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Syntactic Step Depth×Urban Form Morphometrics×
OborUrban StudiesUrban Studies
RodinaProcess / pipelineProcess / pipeline
Rok vzniku19842019
TvůrceBill Hillier & Julienne HansonQuantitative urban-morphology tradition; momepy toolkit by Martin Fleischmann
TypTopological measure of depth and integration between spacesSystematic quantitative measurement of urban form across buildings, plots, blocks, and streets
Původní zdrojHillier, B., & Hanson, J. (1984). The Social Logic of Space. Cambridge University Press. ISBN: 9780521367844Fleischmann, M. (2019). momepy: Urban Morphology Measuring Toolkit. Journal of Open Source Software, 4(43), 1807. DOI ↗
Další názvyTopological Step Depth, Mean Depth (Space Syntax), Justified Graph Depth, Syntactic IntegrationUrban Morphometrics, Quantitative Urban Morphology, Morphometric Analysis of Urban Form, Built-Form Morphometrics
Příbuzné44
ShrnutíSyntactic step depth is the space-syntax measure of how topologically far apart spaces are — how many turns, transitions or moves separate one space from another, regardless of metric distance. Formalised by Bill Hillier and Julienne Hanson in The Social Logic of Space (1984), it is computed from a justified graph in which every space is a node and every direct adjacency an edge, and a single step is one move between connected spaces. Aggregated into mean depth and normalised into an integration value, step depth becomes the workhorse of configurational analysis, predicting which spaces will be most used, most accessible and most central in a building or city.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.
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ScholarGatePorovnat metody: Syntactic Step Depth · Urban Form Morphometrics. Získáno 2026-06-24 z https://scholargate.app/cs/compare