Toward cities without slums: Topology and the spatial evolution of neighborhoods

Brelsford, Christa; Martin, Taylor; Hand, Joe; Bettencourt, Luís M. A.

doi:10.1126/sciadv.aar4644

Cited by 73 publications

(42 citation statements)

References 35 publications

(62 reference statements)

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“…OSM data and OSMnx provide planning practitioners an easy-to-use tool to visualize and examine street networks and building footprints as a planning and communication tool. The data in Figure 2, for instance, could help planners and residents in Monrovia and Portau-Prince collaboratively study how to percolate formal circulation networks into these informal settlements with minimal disruption to the existing urban fabric, homes, and livelihoods (Brelsford et al, 2019(Brelsford et al, , 2018(Brelsford et al, , 2015Masucci et al, 2013;Zook et al, 2010).…”

Section: Urban Circulation Systems and Spatial Logicsmentioning

confidence: 99%

Spatial information and the legibility of urban form: Big data in urban morphology

Boeing

2021

International Journal of Information Management

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Urban planning and morphology have relied on analytical cartography and visual communication tools for centuries to illustrate spatial patterns, propose designs, compare alternatives, and engage the public. Classic urban form visualizations -from Giambattista Nolli's ichnographic maps of Rome to Allan Jacobs's figure-ground diagrams of city streets -have compressed physical urban complexity into easily comprehensible information artifacts. Today we can enhance these traditional workflows through the Smart Cities paradigm of understanding cities via user-generated content and harvested data in an information management context. New spatial technology platforms and big data offer new lenses to understand, evaluate, monitor, and manage urban form and evolution. This paper builds on the theoretical framework of visual cultures in urban planning and morphology to introduce and situate computational data science processes for exploring urban fabric patterns and spatial order. It demonstrates these workflows with OSMnx and data from OpenStreetMap, a collaborative spatial information system and mapping platform, to examine street network patterns, orientations, and configurations in different study sites around the world, considering what these reveal about the urban fabric. The age of ubiquitous urban data and computational toolkits opens up a new era of worldwide urban form analysis from integrated quantitative and qualitative perspectives.Cite: Boeing, G.

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Section: Urban Circulation Systems and Spatial Logicsmentioning

confidence: 99%

Spatial information and the legibility of urban form: Big data in urban morphology

Boeing

2021

International Journal of Information Management

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“…Explicitly structuring these networks in an attempt to equalise distribution could take the form of co-locating resources and end-users to the greatest extent possible, such as locating solar panels or other forms of renewable energy on homes and businesses [40], or increasing the integration of locally-sourced products into a community's food system [41]. Additional efforts, such as intentionally improving RADE network infrastructure to currently underserved populations of end users [42], could also be a significant step in the right direction. The question remains, however, as to whether even the best efforts at improving equality of distribution can offset the argued thermodynamic trajectory for systems to develop increasing patterns of consumption and dissipation (see e.g.…”

Section: Plos Onementioning

confidence: 99%

Trajectories toward maximum power and inequality in resource distribution networks

2020

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Resource distribution networks are the infrastructure facilitating the flow of resources in both biotic and abiotic systems. Both theoretical and empirical arguments have proposed that physical systems self-organise to maximise power production, but how this trajectory is related to network development, especially regarding the heterogeneity of resource distribution in explicitly spatial networks, is less understood. Quantifying the heterogeneity of resource distribution is necessary for understanding how phenomena such as economic inequality or energetic niches emerge across socio-ecological and environmental systems. Although qualitative discussions have been put forward on this topic, to date there has not been a quantitative analysis of the relationship between network development, maximum power, and inequality. This paper introduces a theoretical framework and applies it to simulate the power consumption and inequality in generalised, spatially explicit resource distribution networks. The networks illustrate how increasing resource flows amplify inequality in power consumption at network end points, due to the spatial heterogeneity of the distribution architecture. As increasing resource flows and the development of hierarchical branching can both be strategies for increasing power consumption, this raises important questions about the different outcomes of heterogeneous distribution in natural versus human-engineered networks, and how to prioritise equity of distribution in the latter.

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“…Expanding quality-of-life and economic development opportunities for the inhabitants of informal settlements depends on an accurate picture at the city level of which neighborhoods are critically under-serviced and which could prosper immediately with small and focused upgrading interventions [13]. Though determinations of whether a neighborhood is under-serviced depends greatly on local concerns, a topological analysis of building footprints in relation to the formal road network offers a quantitative criterion [14]. With a topological approach, it is possible to determine the number of building parcels that must be crossed to access the existing street network (and therefore, emergency services, sanitation, clean water, etc.).…”

Section: Contextmentioning

confidence: 99%

“…With a topological approach, it is possible to determine the number of building parcels that must be crossed to access the existing street network (and therefore, emergency services, sanitation, clean water, etc.). Focusing on the topologically-invariant properties of maps also allows us to analyze cities without developing approaches that depend on detailed morphology or visual clues, which are all context-and history-dependent [14].…”

Section: Contextmentioning

confidence: 99%

Worldwide Detection of Informal Settlements via Topological Analysis of Crowdsourced Digital Maps

Soman¹,

Beukes²,

Nederhood³

et al. 2020

Preprint

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The recent growth of high-resolution spatial data, especially in developing urban environments, is enabling new approaches to civic activism, urban planning and the provision of services necessary for sustainable development. A special area of great potential and urgent need deals with urban expansion through informal settlements (slums). These neighborhoods are too often characterized by a lack of connections, both physical and socioeconomic, with detrimental effects to residents and their cities. Here, we show how a scalable computational approach based on the topological properties of digital maps can identify local infrastructural deficits and propose context-appropriate minimal solutions. We analyze 1 terabyte of OpenStreetMap (OSM) crowdsourced data to create worldwide indices of street block accessibility and local cadastral maps and propose infrastructure extensions with a focus on 120 Low and Middle Income Countries (LMIC) in the Global South. We illustrate how the lack of physical accessibility can be identified in detail, how the complexity and costs of solutions can be assessed and how detailed spatial proposals are generated. We discuss how these diagnostics and solutions provide a multiscalar set of new capabilities – from individual neighborhoods to global regions – that can coordinate local community knowledge with political agency, technical capability, and further research.

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Toward cities without slums: Topology and the spatial evolution of neighborhoods

Abstract: Describing the mathematical logic of cities shows a way to help slum residents make space for streets where they do not yet exist.

Cited by 73 publications

References 35 publications

Spatial information and the legibility of urban form: Big data in urban morphology

Spatial information and the legibility of urban form: Big data in urban morphology

Trajectories toward maximum power and inequality in resource distribution networks

Worldwide Detection of Informal Settlements via Topological Analysis of Crowdsourced Digital Maps

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