{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T16:29:58Z","timestamp":1775579398960,"version":"3.50.1"},"reference-count":49,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2023,9,12]],"date-time":"2023-09-12T00:00:00Z","timestamp":1694476800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"2023 Postgraduate Research and Innovation Program in Jiangsu Province, China","award":["KYCX23_1291"],"award-info":[{"award-number":["KYCX23_1291"]}]},{"name":"2023 Postgraduate Research and Innovation Program in Jiangsu Province, China","award":["2022AH010066"],"award-info":[{"award-number":["2022AH010066"]}]},{"name":"2023 Postgraduate Research and Innovation Program in Jiangsu Province, China","award":["KJ2021ZD0130"],"award-info":[{"award-number":["KJ2021ZD0130"]}]},{"name":"2023 Postgraduate Research and Innovation Program in Jiangsu Province, China","award":["2018H191"],"award-info":[{"award-number":["2018H191"]}]},{"name":"Research and innovation team of Physical geography environment in Anhui Province, China","award":["KYCX23_1291"],"award-info":[{"award-number":["KYCX23_1291"]}]},{"name":"Research and innovation team of Physical geography environment in Anhui Province, China","award":["2022AH010066"],"award-info":[{"award-number":["2022AH010066"]}]},{"name":"Research and innovation team of Physical geography environment in Anhui Province, China","award":["KJ2021ZD0130"],"award-info":[{"award-number":["KJ2021ZD0130"]}]},{"name":"Research and innovation team of Physical geography environment in Anhui Province, China","award":["2018H191"],"award-info":[{"award-number":["2018H191"]}]},{"name":"Research on key technologies and demonstration application of rural digital twin holography physical geography 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2022\u20132023","award":["2022AH010066"],"award-info":[{"award-number":["2022AH010066"]}]},{"name":"natural science research project in Anhui Province, China, 2022\u20132023","award":["KJ2021ZD0130"],"award-info":[{"award-number":["KJ2021ZD0130"]}]},{"name":"natural science research project in Anhui Province, China, 2022\u20132023","award":["2018H191"],"award-info":[{"award-number":["2018H191"]}]},{"name":"physical geography environment intelligent technology industry innovation, Chuzhou \u201c113\u201d industry innovation team, 2022\u20132023","award":["KYCX23_1291"],"award-info":[{"award-number":["KYCX23_1291"]}]},{"name":"physical geography environment intelligent technology industry innovation, Chuzhou \u201c113\u201d industry innovation team, 2022\u20132023","award":["2022AH010066"],"award-info":[{"award-number":["2022AH010066"]}]},{"name":"physical geography environment intelligent technology industry innovation, Chuzhou \u201c113\u201d industry innovation team, 2022\u20132023","award":["KJ2021ZD0130"],"award-info":[{"award-number":["KJ2021ZD0130"]}]},{"name":"physical geography environment intelligent technology industry innovation, Chuzhou \u201c113\u201d industry innovation team, 2022\u20132023","award":["2018H191"],"award-info":[{"award-number":["2018H191"]}]},{"name":"Anhui province academic and technical leader candidate research funding project in 2018","award":["KYCX23_1291"],"award-info":[{"award-number":["KYCX23_1291"]}]},{"name":"Anhui province academic and technical leader candidate research funding project in 2018","award":["2022AH010066"],"award-info":[{"award-number":["2022AH010066"]}]},{"name":"Anhui province academic and technical leader candidate research funding project in 2018","award":["KJ2021ZD0130"],"award-info":[{"award-number":["KJ2021ZD0130"]}]},{"name":"Anhui province academic and technical leader candidate research funding project in 2018","award":["2018H191"],"award-info":[{"award-number":["2018H191"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The topographic skeleton is the primary expression and intuitive understanding of topographic relief. This study integrated a topographic skeleton into deep learning for terrain reconstruction. Firstly, a topographic skeleton, such as valley, ridge, and gully lines, was extracted from a global digital elevation model (GDEM) and Google Earth Image (GEI). Then, the Conditional Generative Adversarial Network (CGAN) was used to learn the elevation sequence information between the topographic skeleton and high-precision 5 m DEMs. Thirdly, different combinations of topographic skeletons extracted from 5 m, 12.5 m, and 30 m DEMs and a 1 m GEI were compared for reconstructing 5 m DEMs. The results show the following: (1) from the perspective of the visual effect, the 5 m DEMs generated with the three combinations (5 m DEM + 1 m GEI, 12.5 m DEM + 1 m GEI, and 30 m DEM + 1 m GEI) were all similar to the original 5 m DEM (reference data), which provides a markedly increased level of terrain detail information when compared to the traditional interpolation methods; (2) from the perspective of elevation accuracy, the 5 m DEMs reconstructed by the three combinations have a high correlation (&gt;0.9) with the reference data, while the vertical accuracy of the 12.5 m DEM + 1 m GEI combination is obviously higher than that of the 30 m DEM + 1 m GEI combination; and (3) from the perspective of topographic factors, the distribution trends of the reconstructed 5 m DEMs are all close to the reference data in terms of the extracted slope and aspect. This study enhances the quality of open-source DEMs and introduces innovative ideas for producing high-precision DEMs. Among the three combinations, we recommend the 12.5 m DEM + 1 m GEI combination for DEM reconstruction due to its relative high accuracy and open access. In regions where a field survey of high-precision DEMs is difficult, open-source DEMs combined with GEI can be used in high-precision DEM reconstruction.<\/jats:p>","DOI":"10.3390\/rs15184490","type":"journal-article","created":{"date-parts":[[2023,9,12]],"date-time":"2023-09-12T21:41:12Z","timestamp":1694554872000},"page":"4490","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Integrating Topographic Skeleton into Deep Learning for Terrain Reconstruction from GDEM and Google Earth Image"],"prefix":"10.3390","volume":"15","author":[{"given":"Kai","family":"Chen","sequence":"first","affiliation":[{"name":"School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China"},{"name":"Key Laboratory of Physical Geographic Information in Anhui Province, Chuzhou 239000, China"}]},{"given":"Chun","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Physical Geographic Information in Anhui Province, Chuzhou 239000, China"},{"name":"School of Geographic Information and Tourism, Chuzhou University, Chuzhou 239000, China"}]},{"given":"Mingyue","family":"Lu","sequence":"additional","affiliation":[{"name":"School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7424-644X","authenticated-orcid":false,"given":"Wen","family":"Dai","sequence":"additional","affiliation":[{"name":"School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China"}]},{"given":"Jiaxin","family":"Fan","sequence":"additional","affiliation":[{"name":"School of Remote Sensing & Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-3031-0415","authenticated-orcid":false,"given":"Mengqi","family":"Li","sequence":"additional","affiliation":[{"name":"School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4138-0850","authenticated-orcid":false,"given":"Shaohua","family":"Lei","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing 210029, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,9,12]]},"reference":[{"key":"ref_1","first-page":"870","article-title":"Effects of different DEM spatial interpolation methods on soil erosion simulation: A case study of a typical gully of dry-hot valley based on USPED","volume":"35","author":"Xu","year":"2016","journal-title":"Prog. 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