My goal is to be able to use the JRC Yearly Water classification History imageCollection to calculate the area of seasonal and permanent water for each year available in a specified extent. I am able to do this for a specific image but I am hoping to find a way to automate the process for all the images in the collection. I know that I can map over an imageCollection to analyze it, but I can't print a chart within that function or find a way for the function to return the values of the reduceRegion. The questions I have are:

1) Is there a way to map over the imageCollection and get the values of the area for each class for each image? Or should I be doing something else?


2) Is there a way to get a graph with the area of each class for each of the images? Or do a time series graph by class?

Here is my code for a single image. From here I would just export the csv and then combine them in a different program, but can I do it all in Google Earth Engine?

//import needed images and collections 
var img1984 = ee.Image("JRC/GSW1_1/YearlyHistory/1984"); 
var gsw = ee.Image("JRC/GSW1_1/GlobalSurfaceWater"); 
var yearSeasonality = ee.ImageCollection("JRC/GSW1_1/YearlyHistory");

var roi = ee.Geometry.Polygon([[-113.31109206384143,38.70660386074948], [-113.09136550134143,38.69588646672195], [-112.93481032556018,39.112673412644575], [-113.20672194665393,39.12332806661866], [-113.31109206384143,38.70660386074948]]);


//These are the parameters if you want to map the extent or seasonality layers 
var extentParams = {min: 0, max: 1}; 
var seasonalityParams = {min:1, max: 12, palette: ["#99D9EA", "#0000AA" ]};

//use the max extent of the water body to mask the seasonality layer 
var mask = gsw.select('max_extent') .eq(1) .clip(roi); 
var y1984 = img1984.updateMask(mask);

//calculate the area of the pixels 
var y1984Area= ee.Image.pixelArea().addBands(y1984);

var classNames = ee.List(["No Data", "Not Water", "Seasonal Water", "Permanent Water"]);

//create a chart that adds up the areas of each of the classes

var TimeChart = ui.Chart.image.byClass({ image: y1984Area, classBand: 1, region: roi, reducer: ee.Reducer.sum(), scale:30, classLabels: classNames, }); print(TimeChart);

//another way to get the total areas for each class 

var reduced1984 = y1984Area.reduceRegion({ reducer: ee.Reducer.sum().group({ groupField: 1, groupName: 'waterClass', }), geometry: roi, scale:30, bestEffort: true, });

print("reduced values",reduced1984);

Here is the code for me starting to automate the process (I'm not including the many things I tried that didn't work):

var seasonality = yearSeasonality.map (function(image){ var mask = gsw.select('max_extent') .eq(1) .clip(roi);

return image.updateMask(mask); });

var seasonalityArea = seasonality.map (function(image){ var seasons = ee.Image.pixelArea(); return ee.Image.pixelArea().addBands(image).copyProperties(image,['system:time_start','system:time_end']); }); print (seasonalityArea,"seasonality with area added,not summed");
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    – Vince
    Commented May 14, 2020 at 0:43

1 Answer 1


This script doesn't perhaps take all your requirements into account, but it should answer your two questions:

var roi = ee.Geometry.Polygon([[-113.31109206384143,38.70660386074948], [-113.09136550134143,38.69588646672195], [-112.93481032556018,39.112673412644575], [-113.20672194665393,39.12332806661866], [-113.31109206384143,38.70660386074948]])
var areas = ee.ImageCollection('JRC/GSW1_1/YearlyHistory')

var chart = ui.Chart.feature.byFeature(areas, 'year')

function areaByClass(image) {  
  var classNames = ee.List(['No Data', 'Not Water', 'Seasonal Water', 'Permanent Water']);
  var groups = ee.Image.pixelArea().addBands(image)
      reducer: ee.Reducer.sum()
        .group({ groupField: 1, groupName: 'waterClass', }), 
      geometry: roi, 
      scale: 30
  var areaByClass = ee.Dictionary(
    ee.List(groups).map(function (group) {
      group = ee.Dictionary(group)
      return [
        group.getNumber('sum').divide(1e6) // square km 
  return ee.Feature(null, areaByClass.set('year', image.get('year')))


  • Thank you. It was exactly what I needed and worked great!
    – rebeccalm
    Commented May 14, 2020 at 23:43

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