Exploring Urban Form Through Openstreetmap Data: A Visual Introduction

Geoff Boeing

doi:10.2139/ssrn.3680845

Abstract

This chapter introduces OpenStreetMap—a crowd-sourced, worldwide mapping project and geospatial data repository—to illustrate its usefulness in quickly and easily analyzing and visualizing planning and design outcomes in the built environment. It demonstrates the OSMnx toolkit for automatically downloading, modeling, analyzing, and visualizing spatial big data from OpenStreetMap. We explore patterns and configurations in street networks and buildings around the world computationally through visualization methods—including figure-ground diagrams and polar histograms—that help compress urban complexity into comprehensible artifacts that reflect the human experience of the built environment. Ubiquitous urban data and computation can open up new urban form analyses from both quantitative and qualitative perspectives.

Highlights

New technologies have recently changed how we can see, understand, and plan the urban form
Because we represent all of these street networks here at the same scale—one square mile—it is easy to compare the qualitative urban patterns in these different cities to one another
Consider the design principles manifested in the urban fabric—and their implications for human cognition and comfort from the perspectives of biophilia, thigmotaxis, and prospect-refuge theory (Sussman and Hollander, 2015)

Summary

Introduction

New technologies have recently changed how we can see, understand, and plan the urban form. Cognitive science and biometric tools such as eye-tracking technology help researchers study human psychological and physiological experiences in the built environment to advance evidence-based urban design (Sussman and Hollander, 2015; Sussman and Ward, 2016). User-generated spatial data can even help us introspectively unpack planning and design histories and the spatial logics they manifest, which in turn shape human behavior and experience. This chapter explores a growing source of big data on spatial infrastructure, to reflect on how the built environment constrains and shapes the human experience in urban space. Street networks are perhaps the paradigmatic example of such infrastructure Urban planners model these networks to investigate trips and traffic, explore urban planning and design histories, and better understand the psychology of human navigation and wayfinding in the built environment. We will discuss what it is, how to use it, and how it can help us critique and improve the urban experience

Background and Methods

Results and Discussion

Conclusions