Identification of common error signatures in global digital elevation models based on satellite altimeter reference data |
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| Institution: | 1. Julie Ann Wrigley Global Institute of Sustainability, Arizona State University, Tempe, AZ 85287-5402, United States;2. School of Geographical Sciences & Urban Planning, Arizona State University, Tempe, AZ 85287-5302, United States;3. Department of Health Sciences and Department of Sociology, Northeastern University, Boston, Massachusetts, 02115, United States;4. School of Sustainability, Arizona State University, Tempe, AZ 85287-5502, United States;1. School of Resources and Environmental Engineering, Anhui University, Hefei, China;2. School of Resource and Environmental Sciences, Wuhan University, Wuhan, China;3. The State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China;4. Institute of Meteorology and Climate Research (IMK), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany;1. Ecological Process and Reconstruction Research Center of the Three Gorges Ecological Environment, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, No. 266 Fangzheng Avenue, Shuitu Hi-tech Industrial Park, Shuitu Town, Beibei District, Chongqing 400714, China;2. University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing 100049, China |
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| Abstract: | The generation of a near-global set of orthometric height data derived from satellite altimetry has allowed for the first time an independent evaluation of the accuracy of existing Global Digital Elevation Models (GDEMs) on a near-global scale. This paper presents results from an intercomparison of GLOBE v1, GLOBE β and JGP95E with altimeter based datasets derived from the ERS-1 geodetic mission, together with ERS-1 and ERS-2 35 day data.One result of this research is the identification of common error signatures, where correlated height differences are seen to exist between the altimeter data and several of the DEMs. The ability to identify such erroneous ground truth data using altimetry facilitates the improvement of these global and regional models. Having targetted regions where the height data are inaccurate, it enables examination of these data for mis-registration and reference datum errors, which can then be corrected using altimetry derived heights. |
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