Beyond Vertical Point Accuracy: Assessing Inter-pixel Consistency in 30 m Global DEMs for the Arid Central Andes

Abstract

Quantitative geomorphic research depends on accurate topographic data often collected via remote sensing. Lidar, and photogrammetric methods like structure-from-motion, provide the highest quality data for generating digital elevation models (DEMs). Unfortunately, these data are restricted to relatively small areas, and may be expensive or time-consuming to collect. Global and near-global DEMs with 1 arcsec (∼30 m) ground sampling from spaceborne radar and optical sensors offer an alternative gridded, continuous surface at the cost of resolution and accuracy. Accuracy is typically defined with respect to external datasets, often, but not always, in the form of point or profile measurements from sources like differential Global Navigation Satellite System (GNSS), spaceborne lidar (e.g., ICESat), and other geodetic measurements. Vertical point or profile accuracy metrics can miss the pixel-to-pixel variability (sometimes called DEM noise) that is unrelated to true topographic signal, but rather sensor-, orbital-, and/or processing-related artifacts. This is most concerning in selecting a DEM for geomorphic analysis, as this variability can affect derivatives of elevation (e.g., slope and curvature) and impact flow routing. We use (near) global DEMs at 1 arcsec resolution (SRTM, ASTER, ALOS, TanDEM-X, and the recently released Copernicus) and develop new internal accuracy metrics to assess inter-pixel variability without reference data. Our study area is in the arid, steep Central Andes, and is nearly vegetation-free, creating ideal conditions for remote sensing of the bare-earth surface. We use a novel hillshade-filtering approach to detrend long-wavelength topographic signals and accentuate short-wavelength variability. Fourier transformations of the spatial signal to the frequency domain allows us to quantify: 1) artifacts in the un-projected 1 arcsec DEMs at wavelengths greater than the Nyquist (twice the nominal resolution, so > 2 arcsec); and 2) the relative variance of adjacent pixels in DEMs resampled to 30-m resolution (UTM projected). We translate results into their impact on hillslope and channel slope calculations, and we highlight the quality of the five DEMs. We find that the Copernicus DEM, which is based on a carefully edited commercial version of the TanDEM-X, provides the highest quality landscape representation, and should become the preferred DEM for topographic analysis in areas without sufficient coverage of higher-quality local DEMs.

Avaliação da altimetria do MDE COP-30 no Centro-Oeste do Brasil

“…Alguns trabalhos têm se preocupado em avaliar as formas de relevo, derivações geomorfométricas (e.g. declividade e orientação de vertentes), rede de drenagem e consistência inter-pixel obtidas pelo MDE e não apenas a acurácia vertical do dado (POLIDORI; EL HAGE; VALERIANO, 2014; TOLENTINO, SILVA, SANTIL, 2017; MOZAS-CALVACHE, UREÑA-CÁMARA; ARIZA-LÓPEZ, 2017;ALBA-FERNÁNDEZ, 2021;PURINTON;BOOKHAGEN (2021). Nesse sentido, estudos complementares podem ser explorados para avaliar a qualidade das derivações possíveis de se extrair com o COP-30.…”

DEMIX Wine Contest Method Ranks ALOS AW3D30, COPDEM, and FABDEM as Top 1'' Global DEMs

“…In contrast, some studies such as Gesch (2018) and Hawker et al (2022), focused their analysis primarily on coastal or floodplain terrain which probably accounts for our finding that FABDEM often ranked lower than the COPDEM from which it was derived. At the other elevation extreme in mountain areas, Purinton and Bookhagen (2021) preferred COPDEM while Florinsky et al (2019) and Trevisani et al (2022) found that relative performances between COP and ALOS change according to local morphology, with ALOS slightly better in steep slopes. None of those works provide a confidence level for their conclusions.…”

“…Created reference DEMs to consider the half pixel offset between ALOS and COPDEM (and the other lower quality DEMs) for the inter-comparison, a consequence of the decision not to resample candidate DEMs. This issue is generally not discussed in the literature (or addressed by interpolation) although Purinton and Bookhagen (2021) designed their comparisons to avoid the need for DEM co-registration.…”

A new inventory of High Mountain Asia surge-type glaciers derived from multiple elevation datasets since the 1970s

“…The global RMSE of COP30 DEM is ±1.68 m (AIRBUS, 2020). Several studies have pointed out that this DEM is the most reliable open-access DEM to date (Purinton and Bookhagen, 2021;Guth and Geoffroy, 2021). The source images of COP30 DEM were mostly acquired between 2011 and 2014, and therefore COP30 DEM is suitable to represent the surface elevation in the 2010s.…”