Mapping and dynamic monitoring of desertification on the Qinghai-Tibetan Plateau using surface Albedo and Solar-Induced Chlorophyll Fluorescence

Desertification poses a significant threat to humanity’s long-term survival and sustainable development. In this study, four types of 2D desertification assessment models were created by integrating surface albedo with four vegetation-related indicators: NDVI, MSAVI, EVI, and solar-induced chlorophyll fluorescence (SIF). A comprehensive analysis of the spatiotemporal variations in desertification on the Qinghai-Tibetan Plateau (QTP) from 2001 to 2020 was then conducted. Among the four models, the SA-SIF model demonstrated the highest overall accuracy (0.8675; 95% CI: 0.8512–0.8838) and Kappa coefficient (0.8452; 95% CI: 0.8289–0.8615), significantly outperforming the other three models ( p < 0.01, McNemar’s test). The SA-SIF model’s mapping results revealed substantial regional variability in desertification on the QTP, with the degree of desertification decreasing from northwest to southeast. Over the past decade, the expansion of severe and extremely severe desertification on the QTP has shown signs of slowing, although future trends may become more complex due to the interplay of climatic and anthropogenic factors. The SA-SIF model can serve as a reference for future desertification control operations on the QTP.

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Journal
PLoS ONE
Published
2026-09-25
DOI
https://doi.org/10.1371/journal.pone.0359348
Primary Topic
Remote Sensing in Agriculture
Type
article
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article

Mapping and dynamic monitoring of desertification on the Qinghai-Tibetan Plateau using surface Albedo and Solar-Induced Chlorophyll Fluorescence

Hui Lin, Zhijian Zhao, Linling Tang, Lei Wu et al.
PLoS ONE
Remote Sensing in Agriculture
article

Mapping and dynamic monitoring of desertification on the Qinghai-Tibetan Plateau using surface Albedo and Solar-Induced Chlorophyll Fluorescence

Hui Lin, Zhijian Zhao, Linling Tang, Lei Wu, Xin Xiao
article en

Abstract

Desertification poses a significant threat to humanity’s long-term survival and sustainable development. In this study, four types of 2D desertification assessment models were created by integrating surface albedo with four vegetation-related indicators: NDVI, MSAVI, EVI, and solar-induced chlorophyll fluorescence (SIF). A comprehensive analysis of the spatiotemporal variations in desertification on the Qinghai-Tibetan Plateau (QTP) from 2001 to 2020 was then conducted. Among the four models, the SA-SIF model demonstrated the highest overall accuracy (0.8675; 95% CI: 0.8512–0.8838) and Kappa coefficient (0.8452; 95% CI: 0.8289–0.8615), significantly outperforming the other three models ( p < 0.01, McNemar’s test). The SA-SIF model’s mapping results revealed substantial regional variability in desertification on the QTP, with the degree of desertification decreasing from northwest to southeast. Over the past decade, the expansion of severe and extremely severe desertification on the QTP has shown signs of slowing, although future trends may become more complex due to the interplay of climatic and anthropogenic factors. The SA-SIF model can serve as a reference for future desertification control operations on the QTP.

PLoS ONEVol. 21(9)
Xinyu University (CN), Jiangxi Normal University (CN)
Life in Land
Openalex Percentile: Top 11%
Remote Sensing in Agriculture
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Mapping and dynamic monitoring of desertification on the Qinghai-Tibetan Plateau using surface Albedo and Solar-Induced Chlorophyll Fluorescence — Hui Lin, Zhijian Zhao, et al. · PLoS ONE (2026) | TGRS Research Map | TGRS