Abstract
Abstract. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) system embarked on the Terra (EOS AM-1) satellite has been a source of stereoscopic images covering the whole globe at a 15m resolution at a consistent quality for over 15 years. The potential of this data in terms of geomorphological analysis and change detection in three dimensions is unrivaled and needs to be exploited. However, the quality of the DEMs and ortho-images currently delivered by NASA (ASTER DMO products) is often of insufficient quality for a number of applications such as mountain glacier mass balance. For this study, the use of Ground Control Points (GCPs) or of other ground truth was rejected due to the global “big data” type of processing that we hope to perform on the ASTER archive. We have therefore developed a tool to compute Rational Polynomial Coefficient (RPC) models from the ASTER metadata and a method improving the quality of the matching by identifying and correcting jitter induced cross-track parallax errors. Our method outputs more accurate DEMs with less unmatched areas and reduced overall noise. The algorithms were implemented in the open source photogrammetric library and software suite MicMac.
Highlights
1.1 MotivationThe Terra (EOS AM-1) satellite was launched in December 1999 on a Sun-synchronous orbit
For more than 15 years, pairs of stereo images were collected by ASTER globally at a 15m resolution in the near infrared band, making its data the largest consistent multi-temporal dataset of stereo images available worldwide
Even if the existence of such raw data is a great starting point, DEMs generated by NASA with SilcAst [SILC, 2015] (ASTER DMO products) do not provide a sufficient geometric quality for glacier volume change estimation over short periods, the expected change being significantly smaller than the accuracy of the product (a few meters against ±30m, see Figure 2 of the DMO over a sea ice scene)
Summary
1.1 MotivationThe Terra (EOS AM-1) satellite was launched in December 1999 on a Sun-synchronous orbit. Even if the existence of such raw data is a great starting point, DEMs generated by NASA with SilcAst [SILC, 2015] (ASTER DMO products) do not provide a sufficient geometric quality for glacier volume change estimation over short periods, the expected change being significantly smaller than the accuracy of the product (a few meters against ±30m, see Figure 2 of the DMO over a sea ice (flat) scene). This is due to high frequency satellite jitter inducing attitude perturbation. Proposed causes for this disturbance include the mechanical cooling system, the rotation of mirrors and movements of the high gain antenna, but a source is yet to be formally identified
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