方法对比

	Suitability Analysis	Urban Form Morphometrics
领域	Urban Studies	Urban Studies
方法族	Process / pipeline	Process / pipeline
起源年份	1969	2019
提出者	Ian L. McHarg	Quantitative urban-morphology tradition; momepy toolkit by Martin Fleischmann
类型	Spatial multi-criteria mapping of land suitability for a given use	Systematic quantitative measurement of urban form across buildings, plots, blocks, and streets
开创性文献	McHarg, I. L. (1969). Design with Nature. Natural History Press. ISBN: 9780471114604	Fleischmann, M. (2019). momepy: Urban Morphology Measuring Toolkit. Journal of Open Source Software, 4(43), 1807.
别名	Land Suitability Mapping, Overlay Suitability Analysis, Weighted Overlay Analysis, Suitability Modelling	Urban Morphometrics, Quantitative Urban Morphology, Morphometric Analysis of Urban Form, Built-Form Morphometrics
相关	4	4
摘要	Suitability analysis maps how well each parcel of land supports a proposed use — housing, conservation, a highway, a landfill — by combining the relevant physical, ecological and accessibility factors into a single composite score. In the tradition established by Ian McHarg's 1969 Design with Nature, each factor is captured as a map layer, reclassified onto a common suitability scale, and overlaid so that places good on many factors stand out from places that are not. The result is a suitability surface that makes the trade-offs in a land-use decision explicit, transparent and defensible.	Urban form morphometrics is the systematic, quantitative measurement of the physical form of cities — the dimensions, shapes, spatial arrangement, intensity, and connectivity of buildings, plots, blocks, and streets. Rather than describing morphology in words, it computes hundreds of reproducible numerical characters on each morphological element and its local context, turning the qualitative tradition of urban morphology into a measurable science. The open-source momepy toolkit, introduced by Martin Fleischmann in 2019, standardized this workflow, building a morphological tessellation from building footprints and computing dimension, shape, distribution, intensity, and connectivity characters at scale.