Validation of TanDEM-X elevation data for a forested karst area in Slovakia (Central Europe)
- Published
- Accepted
- Subject Areas
- Computational Science, Spatial and Geographic Information Science
- Keywords
- Slovak Karst, LiDAR, InSAR, DSM, DTM, landforms classification, geomorphons, elevation residuals
- Copyright
- © 2018 Bandura et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2018. Validation of TanDEM-X elevation data for a forested karst area in Slovakia (Central Europe) PeerJ Preprints 6:e27077v1 https://doi.org/10.7287/peerj.preprints.27077v1
Abstract
Recent production of a new radar-based global DEM by the TanDEM-X space mission has opened new options for geomorphometric analysis across multiple scales providing 0.4 arc second spatial resolution. However, the accuracy and suitability of this data has not been evaluated in such an extensive manner as for the widely exploited SRTM data. We present a validation of the vertical accuracy of TanDEM-X DEM product and evaluation of its suitability for landform classification in a forested karst area. The Geomorphons method was used for the automated landform classification focused on identification of dolines for which polygons of dolines mapped by expert-driven approach were used for validation. Airborne lidar data in the form of DSM and DTM were used as the reference dataset for validation of the DEM. The results show that the vertical RMSE of the TanDEM-X data is 3.42 m with respect to lidar DSM and 9.64 m with respect to lidar DTM. The identification of dolines by the geomorphon approach achieved 73 % with TanDEM-X, lower than for the lidar DTM (85 %).
Author Comment
This paper was presented at the Geomorphometry 2018 conference in Boulder, CO in August 2018.