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Open AccessArticle

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

School of Urban Design, Wuhan University, Wuhan 430072, China
Urban Planning Engineering Department, An-Najah National University, Nablus P.O. Box: 7, Palestine
Smart Cities and Regions, Austrian Institute of Technology, Vienna 1210, Austria
Computational Architecture, Bauhaus-University Weimar, Weimar 99423, Germany
SIAT, Chinese Academy of Science, Shenzhen 518055, China
Department of Geography, King’s College London, London WC2R 2LS, UK
Department of Architecture, ETH Zurich, Zurich 8093, Switzerland
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
ISPRS Int. J. Geo-Inf. 2016, 5(11), 218;
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)
PDF [9899 KB, uploaded 22 November 2016]


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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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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