Annual 30 m land cover dataset on the Tibetan Plateau from 1990 to 2023
Abstract Accurate land cover data was fundamental for formulating sound land planning and sustainable development strategies. This study focused on the Tibetan Plateau (TP), a globally sensitive ecological area, and developed a locally tailored annual 30 m resolution land cover dataset from 1990 to...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-03-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-04759-6 |
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| author | Siya Li Quansheng Ge Fubao Sun Qiulei Ji Wenbin Liu Ronggao Liu Duanyang Xu Zexing Tao |
| author_facet | Siya Li Quansheng Ge Fubao Sun Qiulei Ji Wenbin Liu Ronggao Liu Duanyang Xu Zexing Tao |
| author_sort | Siya Li |
| collection | DOAJ |
| description | Abstract Accurate land cover data was fundamental for formulating sound land planning and sustainable development strategies. This study focused on the Tibetan Plateau (TP), a globally sensitive ecological area, and developed a locally tailored annual 30 m resolution land cover dataset from 1990 to 2023 (TPLCD). Leveraging the Google Earth Engine (GEE) platform for Landsat data processing, LandTrendr was employed to generate robust, high-precision training samples. Subsequently, random forest classification and spatiotemporal smoothing strategies were applied to precisely map the land cover dynamics of the TP. Rigorous validation through visual interpretation, authoritative third-party datasets (Geo-Wiki and GLCVSS), and thematic dataset cross-comparisons, revealed an overall accuracy of 84.8%, and a Kappa coefficient of 0.78, fully affirming the dataset’s high reliability. This dataset provided invaluable empirical evidence for understanding the vulnerability and adaptability of the TP’s ecosystem. |
| format | Article |
| id | doaj-art-8226eb2b8fd94db3b1d1bf9688b4f024 |
| institution | DOAJ |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-8226eb2b8fd94db3b1d1bf9688b4f0242025-08-20T02:49:29ZengNature PortfolioScientific Data2052-44632025-03-0112111510.1038/s41597-025-04759-6Annual 30 m land cover dataset on the Tibetan Plateau from 1990 to 2023Siya Li0Quansheng Ge1Fubao Sun2Qiulei Ji3Wenbin Liu4Ronggao Liu5Duanyang Xu6Zexing Tao7Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of SciencesKey Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of SciencesUniversity of Chinese Academy of SciencesUniversity of Chinese Academy of SciencesUniversity of Chinese Academy of SciencesUniversity of Chinese Academy of SciencesKey Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of SciencesKey Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of SciencesAbstract Accurate land cover data was fundamental for formulating sound land planning and sustainable development strategies. This study focused on the Tibetan Plateau (TP), a globally sensitive ecological area, and developed a locally tailored annual 30 m resolution land cover dataset from 1990 to 2023 (TPLCD). Leveraging the Google Earth Engine (GEE) platform for Landsat data processing, LandTrendr was employed to generate robust, high-precision training samples. Subsequently, random forest classification and spatiotemporal smoothing strategies were applied to precisely map the land cover dynamics of the TP. Rigorous validation through visual interpretation, authoritative third-party datasets (Geo-Wiki and GLCVSS), and thematic dataset cross-comparisons, revealed an overall accuracy of 84.8%, and a Kappa coefficient of 0.78, fully affirming the dataset’s high reliability. This dataset provided invaluable empirical evidence for understanding the vulnerability and adaptability of the TP’s ecosystem.https://doi.org/10.1038/s41597-025-04759-6 |
| spellingShingle | Siya Li Quansheng Ge Fubao Sun Qiulei Ji Wenbin Liu Ronggao Liu Duanyang Xu Zexing Tao Annual 30 m land cover dataset on the Tibetan Plateau from 1990 to 2023 Scientific Data |
| title | Annual 30 m land cover dataset on the Tibetan Plateau from 1990 to 2023 |
| title_full | Annual 30 m land cover dataset on the Tibetan Plateau from 1990 to 2023 |
| title_fullStr | Annual 30 m land cover dataset on the Tibetan Plateau from 1990 to 2023 |
| title_full_unstemmed | Annual 30 m land cover dataset on the Tibetan Plateau from 1990 to 2023 |
| title_short | Annual 30 m land cover dataset on the Tibetan Plateau from 1990 to 2023 |
| title_sort | annual 30 m land cover dataset on the tibetan plateau from 1990 to 2023 |
| url | https://doi.org/10.1038/s41597-025-04759-6 |
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