4.5 Article

A Relief Dependent Evaluation of Digital Elevation Models on Different Scales for Northern Chile

出版社

MDPI
DOI: 10.3390/ijgi8100430

关键词

accuracy assessment; digital terrain model; stereo satellite imagery; topography; terrestrial laser scanning; topographic position index; terrain ruggedness index; unmanned aerial vehicles

资金

  1. Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) [268236062-SFB 1211]

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Many geoscientific computations are directly influenced by the resolution and accuracy of digital elevation models (DEMs). Therefore, knowledge about the accuracy of DEMs is essential to avoid misleading results. In this study, a comprehensive evaluation of the vertical accuracy of globally available DEMs from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Shuttle Radar Topography Mission (SRTM), Advanced Land Observing Satellite (ALOS) World 3D and TanDEM-X WorldDEM (TM) was conducted for a large region in Northern Chile. Additionally, several very high-resolution DEM datasets were derived from Satellite Pour l'Observation de la Terre (SPOT) 6/7 and Pleiades stereo satellite imagery for smaller areas. All datasets were evaluated with three reference datasets, namely elevation points from both Ice, Cloud, and land Elevation (ICESat) satellites, as well as very accurate high-resolution elevation data derived by unmanned aerial vehicle (UAV)-based photogrammetry and terrestrial laser scanning (TLS). The accuracy was also evaluated with regard to the existing relief by relating the accuracy results to slope, terrain ruggedness index (TRI) and topographic position index (TPI). For all datasets with global availability, the highest overall accuracies are reached by TanDEM-X WorldDEM (TM) and the lowest by ASTER Global DEM (GDEM). On the local scale, Pleiades DEMs showed a slightly higher accuracy as SPOT imagery. Generally, accuracy highly depends on topography and the error is rising up to four times for high resolution DEMs and up to eight times for low-resolution DEMs in steeply sloped terrain compared to flat landscapes.

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