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Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
Published on: July 3, 2020
Monitoring and driving factors analysis of vegetation in Henan Province from 2000 to 2023
Junqiang Xu1,2, Wendi Luo3, Chao Ren3
1College of Geo-Exploration Science and Technology, Jilin University, Changchun, China.
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.
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