Spatial Information and the Legibility of Urban Form: Big Data in Urban Morphology

Forthcoming, International Journal of Information Management, DOI/10.1016/j.ijinfomgt.2019.09.009

20 Pages Posted: 11 Oct 2019

See all articles by Geoff Boeing

Geoff Boeing

University of Southern California - Sol Price School of Public Policy

Date Written: September 30, 2019

Abstract

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.

Keywords: Cartography, Complexity, Data Science, GIS, Network Analysis, Network Science, Nolli Map, OpenStreetMap, Orientation, OSMnx, Polar Histogram, Python, Rose Diagram, Smart Cities, Spatial Analysis, Spatial Networks, Street Network, Transportation, Urban Design

JEL Classification: R3, R4

Suggested Citation

Boeing, Geoff, Spatial Information and the Legibility of Urban Form: Big Data in Urban Morphology (September 30, 2019). Forthcoming, International Journal of Information Management, DOI/10.1016/j.ijinfomgt.2019.09.009 . Available at SSRN: https://ssrn.com/abstract=3462078 or http://dx.doi.org/10.2139/ssrn.3462078

Geoff Boeing (Contact Author)

University of Southern California - Sol Price School of Public Policy ( email )

Los Angeles, CA 90089-0626
United States

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
71
Abstract Views
311
rank
349,398
PlumX Metrics