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Volume change data is critical to the understanding of glacier response to climate change. The Advanced Spaceborne Thermal Emission\udand Reflection Radiometer (ASTER) system embarked on the Terra (EOS AM-1) satellite has been a unique source of systematic\udstereoscopic images covering the whole globe at 15m resolution and at a consistent quality for over 15 years. While satellite stereo\udsensors with significantly improved radiometric and spatial resolution are available to date, the potential of ASTER data lies in its long\udconsistent time series that is unrivaled, though not fully exploited for change analysis due to lack of data accuracy and precision. Here,\udwe developed an improved method for ASTER DEM generation and implemented it in the open source photogrammetric library and\udsoftware suite MicMac. The method relies on the computation of a rational polynomial coefficients (RPC) model and the detection\udand correction of cross-track sensor jitter in order to compute DEMs. ASTER data are strongly affected by attitude jitter, mainly of\udapproximately 4 km and 30 km wavelength, and improving the generation of ASTER DEMs requires removal of this effect. Our sensor\udmodeling does not require ground control points and allows thus potentially for the automatic processing of large data volumes.\ud  \udAs a proof of concept, we chose a set of glaciers with reference DEMs available to assess the quality of our measurements. We use time\udseries of ASTER scenes from which we extracted DEMs with a ground sampling distance of 15m. Our method directly measures and\udaccounts for the cross-track component of jitter so that the resulting DEMs are not contaminated by this process. Since the along-track\udcomponent of jitter has the same direction as the stereo parallaxes, the two cannot be separated and the elevations extracted are thus\udcontaminated by along-track jitter. Initial tests reveal no clear relation between the cross-track and along-track components so that the\udlatter seems not to be easily modeled analytically from the first one. We thus remove the remaining along-track jitter effects in the\udDEMs statistically through temporal DEM stacks to finally compute the glacier volume changes over time. Our method yields cleaner\udand spatially more complete elevation data, which also proved to be more in accordance to reference DEMs, compared to NASA’s\udAST14DMO DEM standard products.\ud  \udThe quality of the demonstrated measurements promises to further unlock the underused potential of ASTER DEMs for glacier volume\udchange time series on a global scale. The data produced by our method will help to better understand the response of glaciers to climate\udchange and their influence on runoff and sea level

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

GLACIER VOLUME CHANGE ESTIMATION USING TIME SERIES OF IMPROVED ASTER DEMS