Dietwald Gruehn

You are already at the latest version This study examines pedestrian perceptions of streetscapes in Isfahan’s cultural heritage site by integrating deep learning–based image segmentation with urban morphological analysis. Using a U-Net model applied to First-Person Pedestrian View (FPPV) images, five perceptual indices (imageability, enclosure, human scale, greenness, and walking index) were quantified to assess their influence on pedestrian experience.

1. Introduction Walkability, as an attribute of the built environment, lies at the center of debates in urban studies regarding the creation of social and vibrant cities through a sustainable strategy for developing public spaces inclusively. It plays a pivotal role in influencing urban planning decisions for streets in the historic city center, guided by local government policies [1,2,3,4,5].

1. Introduction Developing healthy cities and communities is necessary, especially in light of the impacts of climate change. A healthy and sustainable urban environment consists of a series of pedestrian walkways for commuting, exercising, and leisure use [1]. Walking is considered the most widespread mode of transport [2] as it is a crucial link between the other modes, and pedestrian activity helps to fulfill recreational requirements [3].