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Al perceives like a local: predicting citizen deprivation perception using satellite imagery

Environmental Studies and Forestry

Al perceives like a local: predicting citizen deprivation perception using satellite imagery

A. Abascal, S. Vanhuysse, et al.

This innovative research by Angela Abascal and colleagues explores how satellite imagery and AI can predict citizen perceptions of deprivation in urban settings. By leveraging deep learning and citizen science, the team effectively prioritizes urban needs and guides policy implementation for sustainable development.

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Playback language: English
Abstract
This research develops a method to predict citizens' perception of deprivation in urban areas using satellite imagery, citizen science, and AI. A deprivation perception score was computed from slum-citizens' votes, and AI was used to model this score. Deep learning outperformed conventional machine learning, effectively predicting perception. This tool can help prioritize citizens' requirements and implement urban upgrading policies aligned with SDG-11.
Publisher
npj Urban Sustainability
Published On
Mar 29, 2024
Authors
Angela Abascal, Sabine Vanhuysse, Taïs Grippa, Ignacio Rodriguez-Carreño, Stefanos Georganos, Jiong Wang, Monika Kuffer, Pablo Martinez-Diez, Mar Santamaria-Varas, Eleonore Wolff
Tags
deprivation
urban areas
citizen science
satellite imagery
AI
deep learning
SDG-11

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