Computational urban analyticsfor walkability: Çankaya, Ankara case

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2021-2-08
Ardıç, Sabiha İrem
The complexity of the built environment and the number of components acting upon the cities are increasing and in constant transformation. Analyzing the quality of urban spaces is becoming difficult due to the scale andlevel of interconnectivity between urban data. However, advances in technologies, particularly in computational urban analytics methods, have the potential to facilitate the collection, measurement, and analysis of urban metrics relevant to urban design. Walkability is an important measure related to sustainable urban mobility with its potentials to be evaluatedcomputationally. Themain goalof the research is to explore the methods of computational urban analyticsin assessing walkability at different measurement scales, which are neighborhood and street, and for a specific target group, older adults(over 60). The study consists of three stages implementing in the neighborhoods of Çankaya, Ankara. In the first stage of the study, 115neighborhoods were assessed based on the macro-scale urban features, while in the second stage, nine neighborhoodsof those 115were investigated according to the micro-scale urban features. In the third stage, these nine neighborhoods were re-considered for estimation ofthewalkability level for older adults. The exploratory analysis is comprised ofthe big data approach, semantic segmentation, trip generation, and geometrical operations on 3D digital models. The results showed that the walkability level of a neighborhood could differ based on the considered factors. It was determined that the scopeof computational urban analytics methods on walkability assessment was limited by the accuracy and accessibilityof urban data.

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Citation Formats
S. İ. Ardıç, “Computational urban analyticsfor walkability: Çankaya, Ankara case,” M.S. - Master of Science, Middle East Technical University, 2021.