I am trying to visualize flooding after hurricane Harvey that made landfall on August 25-26 2017.

Based on this video, I've been able to obtain the basics of Sentinel-1 SAR imagery. Sentinel 1 comes in many flavors I am not sure what is the best approach to visualize inundation.

Splitting up my question into smaller ones:

  1. What is the best way to visualize inundation using SAR data?
    1.1 What Acquisition Mode? (I choose IW, based on ESA description)
    1.2 What Polarization should I use? (I randomly choose [VV,HV])
    1.3 Should I handle ascending and descending imagery separately? (I choose to split it up)
    1.4 How to go to create a false color map? (I've tried (r,g,b)(HH,HV,HH/HV) and (r,g,b)(HH,HV,HH-HV).

In addition it would be great to understand what min-max values to choose for each band.

I've created a little testing script in Google Earth Engine (link):

var ic = ee.ImageCollection("COPERNICUS/S1_GRD")
var ivp = {"opacity":1,"bands":["VV","VH","VV/VH"],"min":-20,"max":-5,"gamma":1};
var ivp2 = {"opacity":1,"bands":["VV","VH","VV-VH"],"min":-20,"max":0,"gamma":4.935};

// Harvey made landfall on August 25
var date_start = ee.Date("2017-08-25")
var date_end = ee.Date("2017-09-02")

var ic_vvvh = ee.ImageCollection('COPERNICUS/S1_GRD')
        .filter(ee.Filter.eq('instrumentMode', 'IW'))
        .map(function(image) {
          var edge = image.lt(-50.0);
          var maskedImage = image.mask().and(edge.not());
          return image.updateMask(maskedImage);

function add_ratio_band(image){
  var new_image = ee.Image(image)
  var i_ratio = image.select("VV").divide(image.select("VH"))
  i_ratio = i_ratio.rename("VV/VH")
  new_image = new_image.addBands(i_ratio)
  return new_image

function add_difference_band(image){
  var new_image = ee.Image(image)
  var i_ratio = image.select("VV").subtract(image.select("VH"))
  i_ratio = i_ratio.rename("VV-VH")
  new_image = new_image.addBands(i_ratio)
  return new_image

ic_vvvh = ic_vvvh.map(add_ratio_band)
ic_vvvh = ic_vvvh.map(add_difference_band)

var ic_vvvh_desc = ic_vvvh.filter(ee.Filter.eq('orbitProperties_pass', 'DESCENDING'));
var ic_vvvh_asc = ic_vvvh.filter(ee.Filter.eq('orbitProperties_pass', 'ASCENDING'));

Map.addLayer(ic_vvvh_asc,ivp,"S1 [VV,HV,VV/HV]")
Map.addLayer(ic_vvvh_asc,ivp2,"S1 [VV,HV,VV-HV]")

I am cross referencing with areal imagery: https://storms.ngs.noaa.gov/storms/harvey/index.html#12/29.8395/-95.0695

And the result look promising:

enter image description here

enter image description here

  • I am very interested in your work. Did you have any progress?
    – Marco
    Commented Jan 25, 2019 at 12:43

2 Answers 2


I would check out the tutorial done by Assoc. Prof. Shaun Levick at the GEARS Lab, Darwin Australia University. It covers, polarization and acquisition modes etc.


and the associated text tutorial at:


You will notice in the tutorial that you can adjust the min and max values on:

Map.addLayer(VH, {min: -20, max: -7}, 'VH');

This will help to refine the added layer specific to your region of interest.


NASA organized an ARSET webinar on this topic some months ago. Please check this out: https://arset.gsfc.nasa.gov/sites/default/files/disasters/19-AdvSAR-2/SAR%20Disasters%20Part%201.pdf

According to this document, the answers to your questions are the following:

  • 1.1 IW Acquisition Mode

  • 1.2 Polarizations VV & VH

  • 1.3 They use ascending pass only

  • 1.4 They only use two bands, VH and VV.

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