Published June 8, 2026 | Version 1.0.0
Dataset Open

A City-Scale Dataset of Annual Spatiotemporal Maps of Building Exposure and Physical Vulnerability in Quezon City, Philippines (2016–2030) via Graph Variational State-Space Model (GraphVSSM)

  • 1. University of Cambridge
  • 2. UKRI Centre for Doctoral Training (CDT) in the Application of Artificial Intelligence to the study of Environmental Risks (AI4ER)
  • 3. Cambridge University Centre for Risk in the Built Environment (CURBE)
  • 4. ROR icon Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)
  • 5. ROR icon University of Bonn

Description

A city-scale demonstration of Graph Variational State-Space Model (GraphVSSM) for various indicators of regional exposure and physical vulnerability in Quezon City in the Philippines as a case study.

Notes (English)

History of Versions: 

  • v0.0.0 (2025-08-01): Initial and anonymized upload for scientific double-blind peer review purposes
  • v1.0.0 (2026-06-08): Post-processed spatiotemporal maps of exposure (height and floor levels) and physical vulnerability (building typology)

Files

PreprintEarthArXiv.pdf

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Additional details

Funding

UK Research and Innovation
UKRI Centre for Doctoral Training in Application of Artificial Intelligence to the study of Environmental Risks (AI4ER) EP/S022961/1