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How to Radiometrically Terrain-Correct (RTC) Sentinel-1 Data Using GAMMA Software

Before and after RTC: In this detail from the test granule below, mountains in Bolivia (left) appear stretched on one side and compressed on the other. RTC (right) moves pixels to unstretch the mountains and adjusts pixel values to subtract the effect of slopes on brightness. Credit left: Copernicus Sentinel data 2015. Credit right: ASF DAAC 2016, contains modified Copernicus Sentinel data 2015, processed by ESA. 

Source: ASF Staff

Advanced (Linux): Use GAMMA software and scripts for high-quality results in correcting distortions in synthetic aperture radar (SAR) images. Note: GAMMA requires purchase, a significant cost.


Radiometric correction involves removing the misleading influence of topography on backscatter values. Terrain correction corrects geometric distortions that lead to geolocation errors. The distortions are induced by side-looking (rather than straight-down looking or nadir) imaging, and are compounded by rugged terrain. Terrain correction moves image pixels into the proper spatial relationship with each other. Radiometric terrain correction combines both corrections to produce a more useful product for science applications. This recipe is to support users who are comfortable working in the command line environment and have GAMMA installed on their computers.

ASF provides the perl scripts “” and “” to radiometrically terrain correct Sentinel-1A GRD data using GAMMA software. This script uses a DEM file and a Sentinel-1A granule as inputs and creates terrain-corrected GeoTIFFs of each polarization, an incidence angle map, a layover/shadow map, and a clipped DEM file that matches the area of the SAR image.


Materials List:

  • Sentinel-1A GRD product (download granule of your choice from Vertex or use Sample Granule)
  • Digital Elevation Model (DEM) (available from many sources, including USGS Earth Explorer and OpenTopography; choose projection in meters)
  • GAMMA software package (MSP + ISP + DIF&GEO + LAT). Note: GAMMA requires purchase, a significant expense.
  • GDAL warp (part of GDAL Utilities)
  • (included in the Data Recipe zip button at the top of this recipe)
  • (included in the Data Recipe zip button at the top of this recipe)


    1. Download and install in your local environment the GAMMA software package.
    2. Download and install the most recent version of GDAL utilities; this will include gdalwarp. To do this for the Linux operating system Ubuntu, for example, use apt-get: (sudo apt-get install gdal-bin).
    3. Put the script and the into a directory that is in your path. Modify your path if necessary using “export PATH=$PATH:~[desired directory]”.
    4. To turn these scripts into executable files, change into the directory the scripts are saved in and enter “chmod a+x *”.
    5. Create a directory to house the Sentinel-1A GRD products (the .zip file).
    6. Download a Sentinel-1A GRD granule from ASF Vertex and move it to your GAMMA processing directory. (Sample granule available).
    7. Unzip the Sentinel-1A GRD file in your processing directory.
    8. Download a DEM: The script will automatically download and apply an SRTMGL1 DEM file from OpenTopo, or you may use a DEM of your choice.

Note: If you want to use your own DEM, download an external DEM and corresponding par file in GAMMA format, and place in GAMMA processing directory. The downloaded DEM must be in GAMMA format (DEM and par file).

    1. The following options are available when running the script:
      • output     Output RTC filename
      • -e dem     (option) sepcify a DEM file to use (with par file), e.g., big.dem to specify big.dem and big.dem.par
      • -r res    (option) specify the output resolution (default 10 meters)
    2. Run the script:

perl [options] <output filename>


Once the script has finished running, the main output can be found in the PRODUCT directory. The PRODUCT directory will contain the 4 or 5 output product files — one for each polarization (e.g., VV or VV and VH), one for the incidence angle map (inc_map), one for the layover/shadow map (ls_map), and one for the clipped DEM file (dem).

