Sentinel-1 modified Radar Vegetation Index
The Sentinel-1 modified Radar Vegetation Index (RVI) based on Google Earth Engine (GEE) script below originally developed by my friend Jose Manuel Delgado Blasco (Scholar, Linkedin) as part of our team (GOST) activities to support during Ukraine response last year, published as GOST Public Good’s Github repo https://github.com/worldbank/GOST_SAR/tree/master/Radar_Vegetation_Index
The original GEE script was meant to be used only for individual updates, as time progresses and the need for vegetation monitoring continually increases, I believe it's necessary to obtain this RVI time-series data, which can be matched with monthly rainfall time-series data for monitoring food crop phenology.
For this reason, I've added a function to mosaic every ten days and batch downloading if the list of data is quite extensive.
All credit goes to the awesome work of Jose Manuel! Hats off to him!
RVI in Crimean Peninsula
Above picture is Vegetation Indices based on Sentinel-1 (generated using the GEE script), below picture is Vegetation Indices for the same period based on Sentinel-2 (generated using Climate Engine https://climengine.page.link/sZnR)
NDVI in Crimean Peninsula
Full GEE code is here: https://code.earthengine.google.com/62f799954525c997629cefdd435c500e
/*
* Sentinel-1 modified RADAR VEGETATION INDEX (mRVI)
*
* Within this script SAR Sentinel-1 is being used to generate a vegetation index maps
* using the mRVI approach defined in Çolak et al.(2021) with doi
* 10.5194/isprs-archives-xliii-b3-2021-701-2021. We have selected this one as it has shown to
* provide more similar information to the MODIS NDVI data.
*
* We create mRVI nation-wide composites from both ascending and descending orbits together a
* it has shown to provide better results on successive steps. The final maps are masked using
* the ESA WorldCover map to generate only the mRVI index over crop areas, and finally rescaled
* by a factor of 10000 to convert it into UInt16 (lighter than float)
*
* Originally created by Jose Manuel Delgado Blasco, as part of GOST support to UKR activities
* - https://github.com/worldbank/GOST_SAR/tree/master/Radar_Vegetation_Index
* - https://code.earthengine.google.com/2b3eff8d77e245c0ba67c3dd127ec6e9
* mRVI will use by GOST to monitor the crop phenology: Start of Season, End of Season, etc
* the phenological analysis will use TIMESAT software for smoothing using Savitsky-Golay and
* extract the seasonality parameters
*
* Contact: Benny Istanto. Climate Geographer - GOST/DECAT/DECDG, The World Bank
* related to the use of mRVI for crop growing stage monitoring
*
* Changelog:
* 2022-07-05 last commit by JMDB at GOST_SAR repository
* 2023-06-14 Add function to get list images within dekad calendar, mosaic the result
* Batch downloading using JavaScript console (useful if you have hundred images)
*
* ------------------------------------------------------------------------------
*/
/*
SELECT YOUR OWN STUDY AREA
The user can :
1) select a full country by changing the countryname variable or;
2) use the polygon-tool in the top left corner of the map pane to draw the shape of your
study area. Single clicks add vertices, double-clicking completes the polygon.
**CAREFUL**: Under 'Geometry Imports' (top left in map panel) uncheck the
geometry box, so it does not block the view on the imagery later.
3) load a shapefile stored in the user Assets collection
*/
/*
1) Choose country name
*/
// List of country name: https://en.wikipedia.org/wiki/List_of_FIPS_country_codes
var countryname='Ukraine';
var countries = ee.FeatureCollection('USDOS/LSIB_SIMPLE/2017');
var aoi = countries.filter(ee.Filter.eq('country_na', countryname));
Map.addLayer(aoi,{},'AoI', false);
Map.centerObject(aoi,6);
/*
2) Use a user defined geometry.
Uncomment the two lines below if you want to use a defined geometry as AoI
*/
// var aoi = ee.FeatureCollection(geometry);
// Map.centerObject(aoi,8);
/*
3) Load a shapefile from Assets collection.
Uncomment and modify the lines below if you want to use a shapefile stored in your assets
*/
// var aoi= ee.FeatureCollection('users/josemanueldelgadoblasco/UKR_adm0')
// Map.centerObject(aoi,8);
/*
SET TIME FRAME
Set start and end dates of a period that you want to generate the mRVI. Make sure it is long enough for
Sentinel-1 to acquire an image (repitition rate = 6 days). Adjust these parameters, if
your ImageCollections (see Console) do not contain any elements.
