Urban form and COVID-19 cases and deaths in Greater London: an urban morphometric approach

• URL: http://arxiv.org/abs/2210.08497v1
• Date: Sun, 16 Oct 2022 10:01:10 GMT
• Title: Urban form and COVID-19 cases and deaths in Greater London: an urban morphometric approach
• Authors: Alessandro Venerandi, Luca Maria Aiello, Sergio Porta
• Abstract summary: The COVID-19 pandemic generated a considerable debate in relation to urban density. This is an old debate, originated in mid 19th century's England with the emergence of public health and urban planning disciplines. We describe urban form at individual building level and then aggregate information for official neighbourhoods.
• Score: 63.29165619502806
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The COVID-19 pandemic generated a considerable debate in relation to urban density. This is an old debate, originated in mid 19th century's England with the emergence of public health and urban planning disciplines. While popularly linked, evidence suggests that such relationship cannot be generally assumed. Furthermore, urban density has been investigated in a spatially coarse manner (predominantly at city level) and never contextualised with other descriptors of urban form. In this work, we explore COVID-19 and urban form in Greater London, relating a comprehensive set of morphometric descriptors (including built-up density) to COVID-19 deaths and cases, while controlling for socioeconomic, ethnicity, age, and co-morbidity. We describe urban form at individual building level and then aggregate information for official neighbourhoods, allowing for a detailed intra-urban representation. Results show that: i) control variables significantly explain more variance of both COVID-19 cases and deaths than the morphometric descriptors; ii) of what the latter can explain, built-up density is indeed the most associated, though inversely. The typical London neighbourhood with high levels of COVID-19 infections and deaths resembles a suburb, featuring a low-density urban fabric dotted by larger free-standing buildings and framed by a poorly inter-connected street network.

Related papers

• Eyes on the Streets: Leveraging Street-Level Imaging to Model Urban Crime Dynamics [0.0]
  This study addresses the challenge of urban safety in New York City by examining the relationship between the built environment and crime rates. We aim to identify how urban landscapes correlate with crime statistics, focusing on the characteristics of street views and their association with crime rates.
  arXiv  Detail & Related papers  (2024-04-15T21:33:45Z)
• Uncover the nature of overlapping community in cities [4.497897224837208]
  Our study introduces a graph-based physics-aware deep learning framework, illuminating the intricate overlapping nature inherent in urban communities. Through analysis of individual mobile phone positioning data at Twin Cities metro area (TCMA) in Minnesota, USA, our findings reveal that 95.7 % of urban functional complexity stems from the overlapping structure of communities during weekdays.
  arXiv  Detail & Related papers  (2024-01-31T22:50:49Z)
• A Contextual Master-Slave Framework on Urban Region Graph for Urban Village Detection [68.84486900183853]
  We build an urban region graph (URG) to model the urban area in a hierarchically structured way. Then, we design a novel contextual master-slave framework to effectively detect the urban village from the URG. The proposed framework can learn to balance the generality and specificity for UV detection in an urban area.
  arXiv  Detail & Related papers  (2022-11-26T18:17:39Z)
• Neural Embeddings of Urban Big Data Reveal Emergent Structures in Cities [7.148078723492643]
  We propose using a neural embedding model-graph neural network (GNN)- that leverages the heterogeneous features of urban areas. Using large-scale high-resolution mobility data sets from millions of aggregated and anonymized mobile phone users in 16 metropolitan counties in the United States, we demonstrate that our embeddings encode complex relationships among features related to urban components. We show that embeddings generated by a model trained on a different county can capture 50% to 60% of the emergent spatial structure in another county.
  arXiv  Detail & Related papers  (2021-10-24T07:13:14Z)
• Methodological Foundation of a Numerical Taxonomy of Urban Form [62.997667081978825]
  We present a method for numerical taxonomy of urban form derived from biological systematics. 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.
  arXiv  Detail & Related papers  (2021-04-30T12:47:52Z)
• Transportation Density Reduction Caused by City Lockdowns Across the World during the COVID-19 Epidemic: From the View of High-resolution Remote Sensing Imagery [48.52477000522933]
  The COVID-19 epidemic began to worsen in the first months of 2020. stringent lockdown policies were implemented in numerous cities throughout the world to control human transmission and mitigate its spread. We provide a quantitative investigation of the transportation density reduction before and after lockdown was implemented in six epicenter cities.
  arXiv  Detail & Related papers  (2021-03-02T13:45:16Z)
• C-Watcher: A Framework for Early Detection of High-Risk Neighborhoods Ahead of COVID-19 Outbreak [54.39837683016444]
  C-Watcher aims at screening every neighborhood in a target city and predicting infection risks, prior to the spread of COVID-19 from epicenters to the city. C-Watcher collects large-scale long-term human mobility data from Baidu Maps, then characterizes every residential neighborhood in the city using a set of features based on urban mobility patterns. We carried out extensive experiments on C-Watcher using the real-data records in the early stage of COVID-19 outbreaks.
  arXiv  Detail & Related papers  (2020-12-22T17:02:54Z)
• Urban Mosaic: Visual Exploration of Streetscapes Using Large-Scale Image Data [13.01318877814786]
  Urban Mosaic is a tool for exploring the urban fabric through a spatially and temporally dense data set of 7.7 million street-level images from New York City.
  arXiv  Detail & Related papers  (2020-08-31T02:23:12Z)
• City limits in the age of smartphones and urban scaling [0.0]
  Urban planning still lacks appropriate standards to define city boundaries across urban systems. ICT provide the potential to portray more accurate descriptions of the urban systems. We apply computational techniques over a large volume of mobile phone records to define urban boundaries.
  arXiv  Detail & Related papers  (2020-05-06T17:31:21Z)
• Measuring Spatial Subdivisions in Urban Mobility with Mobile Phone Data [58.720142291102135]
  By 2050 two thirds of the world population will reside in urban areas. This growth is faster and more complex than the ability of cities to measure and plan for their sustainability. To understand what makes a city inclusive for all, we define a methodology to identify and characterize spatial subdivisions.
  arXiv  Detail & Related papers  (2020-02-20T14:37:46Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.