Abstract ID: 28.7295 | Accepted as Talk | Talk/Oral | 2025-02-27 16:15 - 16:30 | Ágnes‐Heller‐Haus/Small Lecture Room

Glacier geodetic mass balance is generally estimated from the difference between two Digital Elevation Models (DEM) acquired at different times. Due to sensor specificities, these DEMs often have a different spatial resolution and/or different spatial sampling, which requires resampling them on a common geometry. When the difference in spatial resolution is large, systematic elevation differences appear: the coarser DEM tend to underestimate the elevation of crests or tops and overestimate the elevation of troughs or valleys. For decametric resolution DEMs like SRTM or TanDEM-X, this bias can reach several meters and has been shown to be well correlated with the terrain curvature (Paul, 2008; Gardelle et al., 2012). However, the origin and impact of this bias has been investigated on a single test DEM only and never revisited since. In this study, we investigate the sources of this bias using datasets obtained from different sensors and different spatial resolutions and propose an empirical correction. First, we create a collection of datasets from multiple sources, including virtual surfaces, drone imagery and satellite data. From each dataset, we generate elevation models at different resolution to create a controlled bias and analyze it with regard to different terrain attributes (elevation, slope, curvature, terrain position index, etc.). Additionally, we test the impact of the resampling algorithm. Our results demonstrate that this bias can be observed for all these source data and share similar characteristics. We show that the terrain position index is the best predictor of this bias and propose an algorithm to empirically correct it. In our test cases, we can reduce this bias by a factor of 10 and improve previous corrections by a factor 5. Finally, we highlight on a study case (SRTM vs Pléiades elevation difference over the Mont Blanc massif) that this correction can impact estimated mean glacier elevation change in a systematic way by more than 0.5 m. Paul, F., 2008. Calculation of glacier elevation changes with SRTM: is there an elevation-dependent bias? Journal of Glaciology 54, 945–946. https://doi.org/10.3189/002214308787779960 Gardelle, J., Berthier, E., Arnaud, Y., 2012. Impact of resolution and radar penetration on glacier elevation changes computed from DEM differencing. Journal of Glaciology 58, 419–422. https://doi.org/10.3189/2012JoG11J175