Tag: transect analysis

We conducted an experiment to explore how Machine Learning (ML) can be utilized as a tool in urban studies research. The current study aims to compare two methodologies to identify urban indicators of the residents’ well-being focusing on three transects across two local watersheds in Jacksonville. The study is framed within the theory of transect analysis. The goal of this experiment was to compare an analogical transect analysis method (AT) to Machine Learning one (MLT) to understand (1) what kind of contribution the latter approach can provide to the development of transect analysis methodologies, and (2) if and how it can connect digitally generated site analysis to local knowledge.The experiment’s findings highlight the ability of the ML algorithms to find noticeable patterns of built environment from aerial imagery. However, local knowledge is indispensable to interpret results in a meaningful way. The combination of the two approaches emphasizes the complementary nature of them and shows how ML methods can be a tool at the service of communities.