‘Serial vision’ as a method for exploring street vitality and urban change

Abstract

In this paper, I adapt Cullen’s ‘serial vision’ approach to isovists to create a series of methods that explores street vitality and urban change using morphologic and semantic information in urban spaces. I determine a series of vantage points on a particular path on both Nolli maps and corresponding street view images. The images illustrate a personal eyelevel experience of a street or path, such as street view tools. The proposed approach brings together two types of data at every vantage point on a path: built form data – based on some isovist characteristics such as area, compactness, perimeter and occlusivity and semantic data – defining the signs, texts and functions on the images using street view data and AI text recognition. I illustrate street vitality and urban change explorations with several examples of paths in different gentrifying areas of Istanbul that are significant to the related comparison. I explore possible interrelations between morphologic and semantic characteristics of space. The findings of the study show that there are correlations between street vitality and urban change levels and the diversity of visual revelations.