北京林业大学学报2026，Vol.48Issue(2)：70-79,10.DOI:10.12171/j.1000-1522.20250205
基于MGWR模型的森林覆盖率分布特征及影响因素
Spatial patterns and drivers of forest cover:a MGWR modeling framework
摘要
Abstract
[Objective]Forest resources constitute the material foundation for social development and a crucial guarantee for sustainable development.Analyzing the spatial distribution characteristics of forest cover and its influencing factors provides valuable insights for protecting and developing forest resources.[Method]Using provincial-level administrative units as the basic research units and integrating regional fundamental data,this study investigated the spatial distribution characteristics of forest cover at the national scale based on ArcGIS Pro and GeoDa platforms.Spatial autocorrelation analysis was employed to reveal the heterogeneity in the spatial distribution of forest cover.Significant influencing variables were screened through multicollinearity tests.Multiple linear regression(OLS),geographically weighted regression(GWR),and multiscale geographically weighted regression(MGWR)models were constructed and compared to evaluate their applicability in explaining the factors influencing forest cover.[Result](1)Forest cover exhibited significant positive spatial dependence,with a global Moran's I index of 0.502,Z=4.34(p<0.001);(2)Based on model evaluation indicators,compared with OLS and GWR models,the MGWR model performs best in analyzing the influencing factors,showing the highest R2 and adjusted R2 and the lowest AICc;(3)MGWR-based analysis indicates that precipitation is positively correlated with forest cover rate spatially,while sunshine duration and average soil pH are negatively correlated.Natural factors have greater influence on forest cover rate in western regions,whereas the eastern regions are more affected by socioeconomic activities.[Conclusion](1)Forest cover rate displays spatial imbalance with an overall"southeast-northwest"decreasing gradient and a clustered spatial pattern.Local spatial associations mainly consist of high-high and low-low clusters,suitable for multiscale geographically weighted regression analysis;(2)The MGWR model shows superior performance in analyzing forest cover rate influencing factors,explaining 81.2%of the spatial variation according to the adjusted R2.关键词
森林覆盖率/多尺度地理加权回归模型/空间异质性/空间分布/地理信息系统Key words
forest cover/multiscale geographically weighted regression(MGWR)/spatial heterogeneity/spatial distribution/geo-information system分类
农业科技引用本文复制引用
吴雅桃,林坤,胡娅楠,林昕毅,孙帅超..基于MGWR模型的森林覆盖率分布特征及影响因素[J].北京林业大学学报,2026,48(2):70-79,10.基金项目
国家自然科学基金项目(32201558). （32201558）
