手法を比較

	Figure-Ground Analysis	Urban Form Morphometrics
分野	Urban Studies	Urban Studies
系統	Process / pipeline	Process / pipeline
提唱年	1986	2019
提唱者	Giambattista Nolli (Nolli map, 1748); Roger Trancik (figure-ground theory)	Quantitative urban-morphology tradition; momepy toolkit by Martin Fleischmann
種類	Pipeline for mapping and measuring built mass versus open space in urban fabric	Systematic quantitative measurement of urban form across buildings, plots, blocks, and streets
原典	Trancik, R. (1986). Finding Lost Space: Theories of Urban Design. Wiley. ISBN: 9780471289562	Fleischmann, M. (2019). momepy: Urban Morphology Measuring Toolkit. Journal of Open Source Software, 4(43), 1807.
別名	Solid-Void Analysis, Nolli Map Analysis, Poché Mapping, Built-Mass and Open-Space Analysis	Urban Morphometrics, Quantitative Urban Morphology, Morphometric Analysis of Urban Form, Built-Form Morphometrics
関連	4	4
概要	Figure-ground analysis is an urban-design technique that maps a city as a pattern of solids and voids — buildings rendered as black figure against the white ground of streets, squares, and open space (or vice versa) — to reveal the structure, density, and spatial quality of the urban fabric. Descended from Giambattista Nolli's 1748 map of Rome, it makes legible the relationship between built mass and open space that ordinary plans obscure. Roger Trancik's 1986 Finding Lost Space established it as a core method of contemporary urban-design theory, arguing that good cities are defined as much by the shape of their voids as by their buildings.	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.