Urban neighbourhood classification and multi-scale heterogeneity analysis of Greater London
Author(s)
Yu, Tengfei
Suetzl, Birgit S
van Reeuwijk, Maarten
Type
Journal Article
Abstract
We study the compositional and configurational heterogeneity of Greater London at the city- and neighbourhood-scale using Geographic Information System (GIS) data. Urban morphometric indicators are calculated including plan-area indices and fractal dimensions of land cover, frontal area index of buildings, evenness, and contagion. To distinguish between city-scale heterogeneity and neighbourhood-scale heterogeneity, the study area of 720 km2 is divided into 1 ×
1 km2 neighbourhoods. City-scale heterogeneity is represented by categorisation of the neighbourhoods using a k-means clustering algorithm based on the morphometric indicators. This results in six neighbourhood types ranging from “greenspace” to “central business district”. Neighbourhood-scale heterogeneity is quantified using a hierarchical multi-scale analysis for each neighbourhood type. The analysis reveals the dominant length scales for land-cover and neighbourhood types and the resolutions with the most information gain. We analyse multi-scale anisotropy and show that small-scale features are homogeneous, and that anisotropy is present at larger length scales.
1 km2 neighbourhoods. City-scale heterogeneity is represented by categorisation of the neighbourhoods using a k-means clustering algorithm based on the morphometric indicators. This results in six neighbourhood types ranging from “greenspace” to “central business district”. Neighbourhood-scale heterogeneity is quantified using a hierarchical multi-scale analysis for each neighbourhood type. The analysis reveals the dominant length scales for land-cover and neighbourhood types and the resolutions with the most information gain. We analyse multi-scale anisotropy and show that small-scale features are homogeneous, and that anisotropy is present at larger length scales.
Date Issued
2023-07-01
Date Acceptance
2022-11-01
Citation
Environment and Planning B: Urban Analytics and City Science, 2023, 50 (6), pp.1534-1558
ISSN
2399-8083
Publisher
SAGE Publications
Start Page
1534
End Page
1558
Journal / Book Title
Environment and Planning B: Urban Analytics and City Science
Volume
50
Issue
6
Copyright Statement
© The Author(s) 2022, Article Reuse Guidelines. This work is published under a CC BY licence (https://creativecommons.org/licenses/by/4.0/)
License URL
Identifier
https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000891010000001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a2bf6146997ec60c407a63945d4e92bb
Subjects
classification
ENERGY
ENVIRONMENT SIMULATOR JULES
Environmental Sciences & Ecology
Environmental Studies
FRAMEWORK
Geography
Life Sciences & Biomedicine
MODEL DESCRIPTION
neighbourhood-scale
Public Administration
Regional & Urban Planning
Science & Technology
Social Sciences
spatial heterogeneity
SPATIAL HETEROGENEITY
urban landscape
Urban Studies
Publication Status
Published
Date Publish Online
2022-11-25