Validation of digital elevation models (DEMs) and comparison of geomorphic metrics on the southern Central Andean Plateau

Benjamin Purinton,Bodo Bookhagen

doi:10.5194/esurf-5-211-2017

Abstract

Abstract. In this study, we validate and compare elevation accuracy and geomorphic metrics of satellite-derived digital elevation models (DEMs) on the southern Central Andean Plateau. The plateau has an average elevation of 3.7 km and is characterized by diverse topography and relief, lack of vegetation, and clear skies that create ideal conditions for remote sensing. At 30 m resolution, SRTM-C, ASTER GDEM2, stacked ASTER L1A stereopair DEM, ALOS World 3D, and TanDEM-X have been analyzed. The higher-resolution datasets include 12 m TanDEM-X, 10 m single-CoSSC TerraSAR-X/TanDEM-X DEMs, and 5 m ALOS World 3D. These DEMs are state of the art for optical (ASTER and ALOS) and radar (SRTM-C and TanDEM-X) spaceborne sensors. We assessed vertical accuracy by comparing standard deviations of the DEM elevation versus 307 509 differential GPS measurements across 4000 m of elevation. For the 30 m DEMs, the ASTER datasets had the highest vertical standard deviation at > 6.5 m, whereas the SRTM-C, ALOS World 3D, and TanDEM-X were all < 3.5 m. Higher-resolution DEMs generally had lower uncertainty, with both the 12 m TanDEM-X and 5 m ALOS World 3D having < 2 m vertical standard deviation. Analysis of vertical uncertainty with respect to terrain elevation, slope, and aspect revealed the low uncertainty across these attributes for SRTM-C (30 m), TanDEM-X (12–30 m), and ALOS World 3D (5–30 m). Single-CoSSC TerraSAR-X/TanDEM-X 10 m DEMs and the 30 m ASTER GDEM2 displayed slight aspect biases, which were removed in their stacked counterparts (TanDEM-X and ASTER Stack). Based on low vertical standard deviations and visual inspection alongside optical satellite data, we selected the 30 m SRTM-C, 12–30 m TanDEM-X, 10 m single-CoSSC TerraSAR-X/TanDEM-X, and 5 m ALOS World 3D for geomorphic metric comparison in a 66 km2 catchment with a distinct river knickpoint. Consistent m∕n values were found using chi plot channel profile analysis, regardless of DEM type and spatial resolution. Slope, curvature, and drainage area were calculated and plotting schemes were used to assess basin-wide differences in the hillslope-to-valley transition related to the knickpoint. While slope and hillslope length measurements vary little between datasets, curvature displays higher magnitude measurements with fining resolution. This is especially true for the optical 5 m ALOS World 3D DEM, which demonstrated high-frequency noise in 2–8 pixel steps through a Fourier frequency analysis. The improvements in accurate space-radar DEMs (e.g., TanDEM-X) for geomorphometry are promising, but airborne or terrestrial data are still necessary for meter-scale analysis.

Highlights

Digital elevation models (DEMs) provide hydrologists and geomorphologists with powerful tools to explore the linkages between fundamental geomorphic processes and landforms
The improvement in quality through weighted stacking of ASTER L1A stereopair digital elevation models (DEMs) versus the low-quality ASTER GDEM2 is apparent in the reduction of the standard deviation (SD) from 11.42 m for a single L1A DEM to 6.93 m for the stack, uncertainty distributions for all ASTER DEMs extend beyond the ±30 m outlier cutoff (Fig. 3b)
The wider, doublepeaked vertical uncertainty distributions for the 6 November 2012 and 25 August 2013 Co-registered Single Look Slant Range Complex (CoSSC) TDX DEMs are caused by their coverage over variable terrain east of the Salar de Pocitos, where accurate DEM generation is complicated by radar shadowing and layover in steeper topography

Summary

Introduction

Digital elevation models (DEMs) provide hydrologists and geomorphologists with powerful tools to explore the linkages between fundamental geomorphic processes and landforms. Modern geomorphologists use the quantitative subdiscipline of geomorphometry (Pike et al, 2009; Wilson, 2012; Sofia et al, 2016) to explore how tectonic, climatic, and lithologic signals can be inferred from DEMs (e.g., Snyder et al, 2000; Wobus et al, 2006; DiBiase et al, 2010; Bookhagen and Strecker, 2012; Kirby and Whipple, 2012; Scherler et al, 2015; Clubb et al, 2016; Olen et al, 2016), but questions remain to what extent transient responses can be recorded in landscape morphology (e.g., DiBiase et al, 2012) and how channel networks and hillslopes can independently act as records of basin transience (e.g., Ouimet et al, 2009; Hurst et al, 2012; Clubb et al, 2016; Forte et al, 2016) Such studies rely on accurate DEMs for the calculation of geomorphic metrics (e.g., slope and curvature) and extraction of geomorphic features (e.g., channels, hillslopes, hilltops). This problem is especially acute given that relatively small elevation errors will propagate and grow in the first (slope) and second (curvature) derivatives, potentially obscuring geomorphometric results (e.g., Wechsler, 2007)

Results

Discussion

Conclusion