Navigation failed to load. If you are on the UNDRR office network, your browser may be blocking access to external resources. Learn how to allow access.
This study evaluates how attention mechanisms and explainable AI (XAI) techniques can improve the reliability and interpretability of deep learning models for post-disaster building damage assessment using satellite imagery.
International Journal of Disaster Risk Reduction (Elsevier)
This entry explains the concept, methodology, and importance of post-disaster damage and needs assessment (PDNA) in supporting effective recovery, reconstruction, and disaster risk reduction.
Designed to walk ADB staff through a Post-Disaster Needs Assessment simulation, this handbook outlines training schedules, introduces methodologies, and provides practical exercises to identify and analyze the broad impacts of a disaster.
In partnership the Community Outcomes and Recovery Sub-committee, Queensland Reconstruction Authority and the National Emergency Management Agency developed the National Disaster Recovery Needs Assessment Guidelines.
The guidelines are a set of documents for assessing the effects and impacts of disasters, as well as providing a methodology for planning for the disaster recovery.