*/
// Set the start and end dates to be used as pre-event in YYYY-MM-DD format.
var startDate = ee.Date('2023-01-01');
var endDate = ee.Date('2023-06-14');
/*
---->>> DO NOT EDIT THE SCRIPT PAST THIS POINT! (unless you know what you are doing) <<<---
------------------>>> now hit the'RUN' at the top of the script! <<<-----------------------
-----> The final mRVI product will be ready for download on the right (under tasks) <-----
*/
// Creating dekad list from the date range
// Calculate the number of months between startDate and endDate
var numMonths = endDate.difference(startDate, 'month').round();
// Generate a sequence of months from startDate to endDate
var monthSequence = ee.List.sequence(0, numMonths, 1).map(function(month) {
return startDate.advance(ee.Number(month), 'month');
});
// Function to generate dekad dates for a given month
var generateDekads = function(date) {
date = ee.Date(date);
var y = date.get('year');
var m = date.get('month');
var dekad1 = ee.Date.fromYMD(y, m, 1);
var dekad2 = ee.Date.fromYMD(y, m, 11);
var dekad3 = ee.Date.fromYMD(y, m, 21);
return [dekad1, dekad2, dekad3];
};
// get the dekadList
var dekadList = monthSequence.map(generateDekads).flatten();
var filteredDekadList = dekadList.map(function(date){
return ee.Algorithms.If(
ee.Date(date).millis().lte(endDate.millis()),
date,
null
);
}).removeAll([null]);
// Remove duplicate dekad dates from filteredDekadList
filteredDekadList = filteredDekadList.distinct();
print(filteredDekadList);
// Auxiliary variables and Data
// VH polarization is needed to compute the mRVI
var polarization = 'VH';
// Using the ESA WorldCover to mask out urban, water and other non crop areas.
var LULC = ee.ImageCollection("ESA/WorldCover/v200");
// Selecting cropland and herbaceous classes (class with value 40)
var cropland = LULC.mosaic().clip(aoi).eq(40);
// Defining auxiliary functions
// Defining the mRVI formula, based on Agapiou, 2020 - https://doi.org/10.3390/app10144764
var addmRVI = function (img) {
var mRVI = img
.select(['VV'])
.divide(img.select(['VV']).add(img.select(['VH'])))
.pow(0.5)
.multiply(
img
.select(['VH'])
.multiply(ee.Image(4))
.divide(img.select(['VV']).add(img.select(['VH'])))
)
.rename('mRVI');
return img.addBands(mRVI);
};
// Translating User Inputs
// DATA SELECTION & PREPROCESSING
// Load the Sentinel-1 GRD data (linear units) and filter by predefined parameters
var rvi = ee.ImageCollection('COPERNICUS/S1_GRD_FLOAT')
.filterBounds(aoi)
.filterDate(startDate, endDate)
.filter(ee.Filter.eq('instrumentMode','IW'))
.filter(ee.Filter.listContains('transmitterReceiverPolarisation', polarization))
.filter(ee.Filter.eq('resolution_meters', 10))
.map(addmRVI)
.select('mRVI');
// Sorted time
var rvi_sorted = rvi.sort("system:time_start");
print(rvi_sorted);
// Mosaic all images within dekad calendar
// Function to create a mosaic for each dekad
var createMosaic = function(dekad) {
// Calculate the start date for the dekad
var startDate = ee.Date(dekad);
// Find the index of the current dekad
var currentIndex = ee.Number(filteredDekadList.indexOf(dekad));
// Find the index of the next dekad
var nextIndex = currentIndex.add(1);
// Check if the next dekad exists. If not, use the endDate.
