Original paper
Measuring social, environmental and health inequalities using deep learning and street imagery
Abstract
Cities are home to an increasing majority of the world's population. Currently, it is difficult to track social, economic, environmental and health outcomes in cities with high spatial and temporal resolution, needed to evaluate policies regarding urban inequalities. We applied a deep learning approach to street images for measuring spatial distributions of income, education, unemployment, housing, living environment, health and crime. Our model...
Paper Details
Title
Measuring social, environmental and health inequalities using deep learning and street imagery
Published Date
Apr 18, 2019
Journal
Volume
9
Issue
1
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