Remote sensing assessment of shrub encroachment and its driving mechanisms in semi-arid grasslands

Influenced by climate change and human activities, shrub encroachment in global arid and semi-arid grasslands profoundly affects ecosystem functions and livestock farming. Remote sensing technology is crucial for evaluating shrub encroachment across spatial and temporal scales, providing a broader perspective for understanding its driving mechanisms. The shrub encroachment dominated by Caragana vegetation in the Inner Mongolia grasslands is typical both in China and globally. However, the lack of remote sensing studies hinders a deeper understanding of the current status and causes of shrub encroachment in this region. This study focuses on the semi-arid grasslands in central Inner Mongolia, estimating shrub coverage based on vegetation indices, SAR backscatter coefficients, phenological metrics, and the extreme gradient boosting algorithm. A new Remote Sensing-based Shrub Encroachment Index (RSSEI) was established to assess the stage of shrub encroachment. The complex driving mechanisms of shrub encroachment were innovatively elucidated through the integrated application of Geographical Detector (GD) and Geographical Convergent Cross Mapping (GCCM). The results show that the shrub coverage estimation model achieved high accuracy (R2 = 0.70, RMSE = 4.0%, MAE = 2.7%), with the SHapley Additive exPlanations (SHAP) value indicating the significant role of phenological metrics in estimating shrub coverage. The RSSEI was found to grade shrub encroachment stages more accurately, with overall accuracy reaching 74.6%. Moderate to severe encroached grasslands dominate the study area, exhibiting an east-high and west-low spatial distribution. GD and GCCM indicated that moisture-related factors, including precipitation, soil water content, and vapor pressure deficit, were the main driving forces of shrub encroachment. And shrub encroachment has a significant causal influence on 2 m-height air temperature. This study provides an improving technical reference for remote sensing observation of shrub encroachment in semi-arid grasslands and is also valuable for understanding the formation causes and feedback effects of shrub encroachment in these areas.

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Publication Details

Journal
GIScience & Remote Sensing
Published
2025-09-02
DOI
https://doi.org/10.1080/15481603.2025.2555073
Citations
1
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
1.72

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article

Remote sensing assessment of shrub encroachment and its driving mechanisms in semi-arid grasslands

Dong Yang, Cong Xu, Min Zhang, Ang Chen et al.
1 citations
GIScience & Remote Sensing
Remote Sensing in Agriculture
1.72
article

Remote sensing assessment of shrub encroachment and its driving mechanisms in semi-arid grasslands

Dong Yang, Cong Xu, Min Zhang, Ang Chen, Yang Xiuchun, Xiaoyu Xing, Bin Xu
article en
1 citations

Abstract

Influenced by climate change and human activities, shrub encroachment in global arid and semi-arid grasslands profoundly affects ecosystem functions and livestock farming. Remote sensing technology is crucial for evaluating shrub encroachment across spatial and temporal scales, providing a broader perspective for understanding its driving mechanisms. The shrub encroachment dominated by Caragana vegetation in the Inner Mongolia grasslands is typical both in China and globally. However, the lack of remote sensing studies hinders a deeper understanding of the current status and causes of shrub encroachment in this region. This study focuses on the semi-arid grasslands in central Inner Mongolia, estimating shrub coverage based on vegetation indices, SAR backscatter coefficients, phenological metrics, and the extreme gradient boosting algorithm. A new Remote Sensing-based Shrub Encroachment Index (RSSEI) was established to assess the stage of shrub encroachment. The complex driving mechanisms of shrub encroachment were innovatively elucidated through the integrated application of Geographical Detector (GD) and Geographical Convergent Cross Mapping (GCCM). The results show that the shrub coverage estimation model achieved high accuracy (R2 = 0.70, RMSE = 4.0%, MAE = 2.7%), with the SHapley Additive exPlanations (SHAP) value indicating the significant role of phenological metrics in estimating shrub coverage. The RSSEI was found to grade shrub encroachment stages more accurately, with overall accuracy reaching 74.6%. Moderate to severe encroached grasslands dominate the study area, exhibiting an east-high and west-low spatial distribution. GD and GCCM indicated that moisture-related factors, including precipitation, soil water content, and vapor pressure deficit, were the main driving forces of shrub encroachment. And shrub encroachment has a significant causal influence on 2 m-height air temperature. This study provides an improving technical reference for remote sensing observation of shrub encroachment in semi-arid grasslands and is also valuable for understanding the formation causes and feedback effects of shrub encroachment in these areas.

GIScience & Remote SensingVol. 62(1)
University of Canterbury (NZ), Peking University (CN), Beijing Forestry University (CN), Chinese Academy of Agricultural Sciences (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation
Openalex Percentile: Top 14%
Remote Sensing in Agriculture
1.72
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