var nextDate = ee.Algorithms.If(
nextIndex.lt(filteredDekadList.size()),
ee.Date(filteredDekadList.get(nextIndex)),
endDate
);
// Filter the images within the dekad
var dekadImages = rvi_sorted.filterDate(startDate, nextDate);
// Select the mRVI band from each image
var mRVIImages = dekadImages.select('mRVI');
// Calculate the median of the mRVI images
var medianImage = mRVIImages.reduce(ee.Reducer.median());
// Return the median image with the dekad property
return medianImage.set('dekad', dekad, 'system:time_start', startDate.millis());
};
// Apply the createMosaic function to each dekad in the filteredDekadList
var mosaicImages = ee.List(filteredDekadList.map(createMosaic));
// Convert the mosaicImages to an ImageCollection
var mosaicCollection = ee.ImageCollection.fromImages(mosaicImages);
// Multiply by 10000 and convert imageCollection to Uint16, can help preserve the precision
var toUInt16 = function(img){
return img.multiply(10000).toUint16().copyProperties(img, ["dekad", "system:time_start"]);
};
// apply mask to imageCollection, get mRVI only in cropland areas
var masking = function(img){
return img.updateMask(cropland).copyProperties(img, ["dekad", "system:time_start"]);
};
// Apply the toUInt16 function to each image in the mosaicCollection
var mosaicCollectionUInt16 = mosaicCollection.map(toUInt16);
// Apply the masking function to each image in the mosaicCollectionUInt16
var mosaicCollectionMasked = mosaicCollectionUInt16.map(masking);
// Print the masked mosaicCollection
print(mosaicCollectionMasked);
print(mosaicCollectionMasked.first().getInfo());
// Visualisation
// Symbology
var rviVis = {
min: 0.0,
max:8000,
palette: [
'FFFFFF', 'CE7E45', 'DF923D', 'F1B555', 'FCD163', '99B718', '74A901',
'66A000', '529400', '3E8601', '207401', '056201', '004C00', '023B01',
'012E01', '011D01', '011301'
],
};
// Add as map layer
Map.addLayer(LULC.first().clip(aoi),{bands: ['Map']},'landcover', false);
Map.addLayer(cropland.updateMask(cropland),{min:0,max:1,palette:['black','green']},'cropland', false);
Map.addLayer(mosaicCollectionMasked.first().clip(aoi), rviVis, 'RVI');
// Download process
// Batch export
mosaicCollectionMasked
.aggregate_array('system:index')
.evaluate(function (indexes){
indexes.forEach(function (index) {
var image = mosaicCollectionMasked
.filterMetadata('system:index', 'equals', index)
.first();
var date = ee.Date(image.get('system:time_start'));
var dateString = date.format('yyyyMMdd');
dateString.evaluate(function(res){
var filename = 'ukr_phy_s1_rvi_' + res;
Export.image.toDrive({
image: image.select('mRVI_median'),
description: filename,
folder:'ukr_rvi',
scale: 100,
maxPixels: 1e13,
region: aoi,
crs: 'EPSG:4326'
});
});
});
});
/*
* Exporting image without clicking RUN button
*
* 1. Run your Google Earth Engine code;
* 2. Wait until all the tasks are listed (the Run buttons are shown);
* 3. Click two computer keys fn and f12 at the same time and bring up console;
* or find it via: menubar Develop > Show JavaScript Console (Safari),
* and menubar View > Developer > JavaScript Console (Chrome)
* 4. Copy and paste (line 313-322 below) into the console, press Enter;
* 5. Wait until the code sends messages to the server to run all the tasks (you wait and relax);
* 6. Wait until GEE shows the dialogue window asking you to click "Run";
* then Copy and paste (line 324-335 below), press Enter
* Notes:
* Please bear in mind, the time execution is depend on the image size you will export.
* Example, 1 year data for Ukraine on MODIS VI takes a minute to popup a window "Task: Initiate image export".
* 7. Keep your computer open until all the tasks (Runs) are done
* (you probably need to set your computer to never sleep).
*/
/**
* Copyright (c) 2017 Dongdong Kong. All rights reserved.
* This work is licensed under the terms of the MIT license.
* For a copy, see <https://opensource.org/licenses/MIT>.
*
* Batch execute GEE Export task
*
* First of all, You need to generate export tasks. And run button was shown.
*
* Then press F12 get into console, then paste those scripts in it, and press
* enter. All the task will be start automatically.
* (Firefox and Chrome are supported. Other Browsers I didn't test.)
*
* @Author:
* Dongdong Kong, 28 Aug' 2017, Sun Yat-sen University
* yzq.yang, 17 Sep' 2021
*/
/*
function runTaskList(){
// var tasklist = document.getElementsByClassName('task local type-EXPORT_IMAGE awaiting-user-config');
// for (var i = 0; i < tasklist.length; i++)
// tasklist[i].getElementsByClassName('run-button')[0].click();
$$('.run-button' ,$$('ee-task-pane')[0].shadowRoot).forEach(function(e) {
e.click();
})
}
runTaskList();
function confirmAll() {
// var ok = document.getElementsByClassName('goog-buttonset-default goog-buttonset-action');
// for (var i = 0; i < ok.length; i++)
// ok[i].click();
$$('ee-table-config-dialog, ee-image-config-dialog').forEach(function(e) {
var eeDialog = $$('ee-dialog', e.shadowRoot)[0]
var paperDialog = $$('paper-dialog', eeDialog.shadowRoot)[0]
$$('.ok-button', paperDialog)[0].click()
})
}
confirmAll();
*/