A data-driven approach to rapidly estimate recovery potential to go beyond building damage after disasters

• Main Authors: Loos, Sabine, Lallemant, David, Khan, Feroz, McCaughey, Jamie W. W., Banick, Robert, Budhathoki, Nama, Baker, Jack W. W.
• Other Authors: Asian School of the Environment
• Format: Article
• Language: English
• Published: 2023
• Subjects: Engineering::Environmental engineering; Social Vulnerability; Natural Hazards
• Online Access: https://hdl.handle.net/10356/171501
• Institution: Nanyang Technological University

Following a disaster, crucial decisions about recovery resources often prioritize immediate damage, partly due to a lack of detailed information on who will struggle to recover in the long term. Here, we develop a data-driven approach to provide rapid estimates of non-recovery, or areas with the pot...