Extraction of Desertification Information and Spatiotemporal Change in the Qinghai‐Tibetan Plateau Based on Optimal Feature Space Combination

ABSTRACT Desertification seriously threatens the ecosystem security of the Qinghai‐Tibetan Plateau and the sustainable development of human society. The regional warming and humidification of the climate caused by global warming have brought uncertainty to the desertification development trend of the Qinghai‐Tibetan Plateau. Therefore, it is crucial to pay close attention to the status and trends of desertification. In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indexes, albedo and topsoil grain size index (TGSI) data for the Qinghai‐Tibetan Plateau were collected by Google Earth Engine (GEE) from 2000 to 2020, established an optimal monitoring model for desertification on the Qinghai‐Tibetan Plateau using the feature space, and analyzed the spatiotemporal evolution patterns. The results show that the albedo‐modified soil‐adjusted vegetation index (MSAVI) model is the most suitable for desertification monitoring in the Qinghai‐Tibetan Plateau region, with an overall accuracy of 88.07%. Generally, desertification on the Qinghai‐Tibetan Plateau shows an overall improving trend from 2000 to 2020, with the proportion of non‐desertification areas rising from 61% in 2000 to 70% in 2020. The desertification situation in most parts of the Qinghai‐Tibetan Plateau shows a worsening rebound from 2010 to 2015, and then improves. There are constant transitions between adjacent levels of desertification land, with more active low desertification land and more stable bare desert. This study provides a simple, feasible, and highly accurate desertification monitoring method for the Qinghai‐Tibetan Plateau region, and provides important data support for the driving mechanism and control measures of desertification.

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Publication Details

Journal
Land Degradation and Development
Published
2025-02-19
DOI
https://doi.org/10.1002/ldr.5528
Citations
3
Primary Topic
Remote Sensing and Land Use
Type
article
Field-Weighted Citation Impact
3.90
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article

Extraction of Desertification Information and Spatiotemporal Change in the Qinghai‐Tibetan Plateau Based on Optimal Feature Space Combination

Wang Tao, Ying Zhi, Shulin Liu, Wenping Kang et al.
3 citations
Land Degradation and Development
Remote Sensing and Land Use
3.90
article

Extraction of Desertification Information and Spatiotemporal Change in the Qinghai‐Tibetan Plateau Based on Optimal Feature Space Combination

Wang Tao, Ying Zhi, Shulin Liu, Wenping Kang, Hanchen Duan
article en
3 citations

Abstract

ABSTRACT Desertification seriously threatens the ecosystem security of the Qinghai‐Tibetan Plateau and the sustainable development of human society. The regional warming and humidification of the climate caused by global warming have brought uncertainty to the desertification development trend of the Qinghai‐Tibetan Plateau. Therefore, it is crucial to pay close attention to the status and trends of desertification. In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indexes, albedo and topsoil grain size index (TGSI) data for the Qinghai‐Tibetan Plateau were collected by Google Earth Engine (GEE) from 2000 to 2020, established an optimal monitoring model for desertification on the Qinghai‐Tibetan Plateau using the feature space, and analyzed the spatiotemporal evolution patterns. The results show that the albedo‐modified soil‐adjusted vegetation index (MSAVI) model is the most suitable for desertification monitoring in the Qinghai‐Tibetan Plateau region, with an overall accuracy of 88.07%. Generally, desertification on the Qinghai‐Tibetan Plateau shows an overall improving trend from 2000 to 2020, with the proportion of non‐desertification areas rising from 61% in 2000 to 70% in 2020. The desertification situation in most parts of the Qinghai‐Tibetan Plateau shows a worsening rebound from 2010 to 2015, and then improves. There are constant transitions between adjacent levels of desertification land, with more active low desertification land and more stable bare desert. This study provides a simple, feasible, and highly accurate desertification monitoring method for the Qinghai‐Tibetan Plateau region, and provides important data support for the driving mechanism and control measures of desertification.

Land Degradation and DevelopmentVol. 36(8)
Chinese Academy of Sciences (CN), Northwest Institute of Eco-Environment and Resources (CN), University of Chinese Academy of Sciences (CN)
Openalex Percentile: Top 8%
Remote Sensing and Land Use
3.90
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