Methodological foundation of a numerical taxonomy of urban form

Cities are complex products of human culture, characterised by a startling diversity of visible traits. Their form is constantly evolving, reflecting changing human needs and local contingencies, manifested in space by many urban patterns. Urban morphology laid the foundation for understanding many such patterns, largely relying on qualitative research methods to extract distinct spatial identities of urban areas. However, the manual, labour-intensive and subjective nature of such approaches represents an impediment to the development of a scalable, replicable and data-driven urban form characterisation. Recently, advances in geographic data science and the availability of digital mapping products open the opportunity to overcome such limitations. And yet, our current capacity to systematically capture the heterogeneity of spatial patterns remains limited in terms of spatial parameters included in the analysis and hardly scalable due to the highly labour-intensive nature of the task. In this paper, we present a method for numerical taxonomy of urban form derived from biological systematics, which allows the rigorous detection and classification of urban types. Initially, we produce a rich numerical characterisation of urban space from minimal data input, minimising limitations due to inconsistent data quality and availability. These are street network, building footprint and morphological tessellation, a spatial unit derivative of Voronoi tessellation, obtained from building footprints. Hence, we derive homogeneous urban tissue types and, by determining overall morphological similarity between them, generate a hierarchical classification of urban form. After framing and presenting the method, we test it on two cities – Prague and Amsterdam – and discuss potential applications and further developments. The proposed classification method represents a step towards the development of an extensive, scalable numerical taxonomy of urban form and opens the way to more rigorous comparative morphological studies and explorations into the relationship between urban space and phenomena as diverse as environmental performance, health and place attractiveness.

[1]  Yan Song,et al.  Quantitative Classification of Neighbourhoods: The Neighbourhoods of New Single-family Homes in the Portland Metropolitan Area , 2007 .

[2]  J. H. Ward Hierarchical Grouping to Optimize an Objective Function , 1963 .

[3]  Michael Mehaffy,et al.  Urban nuclei and the geometry of streets: The ‘emergent neighborhoods’ model , 2009 .

[4]  G. Fusco,et al.  From the street to the metropolitan region: Pedestrian perspective in urban fabric analysis , 2019, Environment and Planning B: Urban Analytics and City Science.

[5]  R. Höfer,et al.  New perspectives in land use mapping based on urban morphology: A case study of the Federal District, Brazil , 2019, Land Use Policy.

[6]  Warren C. Jochem,et al.  Classifying settlement types from multi-scale spatial patterns of building footprints , 2020, Environment and Planning B: Urban Analytics and City Science.

[7]  Jason Parent,et al.  Atlas of Urban Expansion , 2012 .

[8]  M. Conzen Alnwick, Northumberland : a study in town-plan analysis , 1960 .

[9]  Thomas Blaschke,et al.  A Generic Classification Scheme for Urban Structure Types , 2019, Remote. Sens..

[10]  S. Evans,et al.  Wall area, volume and plan depth in the building stock , 2009 .

[11]  Gotthard Meinel,et al.  A Workflow for Automatic Quantification of Structure and Dynamic of the German Building Stock Using Official Spatial Data , 2016, ISPRS Int. J. Geo Inf..

[12]  M. Barthelemy,et al.  A typology of street patterns , 2014, Journal of The Royal Society Interface.

[13]  Karl S. Kropf,et al.  The Handbook of Urban Morphology , 2017 .

[14]  Stan Openshaw,et al.  Modifiable Areal Unit Problem , 2008, Encyclopedia of GIS.

[15]  Xiaoxiang Zhu,et al.  Seven city types representing morphologic configurations of cities across the globe , 2020 .

[16]  Filip Biljecki,et al.  An improved LOD specification for 3D building models , 2016, Comput. Environ. Urban Syst..

[17]  Monika Sester,et al.  IDENTIFYING BUILDING TYPES AND BUILDING CLUSTERS USING 3 D-LASER SCANNING AND GIS-DATA , 2004 .

[18]  A. Agresti An introduction to categorical data analysis , 1997 .

[19]  Jorge Gil,et al.  Street network analysis “edge effects”: Examining the sensitivity of centrality measures to boundary conditions , 2017 .

[20]  Thomas Leduc,et al.  Towards Urban Fabrics Characterization Based on Buildings Footprints , 2012, AGILE Conf..

[21]  G. Schwarz Estimating the Dimension of a Model , 1978 .

[22]  Selim Aksoy,et al.  Modeling urban structures using graph-based spatial patterns , 2007, 2007 IEEE International Geoscience and Remote Sensing Symposium.

[23]  Kay W. Axhausen,et al.  A multiscale classification of the urban morphology , 2016 .

[24]  Robert Weibel,et al.  An Approach for the Classification of Urban Building Structures Based on Discriminant Analysis Techniques , 2008, Trans. GIS.

