# Effect of DEM Used for Terrain Correction on Forest Windthrow Detection Using COSMO SkyMed Data
## 4 Discussion  
To the best of our knowledge, this study represents one of the first investigations into the impact of DEMs on terrain correction for COSMO SkyMed images. While our focus is on COSMO SkyMed data and windthrow detection, the insights gleaned from this research hold relevance for anyone involved in SAR image terrain correction. The use of DEMs with a fine pixel spacing (i.e., 2 m) in the processing of VHR SAR images emerged to be of high importance, as underlined in [15] and [31]. In particular, in [31] the authors underlined that when the pixel spacing of DEM is too rough compared with that of SAR images, lots of spatial information on SAR images will be lost in regions where the terrain changes significantly. This is the case in mountain areas where the terrain elevation can change rapidly. The results obtained with the LiDAR-based DTM at 2 m pixel spacing are undeniably superior to all other datasets. Even when downsampled to 30 m pixel spacing, the LiDAR DTM still provides better corrections than satellite DEMs downsampled at 30 m pixel spacing. This is probably more related to the type of information contained in the DTM itself than to the pixel spacing: while the global satellite DEMs are neither representing the terrain nor the surface (i.e., they are neither DTM nor DSMs), the LiDAR-derived DTM is representing the terrain very accurately. When subtracting the LiDAR DTM from the satellite-based DSMs, significant terrain features emerge, with height differences in the range of \(-73\) to \(+232\) meters. These variations have a direct impact on SAR image corrections, particularly in areas with rugged terrain, where finer topographical details improve the accuracy of the corrections. In [32], [PERSON] et al. analysed the geolocation accuracy  
Figure 5: Windthrow detection maps for a subset of the study area. of COSMO-SkyMed images corrected with a local LiDAR DTM and global DEMs, finding that LiDAR DEM consistently produced superior results across all datasets. Additionally, they observed that the commonly used global DEMs, such as SRTM and ASTER, introduced significant terrain distortions, particularly in mountainous regions. The differences in results obtained when using the same DEM at different pixel spacings (e.g., 2 m vs. 30 m) suggest that it is preferable to use global DEMs at their native resolution. Allowing SNAP to manage any discrepancies in pixel spacing between the DEM and the SAR image yields better outcomes than manually upsampling the DEM before processing in SNAP. Indeed, the SNAP module for terrain flattening requires a DEM pixel spacing higher than the image pixel spacing, and when this is not the case (as for the 30 m pixel spacing DEMs in our study), SNAP either oversamples the DEM to higher pixel spacing or multilooks the source image to lower resolution ([[https://step.esa.int/main/wp-content/help/versions/10.0.0/snap-toolboxes/eu.esa.microwavetbx.sar.op.sar.processing.ui/operators/TerrainFlatteningOp.html](https://step.esa.int/main/wp-content/help/versions/10.0.0/snap-toolboxes/eu.esa.microwavetbx.sar.op.sar.processing.ui/operators/TerrainFlatteningOp.html)]([https://step.esa.int/main/wp-content/help/versions/10.0.0/snap-toolboxes/eu.esa.microwavetbx.sar.op.sar.processing.ui/operators/TerrainFlatteningOp.html](https://step.esa.int/main/wp-content/help/versions/10.0.0/snap-toolboxes/eu.esa.microwavetbx.sar.op.sar.processing.ui/operators/TerrainFlatteningOp.html)), accessed on 15 November 2024). Choosing this second option means that the SAR image is not terrain corrected at 2.5 m using a 30 m pixel spacing DEM, but it is multi-looked to 30 m and terrain corrected at 30 m. The worst results were observed with the LiDAR-based DSM at 2 m pixel spacing.