Articles | Volume 16, issue 7
https://doi.org/10.5194/essd-16-3307-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-3307-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
19 Jul 2024
Data description article |
| 19 Jul 2024
| 19 Jul 2024
A 10 m resolution land cover map of the Tibetan Plateau with detailed vegetation types
Xingyi Huang
Hubei Key Laboratory of Quantitative Remote Sensing of Land and Atmosphere, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
Yuwei Yin
Hubei Key Laboratory of Quantitative Remote Sensing of Land and Atmosphere, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
Luwei Feng
Hubei Key Laboratory of Quantitative Remote Sensing of Land and Atmosphere, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
Xiaoye Tong
Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
Xiaoxin Zhang
Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
Jiangrong Li
Institute of Tibet Plateau Ecology, Tibet Agricultural and Animal Husbandry University, Linzhi, China
Feng Tian
CORRESPONDING AUTHOR
Hubei Key Laboratory of Quantitative Remote Sensing of Land and Atmosphere, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
Perception and Effectiveness Assessment for Carbon-Neutrality Efforts, Engineering Research Center of Ministry of Education, Wuhan, China
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Total article views: 5,777 (including HTML, PDF, and XML)
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Cited
20 citations as recorded by crossref.
- Land cover classification of Shangri-La by using Landsat data based on NDVI and canopy closure time-series characteristics considering fine classification of forests and grasslands Z. Zhou et al. https://doi.org/10.1007/s11676-026-02031-0
- GP-BO-Driven Ensemble Learning for High-Resolution Surface Soil Moisture Retrieval J. Chen et al. https://doi.org/10.1109/LGRS.2025.3639405
- Integrating time-series analysis and deep learning methods to reconstruct the long-term retrogressive thaw slumps dynamics in the Qinghai-Tibet Plateau J. MA et al. https://doi.org/10.1080/15481603.2026.2617753
- Intact peatlands experience smaller fire impact on tree cover than modified peatlands and non-peatlands in Indonesia E. Diatmiko et al. https://doi.org/10.3389/ffgc.2026.1840645
- Reconstruction of Daily MODIS 250-m Two-Band Enhanced Vegetation Index Time Series Using Gaussian Process Regression X. Liu et al. https://doi.org/10.1109/JSTARS.2025.3595541
- Multifaceted plant diversity patterns across the Himalaya: Status and outlook M. Ahmad et al. https://doi.org/10.1016/j.pld.2025.04.003
- The evolution and drivers of changes in Tibetan terrestrial ecosystems over the last millennium P. Zhang et al. https://doi.org/10.1016/j.quascirev.2026.109839
- The Interaction Between Vegetation Change and Land–Atmosphere Heat Exchange on the Tibetan Plateau C. Gong et al. https://doi.org/10.3390/rs17172996
- A novel framework for identifying artificial grassland planting areas using time-series multispectral imagery with enhanced accuracy S. Zheng et al. https://doi.org/10.1016/j.ecolind.2026.114729
- Climate and Altitude Drive Spatial and Temporal Changes in Forests on the Eastern Tibetan Plateau—Evidence from the Shaluli Mountain Y. Feng et al. https://doi.org/10.3390/f15111968
- A dual-scale framework for understanding ecosystem service patterns, interactions, resistance, and multifunctionality on the Qinghai–Tibet Plateau: implications for adaptive management B. Zhao & H. Zhang https://doi.org/10.1016/j.jenvman.2026.130456
- Interpretable machine learning and uncertainty quantification for high-precision fractional vegetation cover inversion across scales in alpine grasslands J. Chen et al. https://doi.org/10.1016/j.jag.2026.105212
- Comparative Study of Potential Habitats for Two Endemic Grassland Caterpillars on the Qinghai-Tibet Plateau Based on BIOMOD2 and Land Use Data C. Li et al. https://doi.org/10.3390/insects15100781
- Ecological Environmental Changes and the Impact on Alpine Wetland Spatiotemporal Differentiation in Western Sichuan H. Wang et al. https://doi.org/10.1007/s13157-025-01908-w
- Spatiotemporal lag effects between vegetation dynamics and climate variability on the Tibetan Plateau during 2001–2024 Z. Satti et al. https://doi.org/10.1016/j.rsase.2026.101984
- VOCs over the Himalayan-Tibetan Plateau: A review of observations, sources, and atmospheric processes D. Shan et al. https://doi.org/10.1016/j.atmosres.2026.109139
- Phenology-preserving temporal reconstruction of satellite-derived NDVI via morphological operations for unsupervised vegetation clustering H. Hosseini et al. https://doi.org/10.1016/j.rineng.2026.110037
- Feature-model strategies for remapping 1:1,000,000 vegetation map: application to the Tibetan Plateau F. Wu et al. https://doi.org/10.1016/j.asr.2026.02.087
- RTSEvo v1.0: a retrogressive thaw slump evolution model J. Xu et al. https://doi.org/10.5194/gmd-19-2919-2026
- Enhancing land cover classification in the heterogeneous landscape by integrating auxiliary data with Sentinel-2 imagery using the random forest algorithm I. Shandu et al. https://doi.org/10.3389/frsen.2025.1697897
20 citations as recorded by crossref.
