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

Geoff Boeing

International Journal of Information Management, 2021, vol. 56, issue C

Abstract: Urban planning and morphology have relied on analytical cartography and visual communication tools for centuries to illustrate spatial patterns, conceptualize proposed 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.

Keywords: OpenStreetMap; Urban design; Urban form; Urban morphology; Urban planning; Visualization (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (9)

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Working Paper: Spatial Information and the Legibility of Urban Form: Big Data in Urban Morphology (2019)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ininma:v:56:y:2021:i:c:s0268401219302154

DOI: 10.1016/j.ijinfomgt.2019.09.009

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