期刊
GISCIENCE & REMOTE SENSING
卷 52, 期 2, 页码 198-217出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/15481603.2015.1008621
关键词
DEM; WorldView; glaciated regions; stereo-photogrammetric; RPCs
资金
- US National Aeronautics and Space Agency [NNX10AN61G]
- Ohio Supercomputing Center
Digital elevation models (DEMs) are critical to a wide range of geoscience investigations. High-latitude and polar regions are particularly challenging for automated, stereo-photogrammetric DEM extraction due to the abundance of surfaces that are low-contrast and repetitively textured, such as snow and shadowed terrain, and have discontinuities such as in crevasse fields, glacier calving faces or iceberg edges. Sub-meter, stereo-mode satellite imagery of high geometric and radiometric quality is becoming increasingly accessible, offering the potential for dramatically increasing the spatial coverage and quality of high-latitude DEMs. Here we demonstrate and validate automated DEMs generated from the Surface Extraction with Triangulated Irregular Network-based Search-space Minimization (SETSM) algorithm designed for these challenging terrains using only the satellite rational polynomial coefficients (RPCs). Comparison between 2-m DEMs created from WorldView image pairs and low-altitude LiDAR point clouds in west Greenland give DEM biases of less than 5m, which is the maximum systematic RPC error. Co-registration with the LiDAR data reduces the DEM RMS error to ~20cm, which is comparable to the uncertainty of the LiDAR data. We demonstrate SETSM's automatic RPC refinement and bias reduction by successfully extracting a high-quality DEM from Pleiades stereo pair images with large RPC errors. Finally, we provide examples of SETSM DEMs that demonstrate their utility for a range of applications of interest to polar scientists.
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