The FABDEM Outperforms the Global DEMs in Representing Bare Terrain Heights

Abstract

Many remote sensing and geoscience applications require a high-precision terrain model. In 2022, the Forest And Buildings removed Copernicus digital elevation model (FABDEM) was released, in which trees and buildings were removed at a 30 m resolution. Therefore, it was necessary to make a comprehensive evaluation of this model. This research aims to perform a qualitative and quantitative analysis of fabdem in comparison with the commonly used global dems. We investigated the effect of the terrain slope, aspect, roughness, and land cover types in causing errors in the topographic representation of all dems. The fabdem had the highest overall vertical accuracy of 5.56 m. It was the best dem in representing the terrain roughness. The fabdem and Copernicus dem were equally influenced by the slopes more than the other models and had the worst accuracy of slope representation. In the tree, built, and flooded vegetation areas of the fabdem, the mean errors in elevation have been reduced by approximately 3.34 m, 1.26 m and 1.55 m, respectively. Based on Welch's t-test, there was no significant difference between fabdem and Copernicus dem elevations. However, the slight improvements in the fabdem make it the best filtered dem to represent the terrain heights over different land cover types.