Global digital elevation model (GDEM) product generation by correcting ASTER GDEM elevation with ICESat-2 altimeter data
<p>Advancements in scientific inquiry and practical applications have created a higher demand for the accuracy of global digital elevation models (GDEMs), especially for GDEMs whose main data source is optical imagery. To address this challenge, integrating GDEM and satellite laser altimeter d...
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Copernicus Publications
2025-01-01
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| Series: | Earth System Science Data |
| Online Access: | https://essd.copernicus.org/articles/17/205/2025/essd-17-205-2025.pdf |
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| author | B. Li B. Li B. Li B. Li H. Xie H. Xie S. Liu Z. Ye Z. Hong Q. Weng Q. Weng Q. Weng Y. Sun Q. Xu X. Tong |
| author_facet | B. Li B. Li B. Li B. Li H. Xie H. Xie S. Liu Z. Ye Z. Hong Q. Weng Q. Weng Q. Weng Y. Sun Q. Xu X. Tong |
| author_sort | B. Li |
| collection | DOAJ |
| description | <p>Advancements in scientific inquiry and practical applications have created a higher demand for the accuracy of global digital elevation models (GDEMs), especially for GDEMs whose main data source is optical imagery. To address this challenge, integrating GDEM and satellite laser altimeter data (global coverage and high-accuracy ranging) is an important research direction, in addition to the technological enhancement of the main data source. In this paper, we describe the datasets and algorithms used to generate a GDEM product (IC2-GDEM) by correcting ASTER GDEM (Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model) elevation data with ICESat-2 altimeter data. The algorithm scheme presents the details of the strategies used for the various challenges, such as the processing of DEM boundaries, the fusion of the different data, and the geographical layout of the satellite laser altimeter data. We used a high-accuracy global elevation control point dataset and multiple high-accuracy local DEMs as the validation data for a comprehensive assessment at the global scale. The results from the validation comparison show that the elevation accuracy of IC2-GDEM is evidently superior to that of the ASTER GDEM product: (1) the RMSE reduction ratio of the corrected GDEM elevation is between 16 % and 82 %, and the average reduction ratio is about 47 %; and (2) from the analysis of the different topographies and land covers, this error reduction is effective even in areas with high topographic relief (<span class="inline-formula">>15<i>°</i></span>) and high vegetation cover (<span class="inline-formula">>60 %</span>). ASTER GDEM has been in use for more than a decade, and many historical datasets and models are based on its elevation data. IC2-GDEM facilitates seamless integration with these historical datasets, which is essential for longitudinal studies examining long-term environmental change, land use dynamics, and climate impacts. Meanwhile, IC2-GDEM can serve as a new complementary data source for existing DEMs (such as Copernicus DEM) mainly sourced from synthetic aperture radar (SAR) observation. By cross-validating qualities, filling data gaps, and conducting multi-scale analyses, it can lead to more reliable and comprehensive scientific discoveries, thereby improving the overall quality and reliability of Earth science research. The IC2-GDEM product is openly available at <a href="https://doi.org/10.11888/RemoteSen.tpdc.301229">https://doi.org/10.11888/RemoteSen.tpdc.301229</a> (Xie et al., 2024).</p> |
| format | Article |
| id | doaj-art-f9d8c66c351941b1855d7a575ee89067 |
| institution | Kabale University |
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| publishDate | 2025-01-01 |
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| spelling | doaj-art-f9d8c66c351941b1855d7a575ee890672025-01-24T10:53:10ZengCopernicus PublicationsEarth System Science Data1866-35081866-35162025-01-011720522010.5194/essd-17-205-2025Global digital elevation model (GDEM) product generation by correcting ASTER GDEM elevation with ICESat-2 altimeter dataB. Li0B. Li1B. Li2B. Li3H. Xie4H. Xie5S. Liu6Z. Ye7Z. Hong8Q. Weng9Q. Weng10Q. Weng11Y. Sun12Q. Xu13X. Tong14College of Surveying and Geo-informatics, and Shanghai Key Laboratory for Planetary Mapping and Remote Sensing for Deep Space Exploration, Tongji University, Shanghai 200092, ChinaJC STEM Lab of Earth Observations, Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR 999077, ChinaResearch Centre for Artificial Intelligence in Geomatics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR 999077, ChinaResearch Institute for Land and Space, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR 999077, ChinaCollege of Surveying and Geo-informatics, and Shanghai Key Laboratory for Planetary Mapping and Remote Sensing for Deep Space Exploration, Tongji University, Shanghai 200092, ChinaShanghai Institute of Intelligent Science and Technology, Tongji University, Shanghai 200092, ChinaCollege of Surveying and Geo-informatics, and Shanghai Key Laboratory