Make a Loop for Monthly NDVI in Google Earth Engine?

Question

I've computed maximum NDVI for each month. but I don't know how can I write this code through a loop in Google Earth Engine?

code link: https://code.earthengine.google.com/99fd025cdb0688dce74ea5fa0966a2c2

Map.centerObject(table);
Map.addLayer(table);

// ndvi jan

var jan = ee.ImageCollection("COPERNICUS/S3/OLCI")
.filterBounds(table)
.filterDate('2018-01-01','2018-02-01')
.map(function(img){
  return img.normalizedDifference(['Oa17_radiance','Oa08_radiance']);
})
.max()
.clip(table)
.rename('jan');

// ndvi feb

var feb = ee.ImageCollection("COPERNICUS/S3/OLCI")
.filterBounds(table)
.filterDate('2018-02-01','2018-03-01')
.map(function(img){
  return img.normalizedDifference(['Oa17_radiance','Oa08_radiance']);
})
.max()
.clip(table)
.rename('feb');

// ndvi mar

var mar = ee.ImageCollection("COPERNICUS/S3/OLCI")
.filterBounds(table)
.filterDate('2018-03-01','2018-04-01')
.map(function(img){
  return img.normalizedDifference(['Oa17_radiance','Oa08_radiance']);
})
.max()
.clip(table)
.rename('mar');

// ndvi apr

var apr = ee.ImageCollection("COPERNICUS/S3/OLCI")
.filterBounds(table)
.filterDate('2018-04-01','2018-05-01')
.map(function(img){
  return img.normalizedDifference(['Oa17_radiance','Oa08_radiance']);
})
.max()
.clip(table)
.rename('apr');

// ndvi may

var may = ee.ImageCollection("COPERNICUS/S3/OLCI")
.filterBounds(table)
.filterDate('2018-05-01','2018-06-01')
.map(function(img){
  return img.normalizedDifference(['Oa17_radiance','Oa08_radiance']);
})
.max()
.clip(table)
.rename('may');

// ndvi jun

var jun = ee.ImageCollection("COPERNICUS/S3/OLCI")
.filterBounds(table)
.filterDate('2018-06-01','2018-07-01')
.map(function(img){
  return img.normalizedDifference(['Oa17_radiance','Oa08_radiance']);
})
.max()
.clip(table)
.rename('jun');

// ndvi jul

var jul = ee.ImageCollection("COPERNICUS/S3/OLCI")
.filterBounds(table)
.filterDate('2018-07-01','2018-08-01')
.map(function(img){
  return img.normalizedDifference(['Oa17_radiance','Oa08_radiance']);
})
.max()
.clip(table)
.rename('jul');

// ndvi aug

var aug = ee.ImageCollection("COPERNICUS/S3/OLCI")
.filterBounds(table)
.filterDate('2018-08-01','2018-09-01')
.map(function(img){
  return img.normalizedDifference(['Oa17_radiance','Oa08_radiance']);
})
.max()
.clip(table)
.rename('aug');

// ndvi sep

var sep = ee.ImageCollection("COPERNICUS/S3/OLCI")
.filterBounds(table)
.filterDate('2018-09-01','2018-10-01')
.map(function(img){
  return img.normalizedDifference(['Oa17_radiance','Oa08_radiance']);
})
.max()
.clip(table)
.rename('sep');

// ndvi oct

var oct = ee.ImageCollection("COPERNICUS/S3/OLCI")
.filterBounds(table)
.filterDate('2018-10-01','2018-11-01')
.map(function(img){
  return img.normalizedDifference(['Oa17_radiance','Oa08_radiance']);
})
.max()
.clip(table)
.rename('oct');

// ndvi nov

var nov = ee.ImageCollection("COPERNICUS/S3/OLCI")
.filterBounds(table)
.filterDate('2018-11-01','2018-12-01')
.map(function(img){
  return img.normalizedDifference(['Oa17_radiance','Oa08_radiance']);
})
.max()
.clip(table)
.rename('nov');

// ndvi dec

var dec = ee.ImageCollection("COPERNICUS/S3/OLCI")
.filterBounds(table)
.filterDate('2018-12-01','2019-01-01')
.map(function(img){
  return img.normalizedDifference(['Oa17_radiance','Oa08_radiance']);
})
.max()
.clip(table)
.rename('dec');

var ndvistack = jan.addBands(feb).addBands(mar).addBands(apr).addBands(may)
.addBands(jun).addBands(jul).addBands(aug).addBands(sep).addBands(oct)
.addBands(nov).addBands(dec);

Answer 1

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.

Answer 2

I have an idea (not sure if it is right).

First, you can add a property month for each image in your ImageColleciton.

Then, calculate NDVI by ImageCollection.map(NDVIfunction),

Finally, obtain the desired NDVI maximum per month by ee.ImageCollection.aggregate_max.

Hope this will help you.