[25]  Hannes Taubenböck,et al.  Building Types’ Classification Using Shape-Based Features and Linear Discriminant Functions , 2016, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[26]  K. Axhausen,et al.  A multiscale classification of urban morphology , 2015 .

[27]  S. Porta,et al.  Measuring urban form: Overcoming terminological inconsistencies for a quantitative and comprehensive morphologic analysis of cities , 2020, Environment and Planning B: Urban Analytics and City Science.

[28]  Martin Fleischmann,et al.  momepy: Urban Morphology Measuring Toolkit , 2019, J. Open Source Softw..

[29]  Gian Luigi Maffei,et al.  Architectural Composition and Building Typology: Interpreting Basic Building , 2001 .

[30]  Karl S. Kropf,et al.  Urban tissue and the character of towns , 1996 .

[31]  R. Herrmann On the origin of space , 2013, 1308.4587.

[32]  S. Porta,et al.  Morphological tessellation as a way of partitioning space: Improving consistency in urban morphology at the plot scale , 2020, Comput. Environ. Urban Syst..

[33]  Philip Steadman,et al.  The Evolution of Designs: Biological Analogy in Architecture and the Applied Arts - revised edition (first published 1979) with new ‘Afterword’ , 2008 .

[34]  Darren Baird,et al.  Alterations in scale: Patterns of change in main street networks across time and space , 2014 .

[35]  T. Oke,et al.  Local Climate Zones for Urban Temperature Studies , 2012 .

[36]  Satej Soman,et al.  Worldwide Detection of Informal Settlements via Topological Analysis of Crowdsourced Digital Maps , 2020, ISPRS Int. J. Geo Inf..

[37]  Geoff Boeing,et al.  Off the Grid…and Back Again? , 2020, 2010.04771.

[38]  M. Berghauser Pont,et al.  Towards analytical typologies of plot systems: Quantitative profile of five European cities , 2019, Environment and Planning B: Urban Analytics and City Science.

[39]  Frank Canters,et al.  Mapping urban form and function at city block level using spatial metrics , 2017 .

[40]  Michael Wurm,et al.  Oliveira, Vítor (2016): Urban Morphology. An Introduction to the Study of the Physical Form of Cities , 2017 .

[41]  Douglas A. Reynolds Gaussian Mixture Models , 2009, Encyclopedia of Biometrics.

[42]  Alex Singleton,et al.  Geodemographics, visualisation, and social networks in applied geography , 2009 .

[43]  Giovanni Fusco,et al.  Decomposing and Recomposing Urban Fabric: The City from the Pedestrian Point of View , 2017, ICCSA.

[44]  A. Moudon Urban Morphology as an emerging interdisciplinary field , 2022, Urban Morphology.

[45]  Luc Anselin,et al.  The Max‐P‐Regions Problem , 2012 .

[46]  Lars Marcus,et al.  Development of urban types based on network centrality, built density and their impact on pedestrian movement , 2019, Environment and Planning B: Urban Analytics and City Science.

[47]  Frank Brown,et al.  A Classification of Built Forms , 2000 .

[48]  K. Gu,et al.  The Typological Process and the Morphological Period: A Cross-Cultural Assessment , 2014 .

[49]  K. Kropf Plots, property and behaviour , 2017, Urban Morphology.

[50]  Jorge Gil,et al.  On the discovery of urban typologies: data mining the many dimensions of urban form , 2011, Urban Morphology.

[51]  I. Thomas,et al.  The urban form of Brussels from the street perspective: The role of vegetation in the definition of the urban fabric , 2021 .

[52]  Mattia Zanella,et al.  On the origin of spaces: Morphometric foundations of urban form evolution , 2019 .

[53]  Saverio Muratori,et al.  Studi per una operante storia urbana di venezia , 1959 .

[54]  Alessandra Feliciotti,et al.  Evolution of Urban Patterns: Urban Morphology as an Open Reproducible Data Science , 2021, Geographical Analysis.

[55]  Vítor Oliveira,et al.  Urban Morphology: An Introduction to the Study of the Physical Form of Cities , 2016 .

[56]  Geoffrey Caruso,et al.  Measuring urban forms from inter-building distances: combining MST graphs with a local index of spatial association , 2017 .

[57]  Sophia Psarra,et al.  Social and Physical Characterization of Urban Contexts: Techniques and Methods for Quantification, Classification and Purposive Sampling , 2018 .

[58]  S. Porta,et al.  The road to masterplanning for change and the design of resilient places , 2017 .

[59]  J. Gil,et al.  The spatial distribution and frequency of street, plot and building types across five European cities , 2019, Environment and Planning B: Urban Analytics and City Science.