A Local-Scale Dataset of Annual Spatiotemporal Maps of Physical Vulnerability in the Cyclone-Impacted Coastal Khurushkul Community (Bangladesh) and Mudslide-Affected Freetown (Sierra Leone) (2016–2023) via Graph Variational State-Space Model (GraphVSSM)
UKRI| UKRI Centre for Doctoral Training in Application of Artificial Intelligence to the study of Environmental Risks (AI4ER)
Dimasaka, Joshua; Geiß, Christian; So, Emily;
A Local-Scale Dataset of Annual Spatiotemporal Maps of Physical Vulnerability in the Cyclone-Impacted Coastal Khurushkul Community (Bangladesh) and Mudslide-Affected Freetown (Sierra Leone) (2016–2023) via Graph Variational State-Space Model (GraphVSSM)
A high-resolution demonstration of yearly changes in physical vulnerability from 2016 to 2023 in the cyclone-impacted coastal Khurushkul community in Bangladesh (also known as "the world's largest climate refugee rehabilitation project") and mudslide-affected Freetown in Sierra Leone in 2017. File Descriptions: Khurushkul_BGD_METEOR_prior.zip - Prior Input Khurushkul_BGD_GoogleOpen25D_BldgHeight.tif - Covariate Input Khurushkul_BGD_OV_V.zip - Posterior Output Freetown_SLE_METEOR_prior.zip - Prior Input Freetown_SLE_GoogleOpen25D_BldgHeight.tif- Covariate Input Freetown_SLE_OV_V.zip - Posterior Output
History of Versions: v0.0.0 (2025-08-01): Initial and anonymized upload for scientific peer review purposes
- University of Cambridge United Kingdom
- University of Bonn Germany
- German Aerospace Center Germany
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