for Planetary Mapping and Remote Sensing for Deep Space Exploration, Tongji University, Shanghai 200092, ChinaCollege of Surveying and Geo-informatics, and Shanghai Key Laboratory for Planetary Mapping and Remote Sensing for Deep Space Exploration, Tongji University, Shanghai 200092, ChinaCollege of Information Technology, Shanghai Ocean University, Shanghai 201306, ChinaJC STEM Lab of Earth Observations, Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR 999077, ChinaResearch Centre for Artificial Intelligence in Geomatics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR 999077, ChinaResearch Institute for Land and Space, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR 999077, ChinaCollege of Surveying and Geo-informatics, and Shanghai Key Laboratory for Planetary Mapping and Remote Sensing for Deep Space Exploration, Tongji University, Shanghai 200092, ChinaCollege of Surveying and Geo-informatics, and Shanghai Key Laboratory for Planetary Mapping and Remote Sensing for Deep Space Exploration, Tongji University, Shanghai 200092, ChinaCollege of Surveying and Geo-informatics, and Shanghai Key Laboratory for Planetary Mapping and Remote Sensing for Deep Space Exploration, Tongji University, Shanghai 200092, China<p>Advancements in scientific inquiry and practical applications have created a higher demand for the accuracy of global digital elevation models (GDEMs), especially for GDEMs whose main data source is optical imagery. To address this challenge, integrating GDEM and satellite laser altimeter data (global coverage and high-accuracy ranging) is an important research direction, in addition to the technological enhancement of the main data source. In this paper, we describe the datasets and algorithms used to generate a GDEM product (IC2-GDEM) by correcting ASTER GDEM (Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model) elevation data with ICESat-2 altimeter data. The algorithm scheme presents the details of the strategies used for the various challenges, such as the processing of DEM boundaries, the fusion of the different data, and the geographical layout of the satellite laser altimeter data. We used a high-accuracy global elevation control point dataset and multiple high-accuracy local DEMs as the validation data for a comprehensive assessment at the global scale. The results from the validation comparison show that the elevation accuracy of IC2-GDEM is evidently superior to that of the ASTER GDEM product: (1) the RMSE reduction ratio of the corrected GDEM elevation is between 16 % and 82 %, and the average reduction ratio is about 47 %; and (2) from the analysis of the different topographies and land covers, this error reduction is effective even in areas with high topographic relief (<span class="inline-formula">>15<i>°</i></span>) and high vegetation cover (<span class="inline-formula">>60 %</span>). ASTER GDEM has been in use for more than a decade, and many historical datasets and models are based on its elevation data. IC2-GDEM facilitates seamless integration with these historical datasets, which is essential for longitudinal studies examining long-term environmental change, land use dynamics, and climate impacts. Meanwhile, IC2-GDEM can serve as a new complementary data source for existing DEMs (such as Copernicus DEM) mainly sourced from synthetic aperture radar (SAR) observation. By cross-validating qualities, filling data gaps, and conducting multi-scale analyses, it can lead to more reliable and comprehensive scientific discoveries, thereby improving the overall quality and reliability of Earth science research. The IC2-GDEM product is openly available at <a href="https://doi.org/10.11888/RemoteSen.tpdc.301229">https://doi.org/10.11888/RemoteSen.tpdc.301229</a> (Xie et al., 2024).</p>https://essd.copernicus.org/articles/17/205/2025/essd-17-205-2025.pdf |
| spellingShingle | B. Li B. Li B. Li B. Li H. Xie H. Xie S. Liu Z. Ye Z. Hong Q. Weng Q. Weng Q. Weng Y. Sun Q. Xu X. Tong Global digital elevation model (GDEM) product generation by correcting ASTER GDEM elevation with ICESat-2 altimeter data Earth System Science Data |
| title | Global digital elevation model (GDEM) product generation by correcting ASTER GDEM elevation with ICESat-2 altimeter data |
| title_full | Global digital elevation model (GDEM) product generation by correcting ASTER GDEM elevation with ICESat-2 altimeter data |
| title_fullStr | Global digital elevation model (GDEM) product generation by correcting ASTER GDEM elevation with ICESat-2 altimeter data |
| title_full_unstemmed | Global digital elevation model (GDEM) product generation by correcting ASTER GDEM elevation with ICESat-2 altimeter data |
| title_short | Global digital elevation model (GDEM) product generation by correcting ASTER GDEM elevation with ICESat-2 altimeter data |
| title_sort | global digital elevation model gdem product generation by correcting aster gdem elevation with icesat 2 altimeter data |
| url | https://essd.copernicus.org/articles/17/205/2025/essd-17-205-2025.pdf |
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