Abstract
The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) system on board the Terra (EOS AM-1) satellite has been a source of stereoscopic images covering the whole globe at 15-m resolution with consistent quality for over 16 years. The potential of these data in terms of geomorphological analysis and change detection in three dimensions is unrivaled and should be exploited more. Due to uncorrected errors in the image geometry due to sensor motion (“jitter”), however, the quality of the DEMs and orthoimages currently available is often insufficient for a number of applications, including surface change detection. We have therefore developed a series of algorithms packaged under the name MicMac ASTER (MMASTER). It is composed of a tool to compute Rational Polynomial Coefficient (RPC) models from the ASTER metadata, a method that improves the quality of the matching by identifying and correcting jitter-induced cross-track parallax errors and a correction for along-track jitter when computing differences between DEMs (either with another MMASTER DEM or with another data source). Our method outputs more precise DEMs with less unmatched areas and reduced overall noise compared to NASA’s standard AST14DMO product. The algorithms were implemented in the open source photogrammetric library and software suite MicMac. Here, we briefly examine the potential of MMASTER-produced DEMs to investigate a variety of geomorphological changes, including river erosion, seismic deformation, changes in biomass, volcanic deformation and glacier mass balance.
Highlights
The analysis of the change of the Earth’s surface relies on time series of DEMs, which in turn rely on the high quality acquisition and processing of data
We have developed MicMac ASTER (MMASTER), a DEM processing tool that does not rely on external data sources, takes into account and corrects the jitter and improves the quality and completeness of ASTER DEMs compared to the data included in the AST14DMO product
We show that it is possible to fit corrections to the bias observed on stable ground and produce MMASTER dDEMs that are suitable to survey glacier elevation change with an accuracy better than ±10 m, whereas it proved challenging to obtain good data with the DMO products
Summary
The analysis of the change of the Earth’s surface relies on time series of DEMs, which in turn rely on the high quality acquisition and processing of data. For more than 17 years, pairs of stereo images were collected by ASTER globally at a 15-m resolution in the near infra-red band, making its data the largest consistent multi-temporal dataset of stereo images available worldwide. The pairs consist of a nadir-pointing image (Band 3N) and a back-looking image (Band 3B) with an effective 30.6◦ parallax angle. The data are plagued with a high frequency satellite jitter that induces an attitude perturbation.
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