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ISPRS Int. J. Geo-Inf. 2016, 5(11), 218; doi:10.3390/ijgi5110218

Assessing Essential Qualities of Urban Space with Emotional and Visual Data Based on GIS Technique

1
School of Urban Design, Wuhan University, Wuhan 430072, China
2
Urban Planning Engineering Department, An-Najah National University, Nablus P.O. Box: 7, Palestine
3
Smart Cities and Regions, Austrian Institute of Technology, Vienna 1210, Austria
4
Computational Architecture, Bauhaus-University Weimar, Weimar 99423, Germany
5
SIAT, Chinese Academy of Science, Shenzhen 518055, China
6
Department of Geography, King’s College London, London WC2R 2LS, UK
7
Department of Architecture, ETH Zurich, Zurich 8093, Switzerland
8
Future Cities Laboratory, Singapore-ETH Centre, Singapore 138602, Singapore
*
Author to whom correspondence should be addressed.
Academic Editors: Bin Jiang, Constantinos Antoniou and Wolfgang Kainz
Received: 20 July 2016 / Revised: 15 November 2016 / Accepted: 17 November 2016 / Published: 22 November 2016
(This article belongs to the Special Issue Geospatial Big Data and Transport)
View Full-Text   |   Download PDF [9899 KB, uploaded 22 November 2016]   |  

Abstract

Finding a method to evaluate people’s emotional responses to urban spaces in a valid and objective way is fundamentally important for urban design practices and related policy making. Analysis of the essential qualities of urban space could be made both more effective and more accurate using innovative information techniques that have become available in the era of big data. This study introduces an integrated method based on geographical information systems (GIS) and an emotion-tracking technique to quantify the relationship between people’s emotional responses and urban space. This method can evaluate the degree to which people’s emotional responses are influenced by multiple urban characteristics such as building shapes and textures, isovist parameters, visual entropy, and visual fractals. The results indicate that urban spaces may influence people’s emotional responses through both spatial sequence arrangements and shifting scenario sequences. Emotional data were collected with body sensors and GPS devices. Spatial clustering was detected to target effective sampling locations; then, isovists were generated to extract building textures. Logistic regression and a receiver operating characteristic analysis were used to determine the key isovist parameters and the probabilities that they influenced people’s emotion. Finally, based on the results, we make some suggestions for design professionals in the field of urban space optimization. View Full-Text
Keywords: urban form; Geographical Information System; walking experience; isovists; logistic regression urban form; Geographical Information System; walking experience; isovists; logistic regression
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Li, X.; Hijazi, I.; Koenig, R.; Lv, Z.; Zhong, C.; Schmitt, G. Assessing Essential Qualities of Urban Space with Emotional and Visual Data Based on GIS Technique. ISPRS Int. J. Geo-Inf. 2016, 5, 218.

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