Yuhang Zhang , Zhenqi Hu , Jiazheng Han , Xizhao Liu , Zhanjie Feng , Xi Zhang
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引用次数: 0
Abstract
Mapping ecological restoration regions (ERRs) is essential for assessing restoration progress and evaluating ecological projects. Traditional methods often face biases due to incomplete data. This study introduces a unified framework that integrates vegetation index evolution and land cover change, enabling precise pixel-level ERR identification across subtypes from 1991 to 2019. By enhancing spatial analysis through quantitative and geometric dimensions, we developed an ecological restoration index and utilized the SHAP model to uncover multi-scale driving factors. Results show ERRs in the Yellow River Basin expanded significantly from 2001 to 2010, averaging 2199.07 km2/a, with gradual vegetation restoration dominating (61.9 %). Key drivers of ecological restoration were identified as precipitation, temperature, and GDP, with mean SHAP values of 0.42, 0.52, and 0.34 at the provincial, municipal, and grid scales, respectively. This study advances ERR identification methodologies and explores the complex interactions between ecological restoration and its drivers at various scales. These insights are vital for the systematic planning and phased adjustment of ecological restoration initiatives.
期刊介绍:
Environmental Impact Assessment Review is an interdisciplinary journal that serves a global audience of practitioners, policymakers, and academics involved in assessing the environmental impact of policies, projects, processes, and products. The journal focuses on innovative theory and practice in environmental impact assessment (EIA). Papers are expected to present innovative ideas, be topical, and coherent. The journal emphasizes concepts, methods, techniques, approaches, and systems related to EIA theory and practice.