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SAR imagery is distorted geometrically and radiometrically In mountainous and hilly areas,. With Geometric Terrain Correction and Terrain Flattening applications, both the geometric and radiometric terrain effects can be removed from the backscatters, leaving noise being the only factor affecting the land cover classification accuracy. A multi-temporal compositing technique in ESA-SNAP can be applied in this case to reduce the noise level. Also, spatially varying local resolution effects can be compensated if images of both ascending and descending views are combined (not performed in this video but you can try it by yourself). The technique described in this video generates a composite SAR image from a stack of terrain-flattened and geometrically terrain corrected images together with their simulated local illuminated areas. 

DEM ( Digital Elevation Model ) extraction is one of popular topic in GIS and Remote Sensing. There are so many ways and methods to produce a DEM. You can use survey data in points format then interpolate it to became raster DEM, or using contour lines to generate DEM. Almost every GIS and Remote Sensing can do this kind of analysis. The better approach and yielding a better result is using Photogrammetry techniques. For photogrammetry, you needs satellite imagery or aerial photographs that has image overlap between flight line that later can be opened together in a photogrammetric software, and then from the overlaps, height and elevation information could be reconstructed and sampled together in their respective grids, and finally a DEM has been created.  Recent development of survey technology has introduce us to LIDAR technology that enabling us to get a DEM in superfine resolution and covering large area. UAV technology is also progressed so much even photogrammetry survey can...

This article is a continuation from my previous post about how to perform Wind Direction and Speed Estimation from SAR data. In previous post that you can also read from this blog, I have shown how to directly measure Wind Speed and Wind Direction using ENVISAT-ASAR data. And you can also perform this kind of analysis using other kind SAR Sensors like ALOS PALSAR, Sentinel-1 or ERS.  Now for this post, I will talks about post-processed wind speed and wind direction data generated from Sentinel-1 SAR data. Why Post-Processed ? because ESA already publish wind data from Sentinel-1 into Sentinel-1 OCN Product. So if you are using this OCN product, you dont have to generate Wind Speed and Wind Direction by yourself.  The video tutorial below demonstrate how to get those wind parameters data from Sentinel-1 OCN Product, using ESA-SNAP Software. Hopefully it will find some use to you out there.