Urban Forest Health Under Rapid Urbanization: Spatiotemporal Patterns and Driving Mechanisms from the Chang–Zhu–Tan Green Heart Area

The Ecological Green Heart Area of the Chang–Zhu–Tan Urban Agglomeration in Central China faces increasing forest health threats due to rapid urbanization and land use change. This study assessed the spatiotemporal dynamics and drivers of forest health from 2005 to 2023 using a multi-dimensional framework based on vitality, organizational structure, and anti-interference capacity. A forest health index (FHI) was constructed using multi-source data, and the optimal parameter geographic detector (OPGD) model was applied to identify dominant and interacting factors. The results show the following: (1) FHI declined from 0.62 (2005) to 0.55 (2015) and rebounded to 0.60 (2023). (2) Healthier forests were concentrated in the east and center, with degradation in the west and south; (3) Topography was the leading driver (q = 0.17), followed by climate, while socioeconomic factors gained influence over time. (4) Interactions among factors showed strong nonlinear enhancement. This research demonstrates the effectiveness of the OPGD model in capturing spatial heterogeneity and interaction effects, underscoring the need for differentiated, spatially informed conservation and land management strategies. This research provides scientific support for integrating ecological protection with urban planning, contributing to the broader goals of ecosystem resilience, sustainable land use, and regional sustainability.

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Publication Details

Journal
Sustainability
Published
2025-08-12
DOI
https://doi.org/10.3390/su17167268
Citations
1
Primary Topic
Urban Green Space and Health
Type
article
Field-Weighted Citation Impact
1.20

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article

Urban Forest Health Under Rapid Urbanization: Spatiotemporal Patterns and Driving Mechanisms from the Chang–Zhu–Tan Green Heart Area

Jiyun She, Caihong Chen, Ye Xu, Jiajun Lei
1 citations
Sustainability
Urban Green Space and Health
1.20
article

Urban Forest Health Under Rapid Urbanization: Spatiotemporal Patterns and Driving Mechanisms from the Chang–Zhu–Tan Green Heart Area

Jiyun She, Caihong Chen, Ye Xu, Jiajun Lei
article en
1 citations

Abstract

The Ecological Green Heart Area of the Chang–Zhu–Tan Urban Agglomeration in Central China faces increasing forest health threats due to rapid urbanization and land use change. This study assessed the spatiotemporal dynamics and drivers of forest health from 2005 to 2023 using a multi-dimensional framework based on vitality, organizational structure, and anti-interference capacity. A forest health index (FHI) was constructed using multi-source data, and the optimal parameter geographic detector (OPGD) model was applied to identify dominant and interacting factors. The results show the following: (1) FHI declined from 0.62 (2005) to 0.55 (2015) and rebounded to 0.60 (2023). (2) Healthier forests were concentrated in the east and center, with degradation in the west and south; (3) Topography was the leading driver (q = 0.17), followed by climate, while socioeconomic factors gained influence over time. (4) Interactions among factors showed strong nonlinear enhancement. This research demonstrates the effectiveness of the OPGD model in capturing spatial heterogeneity and interaction effects, underscoring the need for differentiated, spatially informed conservation and land management strategies. This research provides scientific support for integrating ecological protection with urban planning, contributing to the broader goals of ecosystem resilience, sustainable land use, and regional sustainability.

SustainabilityVol. 17(16)
Central South University of Forestry and Technology (CN), Central South University (CN)
National Key Research and Development Program of China
Openalex Percentile: Top 20%
Urban Green Space and Health
1.20
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Urban Forest Health Under Rapid Urbanization: Spatiotemporal Patterns and Driving Mechanisms from the Chang–Zhu–Tan Green Heart Area — Jiyun She, Caihong Chen, et al. · Sustainability (2025) | TGRS Research Map | TGRS