Sentinel 1 images SLC and GRD

[ABraun]

About the differences between SLC and GRD, please see here:

GTC (Geocoded terrain corrected) data

it means that its already ground-range corrected. Unlike SLC data the pixels’ areas are already of same size. Astrium has made nice graphics for this case. They refer to TerraSAR-X but the principle is the same for most SAR satellites: Slant Range Complex (SLC/SSC/L.1.1) [image] Data is neither multi-looked nor projected Ground Range Detected (GRD/MGD/L1.5) [image] Data is multi-looked but not projected Geocoded Ellipsoid Corrected (GEC/L2.0) [image] Data is projected but topographic d…

About suitable workflows:

Radiometric & Geometric Correction Workflow

for SLC data I would suggest TOPS Split Apply Orbit file Thermal Noise Removal Calibration to Beta0* TOPSAR Deburst Radiometric terrain flattening (Speckle filtering) Range Doppler Terrain Correction If you don’t need the phase information you can also download it as a GRD product and only apply the following: Apply Orbit file Thermal noise removal Calibration to Beta0 Radiometric terrain flattening (Speckle filtering) Range Doppler Terrain Correction or (if you don’t have much topography)…

But I think GRD images are enough for classification purposes:

How Decompose Sentinel-1 GRDH data

for the estimation of forest areas GRD data is completely sufficient. The general work flow is: Apply Orbit File Calibrate Speckle Filter Range-Doppler Terrain Correction You can use the ratio between VV and VH in order to extract the forest areas. VH values are high where ever the incoming vertical wave is backscattered horizontally to a high degree. This is often the case for vegetation with larger volumes. Make A RGB composite out of Red: VV Green: VH and Blue: VH/VV. The Forest ares sh…

How classifications are performed in SNAP is explained here:

Sentinel 1 land cover classification

I’m looking to do a landcover classification of Sentinel 1 sar data in either SNAP or QGIS. Does anyone know how to go about doing this?