TanDEM-X elevation data for mass balance estimation - Abdullahi, Sahra; Burgess, David; Wessel, Birgit; Roth, Achim (2023)
Ongoing global warming leads to dramatic changes in the cryosphere. In view of these rapid changes as well as the large uncertainties regarding forecasts, there is a constantly growing need for reliable and consistent information on the current state and the evolution of the ice sheets, ice caps and glaciers worldwide. In this context, satellite-based remote sensing allows cost-effective data collection even for inaccessible areas. Radar altimetry, gravimetry and laser altimetry have been widely used to detect height and mass changes. However, these systems either offer only point-based measurements or acquire at low spatial resolution. Since 2010, the single-pass SAR (Synthetic Aperture Radar) interferometry mission TanDEM-X provides area-wide information with high spatial resolution of 0.4 arcsec (i.e. about 12 m) at a global scale. The huge amount of globally consistent elevation data could contribute to meet the urgent need for information with high spatial resolution to monitor the dynamics of the cryosphere. However, the data suffers from an elevation bias up to several meters due to signal penetration. The penetration bias mainly depends on snow and ice characteristics as well as on the continuously changing acquisition geometry and underlies inter- and intra-annual variations. In this regard, we quantify the impact of X-band InSAR penetration bias on mass balance estimation based on TanDEM-X digital elevation models (DEM). In detail, a multiple regression model based on interferometric coherence and backscatter intensity is used to correct a time series of TanDEM-X DEMs acquired between 2010 and 2018 over the Devon Ice Cap (Nunavut, Canada), from which changes in elevation and mass are derived. For validation, GPS and laser altimeter measurements are used, which show good agreement between predictions and observations, with mean deviations between 0.01 and 0.20 m. The predictions well reflect the inter- and intra-annual variations, with a mean penetration bias varying between 2.44 and 3.40 m. Regarding ...