index": "2"
            }),
        ee.Feature(
            ee.Geometry.Point([79.67762384859742, 25.384298993749066]),
            {
              "system:index": "3"
            }),
        ee.Feature(
            ee.Geometry.Point([79.03663818061774, 26.351856976593158]),
            {
              "system:index": "4"
            }),
        ee.Feature(
            ee.Geometry.Point([79.34425536811774, 27.434530441120618]),
            {
              "system:index": "5"
            }),
        ee.Feature(
            ee.Geometry.Point([80.71754638374274, 27.087836405728336]),
            {
              "system:index": "6"
            })]),
    geometry = 
    /* color: #d63000 */
    /* shown: false */
    /* displayProperties: [
      {
        "type": "rectangle"
      },
      {
        "type": "rectangle"
      }
    ] */
    ee.FeatureCollection(
        [ee.Feature(
            ee.Geometry.Polygon(
                [[[78.577958981399, 27.636673418136443],
                  [78.577958981399, 25.181926141677547],
                  [81.8463915985865, 25.181926141677547],
                  [81.8463915985865, 27.636673418136443]]], null, false),
            {
              "system:index": "0"
            }),
        ee.Feature(
            ee.Geometry.Polygon(
                [[[81.84364501655524, 25.216718878626583],
                  [81.84364501655524, 25.14215084694132],
                  [81.84364501655524, 25.14215084694132],
                  [81.84364501655524, 25.216718878626583]]], null, false),
            {
              "system:index": "1"
            })]);

var aod = maod
              .filterDate('2019-01-01', '2019-12-31')
              .map(function(image){return image.clip(kanpur)})
              .select('Optical_Depth_055');

Map.centerObject(kanpur,8);

var aoc = {
  min: 380,
  max: 700,
  palette: ['black', 'blue', 'purple', 'cyan', 'green', 'yellow', 'red']
};
var aodavg = aod.reduce(ee.Reducer.mean());
Map.addLayer(aodavg, aoc, "AOD Monthly Average");

var chart = 
      ui.Chart.image
          .series({
            imageCollection: aod, 
            region: kanpur, 
            reducer: ee.Reducer.mean(), 
            scale: 500, 
            // xProperty: 'system_time_start'
          })
          .setSeriesNames(['Aerosol Optical Depth'])
          .setOptions({
            title: 'AOD MODIS Time Series', 
            hAxis: {title: 'Date', titleTextStyle: {italic: false, bold: true}}, 
            vAxis: {
              title: 'AOD Value', 
              titleTextStyle: {italic: false, bold: true}
            },
            lineWidth: 5, 
            colors: ['e37d05'],
            curveType: 'function'
          });
// print(chart);

var points = ee.FeatureCollection(MultiPointAOD);
var pointsamp = points.map(function(feature){
  return ee.Feature(feature.kanpur(), {'id': feature.id()});
});

var char2 = ui.Chart.image.seriesByRegion({
  imageCollection: aod, 
   regions: pointsamp, 
   reducer: ee.Reducer.mean(), 
}).setOptions({
      interpolateNulls: true, 
      lineWidth: 1, 
      pointSize: 3, 
      title: 'Overtime AOD at diff hotspots', 
      vAxis: {title: 'AOD Value'}, 
      hAxis: {title: 'Date', format: 'YYYY-MMMM', gridlines: {count: 12}},
      colors: ['blue', 'yellow', 'red']
});
print(char2);

Answer 1

There are three things that are responsible of the errors: 1) there is an error in the part defining pointsamp, 2) there is a limit in the number of objects that GEE can show in a plot or in the console (i.e., 5000 elements), and 3) finally, you need to specify a scale or crs parameter in ui.Chart.image.seriesByRegion. Errors number 1 and 3 can easily be fixed, however, to reduce the number of elements, I assumed you were interested in obtaining a mean value for each day of the year. Thus, this solution makes first a collection of images representing the daily average and then using that collection to make the chart (while reducing the number of elements being shown in the chart).

var points = ee.FeatureCollection(MultiPointAOD);
print('points', points);
var pointsamp = points.map(function(feature){
  // Removed the kanpur part
  return ee.Feature(feature).set('id', feature.id());
});
print('pointsamp', pointsamp);

// Too many images in aod, lets make one per day
var days = aod.aggregate_array('system:time_start')
              .map(function(date){
                return ee.Date(date).format('y-M-d');
              })
              // Get distinct dates
              .distinct();
              
print('days', days);

// Create new collection from daily images
var aod2 = ee.ImageCollection.fromImages(days.map(function(date){
  var start = ee.Date(date);
  var end = start.advance(1,'day');
  
  var resul = aod.filterDate(start, end)
                 .mean();
  
  return resul.set('system:time_start', start);               
}));
print('aod2', aod2);

// Now do the chart
var char2 = ui.Chart.image.seriesByRegion({
   imageCollection: aod2, 
   regions: pointsamp, 
   reducer: ee.Reducer.mean(), 
   // Need to define scale
   scale:500
}).setOptions({
      interpolateNulls: true, 
      lineWidth: 1, 
      pointSize: 3, 
      title: 'Overtime AOD at diff hotspots', 
      vAxis: {title: 'AOD Value'}, 
      hAxis: {title: 'Date', format: 'YYYY-MMMM', gridlines: {count: 12}},
      colors: ['blue', 'yellow', 'red']
});
print(char2);