Unstable changes in ecological quality of the four major sandy lands in northern China based on Google Earth Engine

• Monitor ecological quality of China’s 4 major sandy lands from 2000 to 2022. • Decompose trends and abrupt changes using time series decomposition algorithm. • Use Geographical Detector to explore driving mechanisms over different periods. • The ecological quality of the 4 sandy lands improves, while 2 show unstable trends. • Natural factors primarily drive 3 sandy lands, while anthropogenic factors drive 1. Based on the Google Earth Engine (GEE) platform, this study constructed a Remote Sensing-based Ecological Index (RSEI) model for four major sandy lands in northern China from 2000 to 2022. RESI incorporates a Bayesian Estimator of Abrupt change, Seasonal change, and Trend (BEAST) to mine abrupt change years and key information within the time series data. Moreover, it combines Geographical Detector (GD) to conduct a detailed quantitative study on the spatiotemporal variation and driving mechanisms of the Ecological Quality (EQ) in these sandy lands at different times and discusses possible causes for abrupt changes in the EQ. The results indicated that from 2000 to 2022, the EQ of all four major sandy lands improved to varying degrees. However, the introduction of BEAST revealed that the RSEI of all four sandy lands experienced abrupt changes in the latter half of the study period, with the EQ in the Horqin and Hulun Buir showing potential for continued improvement post-change. By contrast, the EQ of the Mu Us and Otindag showed a downward trend within certain intervals, indicating instability under adverse natural conditions. Regarding the driving mechanisms, the spatial distribution of the EQ in the four sandy lands was influenced by natural and anthropogenic factors, displaying complex interactions of driving factors within each sandy land. Among them, in the Mu Us, Otindag, and Hulun Buir, natural factors played a dominant role, whereas in the Horqin, anthropogenic factors played a dominant role.

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Publication Details

Journal
Ecological Indicators
Published
2025-02-01
DOI
https://doi.org/10.1016/j.ecolind.2025.113195
Citations
5
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
5.53

Funders

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article

Unstable changes in ecological quality of the four major sandy lands in northern China based on Google Earth Engine

Enliang Guo, Jisiguleng Wu, Rui Wang, Haowen Ma et al.
5 citations
Ecological Indicators
Land Use and Ecosystem Services
5.53
article

Unstable changes in ecological quality of the four major sandy lands in northern China based on Google Earth Engine

Enliang Guo, Jisiguleng Wu, Rui Wang, Haowen Ma, Yao Kang, Shan Yin, Jiapei Zhao, Quanfei Mu, Yanli Wang, Delong Zhou
article en
5 citations

Abstract

• Monitor ecological quality of China’s 4 major sandy lands from 2000 to 2022. • Decompose trends and abrupt changes using time series decomposition algorithm. • Use Geographical Detector to explore driving mechanisms over different periods. • The ecological quality of the 4 sandy lands improves, while 2 show unstable trends. • Natural factors primarily drive 3 sandy lands, while anthropogenic factors drive 1. Based on the Google Earth Engine (GEE) platform, this study constructed a Remote Sensing-based Ecological Index (RSEI) model for four major sandy lands in northern China from 2000 to 2022. RESI incorporates a Bayesian Estimator of Abrupt change, Seasonal change, and Trend (BEAST) to mine abrupt change years and key information within the time series data. Moreover, it combines Geographical Detector (GD) to conduct a detailed quantitative study on the spatiotemporal variation and driving mechanisms of the Ecological Quality (EQ) in these sandy lands at different times and discusses possible causes for abrupt changes in the EQ. The results indicated that from 2000 to 2022, the EQ of all four major sandy lands improved to varying degrees. However, the introduction of BEAST revealed that the RSEI of all four sandy lands experienced abrupt changes in the latter half of the study period, with the EQ in the Horqin and Hulun Buir showing potential for continued improvement post-change. By contrast, the EQ of the Mu Us and Otindag showed a downward trend within certain intervals, indicating instability under adverse natural conditions. Regarding the driving mechanisms, the spatial distribution of the EQ in the four sandy lands was influenced by natural and anthropogenic factors, displaying complex interactions of driving factors within each sandy land. Among them, in the Mu Us, Otindag, and Hulun Buir, natural factors played a dominant role, whereas in the Horqin, anthropogenic factors played a dominant role.

Ecological IndicatorsVol. 171
Inner Mongolia Agricultural University (CN), Inner Mongolia Normal University (CN), Inner Mongolia University (CN)
National Natural Science Foundation of China
Life in Land
Openalex Percentile: Top 5%
Land Use and Ecosystem Services
5.53
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