Monitoring and driving factors analysis of vegetation in Henan Province from 2000 to 2023

Vegetation dynamics reflect coupled climate and land-use change, yet their drivers often vary across physiographic and basin contexts, complicating regional attribution. This study assesses spatiotemporal NDVI changes in Henan Province, China, from 2000 to 2023 and diagnoses the relative roles of climate and human activities across the Yellow, Huai, Hai, and Yangtze river basins. Annual mean growing-season NDVI time series were analyzed using Theil-Sen slope estimation and significance testing to map trend magnitude and direction. Basin-scale climate-vegetation relationships were examined with partial correlation against temperature and precipitation, while GeoDetector was used to quantify dominant controls and interaction effects among topographic and edaphic factors. A residual trend approach was further applied to separate the net anthropogenic signal after accounting for climatic influences, and pixels with statistical significance (p < 0.05) were mapped. Results indicate an overall greening tendency with marked spatial heterogeneity, including localized degradation hotspots. Topography and soil-related factors and their interactions explain substantial spatial stratified heterogeneity, whereas NDVI responses to temperature and precipitation differ among basins. Residual attribution suggests that human activities predominantly promote vegetation improvement, while inhibiting effects are more localized and fragmented. These findings provide basin-explicit evidence for targeted ecosystem management and climate-adaptive land-use planning in Henan.

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Publication Details

Journal
PLoS ONE
Published
2026-08-27
DOI
https://doi.org/10.1371/journal.pone.0357044
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
0.00

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article

Monitoring and driving factors analysis of vegetation in Henan Province from 2000 to 2023

Junqiang Xu, Qian Yang, Chao Ren, Wendi Luo et al.
PLoS ONE
Remote Sensing in Agriculture
article

Monitoring and driving factors analysis of vegetation in Henan Province from 2000 to 2023

Junqiang Xu, Qian Yang, Chao Ren, Wendi Luo, Yafen Yu, Lei Wang
article en

Abstract

Vegetation dynamics reflect coupled climate and land-use change, yet their drivers often vary across physiographic and basin contexts, complicating regional attribution. This study assesses spatiotemporal NDVI changes in Henan Province, China, from 2000 to 2023 and diagnoses the relative roles of climate and human activities across the Yellow, Huai, Hai, and Yangtze river basins. Annual mean growing-season NDVI time series were analyzed using Theil-Sen slope estimation and significance testing to map trend magnitude and direction. Basin-scale climate-vegetation relationships were examined with partial correlation against temperature and precipitation, while GeoDetector was used to quantify dominant controls and interaction effects among topographic and edaphic factors. A residual trend approach was further applied to separate the net anthropogenic signal after accounting for climatic influences, and pixels with statistical significance (p < 0.05) were mapped. Results indicate an overall greening tendency with marked spatial heterogeneity, including localized degradation hotspots. Topography and soil-related factors and their interactions explain substantial spatial stratified heterogeneity, whereas NDVI responses to temperature and precipitation differ among basins. Residual attribution suggests that human activities predominantly promote vegetation improvement, while inhibiting effects are more localized and fragmented. These findings provide basin-explicit evidence for targeted ecosystem management and climate-adaptive land-use planning in Henan.

PLoS ONEVol. 21(8)
Jilin University (CN), Chinese Academy of Sciences (CN), Jilin Jianzhu University (CN), Northeast Institute of Geography and Agroecology (CN), Remote Sensing Application Center (BG), Jilin Province Science and Technology Department (CN), Henan Institute of Geological Survey (CN), State Key Laboratory of Remote Sensing Science (CN)
National Aeronautics and Space Administration
Climate action
Openalex Percentile: Top 10%
Remote Sensing in Agriculture
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