Analysing Cities through Cognitive Models of Geographic Space

Authors: Ed Manley*, University College London
Topics: Spatial Analysis & Modeling, Behavioral Geography, Geographic Information Science and Systems
Keywords: spatial cognition, GIS, urban
Session Type: Paper
Scheduler ID: THU-064-10:00 a.m.
Day: 4/12/2018
Start / End Time: 10:00 AM / 11:40 AM
Room: Bayside A, Sheraton, 4th Floor

We analyse urban systems using geospatial data, yet the humans at the heart of these urban systems do not view the city in the same terms. Years of research in neuroscience and behavioural geography has shown that human spatial cognition is subjective, experiential, biased by spatial features, and skewed by error. Geospatial data, on the other hand, is a near-perfect representation of the geometry and configuration of space, and thus a poor reflection of human cognition. It may be argued, therefore, that some areas of geospatial analysis and modelling are inhibited from the basic unit of analysis, and that a reconsideration of how we represent space during the analysis of cities is overdue. In this paper, exploratory methods for the development of a ‘cognitive’, augmented form of GIS are presented. Making use of conventional geospatial representations, machine learning, and network analysis methods, in addition to traditional spatial cognition experimentation, new approaches to modelling geographic space are presented. Using these new models of space, it will be explored how geospatial phenomena, and in particular, economic activity, crime patterns, and mobility can be analysed and modelled with greater specificity within a cognitive GIS framework, relative to conventional models of space.

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