# Effect of DEM Used for Terrain Correction on Forest Windthrow Detection Using COSMO SkyMed Data
## 1 Introduction  
Synthetic Aperture Radar (SAR) images acquired over areas with complex topography often exhibit significant distortions in the backscatter values due to the side-looking nature of SAR sensors. For instance, hills facing the SAR system typically appear brighter (with higher backscatter values) because they reflect energy back toward the sensor, while hills facing away appear darker (with lower backscatter values) because they scatter energy away from the sensor. Additionally, SAR images provided in Level 1A or 1B by the data providers (e.g., European Space Agency) also need a geometric correction to determine the correct location of each pixel with respect to the ground using a digital elevation model. Usually, the process to radiometrically correct the images with respect to the topography is called radiometric terrain correction, while the correction of the geometric distortions and the correct positioning of the pixels with respect to the terrain is called geometric terrain correction. SAR images in complex topography can be affected by layover and shadows. Layover occurs when the radar beam reaches the top of a tall feature before reaching its base. In a SAR image with layover, the mountains look as if they have fallen over toward the sensor. Steeper angles lead to more extreme layovers, where mountain tops appear to lay over their base. Layover pixels appear to have high values in the image (bright pixels). Shadows in SAR images arise when higher objects obstruct the radar beam, resulting in certain areas not being illuminated and appearing dark due to the absence of backscattered energy. The extent of shadow effects increases as the radar beam's incidence angle becomes more oblique with respect to the surface. Where slopes are very steep, the dim side may be completely dark because no radar signal is returned at all. Before SAR images can be reliably used for surface mapping and change detection, it is essential to correct the backscatter values for topographic effects and to address distortions caused by layovers and shadows. The process adopted to map layover and/or shadow areas is known as layover/shadows masking. Many algorithms exist in the literature to perform both radiometric and geometric terrain correction [1; 2; 3; 4] and layover/shadows masking [5; 6; 7; 8] and all of them rely on the use of a Digital Elevation Model (DEM). A DEM is the umbrella term to indicate, in the most generic possible way, an elevation model. Inside DEMs it is possible to differentiate two products, the digital terrain models (DTMs) and the digital surface models (DSMs). A DSM is the specific term to indicate a surface model, i.e., it represents the absolute elevation at the very top of solid objects in the scene; it includes buildings, infrastructures, and vegetation. A DSM is therefore a DEM, but a DEM is not necessarily a DSM. A DTM is the specific term to indicate the elevation of the natural topography, i.e., after having removed vegetation and man-made buildings. As for the DSM, a DTM is a DEM, but a DEM is not necessarily a DTM. There are some worldwide DEMs that are widely used for remote sensing applications, such as the SRTM [9], the ASTER [10], the ALOS [11], or the Copernicus one [12]. These models are usually DSMs, or if based on SAR data, they could be either a DSM, a DTM, or something in between depending on the SAR wavelength. Such data are available worldwide, but they typically have a significantly coarser pixel spacing compared to those generated from LiDAR data. Airborne LiDAR-based DEMs are available nationwide in a few countries or locally in some regions of the world. Terrain correction with a detailed VHR DEM becomes particularly important when using SAR data at a VHR. Indeed, the most advanced and recent satellite constellations acquire SAR images with a pixel spacing in the order of meters or even sub-meters (VHR). In these cases, the terrain correction with a high-spatial-resolution model becomes fundamental to preserving the spatial details of the images [13; 14].