Yürünebilirlik için sayısal kent analitiği: Çankaya, Ankara örneği

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 and level 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 evaluated computationally. The main goal of the research is to explore the methods of computational urban analytics in 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, 115 neighborhoods were assessed based on the macro-scale urban features, while in the second stage, nine neighborhoods of those 115 were investigated according to the micro-scale urban features. In the third stage, these nine neighborhoods were re-considered for estimation of the walkability level for older adults. The exploratory analysis is comprised of the 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 scope of computational urban analytics methods on walkability assessment was limited by the accuracy and accessibility of urban data.