Here is a sample PRODUCT directory listing:

ls -1 PRODUCT/

Many intermediate files are left in the current working directory as well as several sub-directories being created after the run has completed. These files can be deleted once processing of the RTC products has completed. Below is a list of the intermediate files that do not need to be archived further.

ls -1 20150513T100702.log
big.dem big.dem.par dem.tif geo_vh


Before and After Images

Sample granule prior to RTC processing
RTC product

How the Perl Scripts Work

Given the following:

pol polarization being worked on
output output name
res desired output resolution
look_fact calculated look factor = int($res/10+0.5)
dem input DEM file
    1. Ingests the data into GAMMA format to begin radiometric terrain correction of the main polarization data.

par_S1_GRD */*/*$pol*.tiff */*/*$pol*.xml */*/*/calibration-*$pol*.xml
*/*/*/noise-*$pol*.xml $output.$pol.GRD.par $output.$pol.GRD

    1. (Optional if users use -r res) Multi-looks the data to the desired resolution.

​multi_look_MLI $output.$pol.GRD $output.$pol.GRD.par
$output.$pol.mgrd $output.$pol.mgrd.par $look_fact $look_fact

Note: Multi-looking will not be performed if $look_fact < 2.

    1. Converts the data from ground range to slant range.

GRD_to_SR $output.$pol.mgrd.par $output.$pol.mli.par –
$output.$pol.mgrd $output.$pol.mli 1 1 2 $res $res

    1. Generates initial lookup table, simulated SAR image, and DEM segment parameters; erases existing DEM segment parameters.

​ $output.$pol.mli $output.$pol.mli.par $dem
$dem.par geo_$pol/area.dem geo_$pol/area.dem_par geo_$pol image $res 0 -p -j -n 1 -q -c

Here, the options used are as follows:

-p use the pixel area program to create simulated SAR image
-j don't use layover-shadow map in pixel area calculation
-n 1 use a first-order mapping function
-q quiet mode — don't display intermediate results
-c create calibrated output files
    1. Measures initial offset between simulated SAR image and actual SAR image.

​ $output.$pol.mli $output.$pol.mli.par $dem
$dem.par geo_$pol/area.dem geo_$pol/area.dem_par geo_$pol image $res 1 -p -j -n 1 -q -c

    1. Performs refinement of lookup table by offset measurement with respect to the simulated SAR image. $output.$pol.mli $output.$pol.mli.par $dem
$dem.par geo_$pol/area.dem geo_$pol/area.dem_par geo_$pol image $res 2 -p -j -n 1 -q -c

    1. Updates lookup table and produce terrain-geocoded SAR image and DEM in SAR range-Doppler coordinates (RDC). $output.$pol.mli $output.$pol.mli.par $dem
$dem.par geo_$pol/area.dem geo_$pol/area.dem_par geo_$pol image $res 3 -p -j -n 1 -q -c

Note: Once the first polarization is completed, the second polarization proceeds as follows (assuming it exists):

    1. Ingests the data into GAMMA format to perform terrain correction on the second polarization.

​par_S1_GRD */*/*$pol*.tiff */*/*$pol*.xml */*/*/calibration-*$pol*.xml
*/*/*/noise-*$pol*.xml $output.$pol.GRD.par $output.$pol.GRD

    1. Multi-looks the data to the desired resolution (optional step)

multi_look_MLI $output.$pol.GRD $output.$pol.GRD.par
$output.$pol.mgrd $output.$pol.mgrd.par $look_fact $look_fact

Note that multi-looking will not be performed if $look_fact < 2.

    1. Converts the data from ground range to slant range.

GRD_to_SR $output.$pol.mgrd.par $output.$pol.mli.par –
$output.$pol.mgrd $output.$pol.mli 1 1 2 $res $res

    1. Performs refinement of lookup table by offset measurement with respect to the simulated SAR image. $output.$pol2.mli $output.$pol2.mli.par $dem
$dem.par geo_$pol1/area.dem geo_$pol1/area.dem_par geo_$pol2image $res 3 -p -j -n 1 -q -c

Note: $pol2 is the cross-polarization and $pol1 is the main polarization.

Example Run

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