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Sentinel-1 Toolbox and Radar Processing


By Connormah (Based off) [CC BY-SA 3.0 (http://creativecommons.org/licenses/by-sa/3.0)], via Wikimedia Commons

Hi everyone, I've started my M.Sc program here at Western University with Dr. Catherine Neish. Together with the radar research group and the Centre of Planetary Science Exploration, we are taking on a radar remote sensing project of Axel Heiberg Island in the Canadian Arctic. I'm really excited to be working on this project, with this team. My current goals are to develop the tools and skill sets needed to begin radar data processing once our RADARSAT-2 data are acquired. We have some images already, but have requested new acquisitions from the Canadian Space Agency that will be taken in July 2016.

Although I have worked with radar data before (see previous post on Magellan Venus data), I was not involved with any of the pre-processing or filtering. The new RADARSAT-2 data will be raw, and so a large component of this project will processing the data for interpretation.

Sentinel-1 Interface with sample data from Vancouver

One tool that can be used for radar processing is the Sentinel-1 Toolbox. The Sentinel-1Toolbox is free to download from the European Space Agency here. Previously, I had tried learning to use another radar program, PolSARpro, with less success. So far, I am finding that Sentinel-1 is more accessible and friendly to beginners, as the ESA provides comprehensive tutorials on how to use the program. This post is giving a quick overview of what is learned in the first Polarimetric SAR Basics Tutorial.

The ESA gives us some sample data to work with, from RADARSAT-2 over Vancouver, B.C. After opening the quad-pol files, we are prompted to calibrate the data. Sentinel is a clever program that auto-detects the properties of the input data, and determines how it ought to be calibrated.

The next type of processing introduced is multi-look processing. If a radar beam is divided into multiple sub-beams, then the various "looks" can be averaged together to reduce speckle noise in the image.

Noise can also be removed through speckle reduction. Speckle reduction is a filtering process by which calculations of average pixel value is performed in small groups to smooth out the 'salt and pepper' affect seen on unprocessed radar images. Speckle reduction, along with multi-look processing, smooths over the image, and has the consequence of lowering the image resolution.

Vancouver image with multi-look processing
Vancouver image with multi-look processing and speckle reduction filtering

The final tool introduced in the SAR Basics Tutorial is Terrain Correction. Distortion can occur in a SAR image through foreshortening, layover, and shadow effects. Foreshortening occurs when a radarbeam interacts with the base of a slope tilted towards the radar prior to the peak of the slope. The slope appear shorters in the image than in reality. In contrast, layover occurs when the radar signal reaches the top of a feature before the base; opposite of foreshortening. Similar to foreshortening, layover effects distortes the positions of the peak and base of a slope relative to another, making it appear such that the peak arrives "first" in the image. Foreshortening and layover cause radar shadow, which is when an area on the backslope is blocked from the radar. Shadow results in a dark area of little to no radar return. Terrain Correction uses a digital elevation model to geocode an image, and converts the slant range to a map coordinate system to georectify any geometric distortion caused by foreshortening, layover, or shadow. The image and DEM are resampled, in the case of the tutorial, through bilenear interpolation.

Terrain Corrected Vancouver Map
Terrain Corrected Vancouver Map in Virtual Band

This concludes the SAR Basics Tutorial from ESA.

Next week I will check out the Radarsat-2 Interferometry and the SAR Polarimetry tutorials.

Veci, Luis. (2015). SENTINEL-1 Toolbox: SAR Basics Tutorial. Array Systems Computing Inc.

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