Architecture Program
Date of this Version
2022
Citation
Published in Artificial Intelligence in Urban Planning and Design, ed. Imdat As, Prithwish Basu, & Pratap Talwar (2022), pp. 121–138.
doi:10.1016/B978-0-12-823941-4.00018-4
Abstract
The application of deep learning to urban health analysis is in its early stages, but offers new and promising capabilities in using large image-based datasets to better understand the built environment and its effects on human health. This chapter will introduce and explore some of these capabilities, providing the allied design fields with a roadmap of this emerging area of research, its potentials, and current challenges. The chapter begins with a brief overview of existing research related to urban morphology and health, in which precedent work using traditional methods as well as deep learning are introduced. Next, research is presented demonstrating methods for the use of discriminative and generative deep learning processes for both urban health estimation and analysis. The chapter then concludes with a discussion of key challenges and directions for future work in this emerging field of research.
Comments
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