2019
DOI: 10.2139/ssrn.3462078
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Spatial Information and the Legibility of Urban Form: Big Data in Urban Morphology

Abstract: A B S T R A C TUrban 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 visualizationsfrom Giambattista Nolli's ichnographic maps of Rome to Allan Jacobs's figure-ground diagrams of city streetshave compressed physical urban complexity into easily comprehensible information artifacts. Today we can enhance these traditional workfl… Show more

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Cited by 5 publications
(7 citation statements)
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“…We hope that the concept of the ClockBoard zoning system presented in this paper, and the ease with which open access data representing 'ClockBoards' for different cities can be created, will encourage more quantitative urban analytical research comparing different cities, building on recent work in the field [19]. Moreover, we hope that the implementation of the concept in open source software encourages other zoning systems with different attributes to be developed, to meet different criteria than those that motivated the design of the ClockBoard system.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…We hope that the concept of the ClockBoard zoning system presented in this paper, and the ease with which open access data representing 'ClockBoards' for different cities can be created, will encourage more quantitative urban analytical research comparing different cities, building on recent work in the field [19]. Moreover, we hope that the implementation of the concept in open source software encourages other zoning systems with different attributes to be developed, to meet different criteria than those that motivated the design of the ClockBoard system.…”
Section: Discussionmentioning
confidence: 99%
“…The visualisation of direction has been driven by new navigational requirements and datasets, with circular compasses and displays common in land and sea navigational systems since the mid 1900s [18]. Circular visualisation techniques, in the form of rose diagrams, were used in a more recent study to indicate the most common road directions relative to North [19]. The resulting visualisations are attractive and easy to interpret, but are not geographical, in the sense that they cannot meaningfully be overlaid on mapped data.…”
Section: Introductionmentioning
confidence: 99%
“…The World Bank collects building footprint data then trains a random forest model to identify OpenStreetMap coverage gaps that can inform future crowd‐sourcing efforts and mapping campaigns (Jones, 2019). Boeing (2020b) explores the growing role of big data in computational urban morphology and visual analytics (Figure 1). Boeing (2019b) conducts a cluster analysis of urban street networks around the world to theorize how planners produce different forms of geometric spatial order, illustrated in Figure 2.…”
Section: Empirical Street Network Science With Osmnxmentioning
confidence: 99%
“…Across many research areas there is a trend towards big data analysis to explore urban areas [ 5 ], including using building datasets and morphology metrics. This trend has been noted previously as part of the growing use of computational methods and larger datasets more generally and particularly in geographic data science [ 15 ].…”
Section: Introductionmentioning
confidence: 99%
“…Identifying and mapping the footprints of structures and their agglomerations into human settlements is a first step towards improving our understanding of local population patterns, providing services and utilities to all areas, and mapping building stock and urban extents [1][2][3][4]. Within the field of planning and particularly the area of urban morphology, the form and the patterns of buildings in space have been a means to explore the history of cities and the political economic and social forces shaping their developments [5,6]. The visible patterns and features of the built environment can be quantified with a wide range of morphology metrics [7].…”
Section: Introductionmentioning
confidence: 99%