福建师范大学学报（自然科学版）2026，Vol.42Issue(1)：80-90,11.DOI:10.12046/j.issn.1000-5277.2025020028
基于最小阻力模型的生态公路网络构建
Construction of an Ecological Highway Network Based on the Minimum Cumulative Resistance
摘要
Abstract
Environmentally friendly highway alignment is crucial for advancing national ecolog-ical civilization.This study focuses on Fuzhou City as the research area and uses human footprint in-dex and morphological spatial pattern analysis to identify transportation nodes.Eight evaluation fac-tors—normalized difference vegetation index,remote sensing ecological index,carbon sequestra-tion,net primary productivity,land use type,slope,elevation,and distance to water systems—are selected to construct the resistance surface.Based on this,the minimum cumulative resistance(MCR)model is applied to construct an ecological highway network.The results indicate that:(1)Human activities in Fuzhou City are primarily concentrated in the southeastern coastal areas,while the western region exhibits small-scale clusters and widely dispersed distribution;(2)The overall comprehensive resistance of Fuzhou City shows a west-high,east-low trend;(3)The ecological highway network extracted using the MCR model presents a crisscrossed,irregular"fishing net"structure,including 16 nodes,120 routes,and a total length of approximately 2001 km;(4)Ec-ological cost analysis based on 1000 m×1000 m grid units reveals that the average ecological cost of the ecological highway network(5.457)is lower than that of the existing road network(5.801).The findings provide a scientific basis for ecological highway alignment and offer valuable references for green infrastructure planning in other ecologically sensitive areas.关键词
绿色交通/路网规划/最小阻力模型/形态学空间格局分析/人类足迹指数Key words
green transportation/road network planning/minimum cumulative resistance/morphological spatial pattern analysis/human footprint index分类
交通工程引用本文复制引用
蓝俊杰,王群,林玉英,林程翔,林森,姜莉,胡喜生..基于最小阻力模型的生态公路网络构建[J].福建师范大学学报（自然科学版）,2026,42(1):80-90,11.基金项目
国家自然科学基金项目(41201100) （41201100）
福建省社会科学基金重点项目(FJ2025MGCA022) （FJ2025MGCA022）
福建省自然科学基金项目(2023J01514) （2023J01514）
