Abstract

Abstract. The resolution and accuracy of digital elevation models (DEMs) have direct influence on further geoscientific computations like landform classifications and hydrologic modelling results. Thus, it is crucial to analyse the accuracy of DEMs to select the most suitable elevation model regarding aim, accuracy and scale of the study. Nowadays several worldwide DEMs are available, as well as DEMs covering regional or local extents. In this study a variety of globally available elevation models were evaluated for an area of about 190,000 km2. Data from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) 30 m, Shuttle Radar Topography Mission (SRTM) 30 m and 90 m, Advanced Land Observing Satellite (ALOS) World 3D 30 m and TanDEM-X WorldDEM™ – 12 m and 90 m resolution were obtained. Additionally, several very high resolution DEM data were derived from stereo satellite imagery from SPOT 6/7 and Pléiades for smaller areas of about 100–400 km2 for each dataset. All datasets were evaluated with height points of the Geoscience Laser Altimeter System (GLAS) instrument aboard the NASA Ice, Cloud, and land Elevation (ICESat) satellite on a regional scale and with nine very high resolution elevation models from UAV-based photogrammetry on a very large scale. For all datasets the root mean square error (RMSE) and normalized median absolute deviation (NMAD) was calculated. Furthermore, the association of errors to specific terrain was conducted by assigning these errors to landforms from the topographic position index (TPI), topographic roughness index (TRI) and slope. For all datasets with a global availability the results show the highest overall accuracies for the TanDEM-X 12 m (RMSE: 2.3 m, NMAD: 0.8 m). The lowest accuracies were detected for the 30 m ASTER GDEM v3 (RMSE: 8.9 m, NMAD: 7.1 m). Depending on the landscape the accuracies are higher for all DEMs in flat landscapes and the errors rise significantly in rougher terrain. Local scale DEMs derived from stereo satellite imagery show a varying overall accuracy, mainly depending on the topography covered by the scene.

Highlights

  • Nowadays digital elevation models (DEMs) are mainly generated by remote sensing techniques

  • The highest accuracies were measured for the 12 m TanDEM-X with a root mean square error (RMSE) of 2.3 m and a normalized median absolute deviation (NMAD) of 0.8 m

  • The lowest were detected for the 30 m ASTER GDEM with a RMSE of 8.9 m and a NMAD of 7.1 m

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Summary

Introduction

Nowadays digital elevation models (DEMs) are mainly generated by remote sensing techniques. They are acquired by airborne or satellite imagery with optical stereoscopy, space-borne Interferometric Synthetic Aperture Radar (InSAR) or Light Detection and Ranging (LiDAR). It is crucial to analyse the accuracy of digital elevation models to select the most suitable one regarding to aim, accuracy and scale of the study. While the identification of large channel profiles over wide distances is possible even with 90 m resolution data, landscapes in large scales require DEMs with 1 – 30 m spatial resolution to identify individual hillslopes and ridges (Grieve et al, 2016a, Grieve et al, 2016b)

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