方法对比

	服务区域分析	最小成本路径 / 成本距离分析	区位-分配模型
领域	空间分析	空间分析	空间分析
方法族	Process / pipeline	Process / pipeline	Process / pipeline
起源年份	2001	1994	1963
提出者	Harvey Miller & Shih-Lung Shaw	Edsger Dijkstra (shortest path); GIS cost-surface adaptation	Leon Cooper; S. L. Hakimi
类型	Network GIS pipeline	Raster cost-surface routing	Spatial facility-location optimization
开创性文献	Miller, H. J., & Shaw, S.-L. (2001). Geographic Information Systems for Transportation: Principles and Applications. Oxford University Press. ISBN: 978-0-19-512394-4	Dijkstra, E. W. (1959). A note on two problems in connexion with graphs. Numerische Mathematik, 1(1), 269–271.	Cooper, L. (1963). Location-allocation problems. Operations Research, 11(3), 331–343.
别名	Isochrone Analysis, Network Catchment Area Analysis, Travel-Time Polygon Analysis, Hizmet Alanı Analizi	cost-distance analysis, accumulated cost surface, least-cost corridor, en düşük maliyetli yol	facility location, p-median problem, maximal covering location problem, yer-tahsis modelleri
相关	3	3	4
摘要	Service Area Analysis delineates the geographic region reachable from one or more origin facilities within a specified travel cost — typically time, distance, or generalized impedance — by traversing a real road or transit network. It is widely used by urban planners, public health officials, logistics managers, and emergency response coordinators who need to understand actual accessibility rather than simple straight-line buffers.	Least-cost path analysis finds the route between two locations that minimizes accumulated travel cost across a landscape, rather than minimizing straight-line distance. By encoding terrain, slope, land cover, and other frictions into a cost surface and accumulating cost outward from a source, it identifies optimal corridors for roads, pipelines, trails, power lines, and wildlife movement — a core raster-GIS technique built on Dijkstra's shortest-path logic.	Location-allocation models decide where to place a set of facilities and simultaneously assign demand points to them so as to optimize an objective such as total travel cost, worst-case distance, or population covered. Rooted in the operations-research work of Cooper (1963) and Hakimi (1964) and central to network GIS, they answer questions like where to site warehouses, hospitals, fire stations, or schools to best serve a spatially distributed population.