- Land cover classification of Shangri-La by using Landsat data based on NDVI and canopy closure time-series characteristics considering fine classification of forests and grasslands Z. Zhou et al. https://doi.org/10.1007/s11676-026-02031-0
- GP-BO-Driven Ensemble Learning for High-Resolution Surface Soil Moisture Retrieval J. Chen et al. https://doi.org/10.1109/LGRS.2025.3639405
- Integrating time-series analysis and deep learning methods to reconstruct the long-term retrogressive thaw slumps dynamics in the Qinghai-Tibet Plateau J. MA et al. https://doi.org/10.1080/15481603.2026.2617753
- Intact peatlands experience smaller fire impact on tree cover than modified peatlands and non-peatlands in Indonesia E. Diatmiko et al. https://doi.org/10.3389/ffgc.2026.1840645
- Reconstruction of Daily MODIS 250-m Two-Band Enhanced Vegetation Index Time Series Using Gaussian Process Regression X. Liu et al. https://doi.org/10.1109/JSTARS.2025.3595541
- Multifaceted plant diversity patterns across the Himalaya: Status and outlook M. Ahmad et al. https://doi.org/10.1016/j.pld.2025.04.003
- The evolution and drivers of changes in Tibetan terrestrial ecosystems over the last millennium P. Zhang et al. https://doi.org/10.1016/j.quascirev.2026.109839
- The Interaction Between Vegetation Change and Land–Atmosphere Heat Exchange on the Tibetan Plateau C. Gong et al. https://doi.org/10.3390/rs17172996
- A novel framework for identifying artificial grassland planting areas using time-series multispectral imagery with enhanced accuracy S. Zheng et al. https://doi.org/10.1016/j.ecolind.2026.114729
- Climate and Altitude Drive Spatial and Temporal Changes in Forests on the Eastern Tibetan Plateau—Evidence from the Shaluli Mountain Y. Feng et al. https://doi.org/10.3390/f15111968
- A dual-scale framework for understanding ecosystem service patterns, interactions, resistance, and multifunctionality on the Qinghai–Tibet Plateau: implications for adaptive management B. Zhao & H. Zhang https://doi.org/10.1016/j.jenvman.2026.130456
- Interpretable machine learning and uncertainty quantification for high-precision fractional vegetation cover inversion across scales in alpine grasslands J. Chen et al. https://doi.org/10.1016/j.jag.2026.105212
- Comparative Study of Potential Habitats for Two Endemic Grassland Caterpillars on the Qinghai-Tibet Plateau Based on BIOMOD2 and Land Use Data C. Li et al. https://doi.org/10.3390/insects15100781
- Ecological Environmental Changes and the Impact on Alpine Wetland Spatiotemporal Differentiation in Western Sichuan H. Wang et al. https://doi.org/10.1007/s13157-025-01908-w
- Spatiotemporal lag effects between vegetation dynamics and climate variability on the Tibetan Plateau during 2001–2024 Z. Satti et al. https://doi.org/10.1016/j.rsase.2026.101984
- VOCs over the Himalayan-Tibetan Plateau: A review of observations, sources, and atmospheric processes D. Shan et al. https://doi.org/10.1016/j.atmosres.2026.109139
- Phenology-preserving temporal reconstruction of satellite-derived NDVI via morphological operations for unsupervised vegetation clustering H. Hosseini et al. https://doi.org/10.1016/j.rineng.2026.110037
- Feature-model strategies for remapping 1:1,000,000 vegetation map: application to the Tibetan Plateau F. Wu et al. https://doi.org/10.1016/j.asr.2026.02.087
- RTSEvo v1.0: a retrogressive thaw slump evolution model J. Xu et al. https://doi.org/10.5194/gmd-19-2919-2026
- Enhancing land cover classification in the heterogeneous landscape by integrating auxiliary data with Sentinel-2 imagery using the random forest algorithm I. Shandu et al. https://doi.org/10.3389/frsen.2025.1697897
Saved (final revised paper)
Latest update: 27 Jul 2026
Short summary
The Tibetan Plateau, with its diverse vegetation ranging from forests to alpine grasslands, plays a key role in understanding climate change impacts. Existing maps lack detail or miss unique ecosystems. Our research, using advanced satellite technology and machine learning, produced the map TP_LC10-2022. Comparisons with other maps revealed TP_LC10-2022's excellence in capturing local variations. Our map is significant for in-depth ecological studies.
The Tibetan Plateau, with its diverse vegetation ranging from forests to alpine grasslands,...
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