Abstract

Freely available global digital elevation models (DEMs) are important inputs for many research fields and applications. During the last decade, several global DEMs have been released based on satellite data. ASTER and SRTM are the most widely used DEMs, but the more recently released, AW3D30, TanDEM-X and MERIT, are being increasingly used. Many researchers have studied the quality of these DEM products in recent years. However, there has been no comprehensive and systematic evaluation of their quality over areas with variable topography and land cover conditions. To provide this comparison, we examined the accuracy of six freely available global DEMs (ASTER, AW3D30, MERIT, TanDEM-X, SRTM, and NASADEM) in four geographic regions with different topographic and land use conditions. We used local high-precision elevation models (Light Detection and Ranging (LiDAR), Pleiades-1A) as reference models and all global models were resampled to reference model resolution (1m). In total, 608 million 1x1 m pixels were analyzed. To estimate the accuracy, we generated error rasters by subtracting each reference model from the corresponding global DEM and calculated descriptive statistics for this difference (e.g., median, mean, root-mean-square error (RMSE)). We also assessed the vertical accuracy as a function of the slope, slope aspect, and land cover. We found that slope had the strongest effect on DEM accuracy, with no relationship for slope aspect. The AW3D30 was the most robust and had the most stable performance in most of the tests and is therefore the best choice for an analysis of multiple geographic regions. SRTM and NASADEM also performed well where available, whereas NASADEM, as a successor of SRTM, showed only slight improvement in comparison to SRTM. MERIT and TanDEM-X also performed well despite their lower spatial resolution.

Highlights

  • Digital elevation models (DEMs) and the topographic and terrain variables derived from these models are fundamental inputs for environmental and landscape modeling and spatial analysis [1,2,3,4,5], especially for research in geomorphology [6], hydrology [7], and geology [8]

  • We examined the accuracy of six freely available global digital elevation models (DEMs) (ASTER, ALOSWorld3D m DEM (AW3D30), Multi-Error-Removed Improved-Terrain (MERIT), TanDEM-X, Shuttle Radar Topography Mission (SRTM), and NASADEM) in four geographic regions with different topographic and land use conditions

  • Due to the potential analytical bias that results from artifacts and inconsistencies in DEMs, several studies have investigated the quality of such products, especially for those developed at a global scale

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Summary

Introduction

Digital elevation models (DEMs) and the topographic and terrain variables derived from these models (e.g., slope aspect, slope, channels, hillslopes) are fundamental inputs for environmental and landscape modeling and spatial analysis [1,2,3,4,5], especially for research in geomorphology [6], hydrology [7], and geology [8]. Due to the potential analytical bias that results from artifacts and inconsistencies in DEMs, several studies have investigated the quality of such products, especially for those developed at a global scale These investigations usually focused on the height (vertical) accuracy of the DEM [15,16] or the model’s performance in different applications, such as river network generation, the acquisition of geomorphological metrics, and flood simulation [12,17]. The vertical accuracy of the Shuttle Radar Topography Mission (SRTM; released in 2003) ranges from 2.18 to 21.70 m [10,20] and for the Advanced Spaceborne Thermal Emission and Reflection satellite (ASTER, released in 2006), the accuracy ranges from 4.56 to 7.10 m [10,20] These high-resolution global DEM products, developed based on radar data (SRTM) and data from optical sensors (ASTER), were one of the first freely available DEMs at a global scale. If their accuracy can be confirmed, these new DEM products, which are based on more current remote sensing data and better processing methods, will be highly valuable because of their ability to capture natural or man-made changes in the topography of terrestrial surfaces [29]

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