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Exposure Modeling (Disaster Risk)

Exposure modeling builds the geolocated inventory of assets, people, and values that are at risk from a hazard, the elements-at-risk layer that, together with hazard and vulnerability, determines disaster loss. It answers what is where and worth how much: how many buildings of each construction type sit in each location, their replacement value, and the population that occupies them at different times of day. Catalina Yepes-Estrada, Vitor Silva, and colleagues' 2017 South America residential exposure model and Vitor Silva and colleagues' 2020 global seismic risk model exemplify the modern approach of synthesizing census statistics, building characteristics, and expert mapping into open, georeferenced databases. Because loss equals hazard acting on exposure through vulnerability, exposure accuracy often dominates the realism of a risk estimate. Exposure models feed catastrophe models, HAZUS-style loss estimation, and probabilistic risk metrics like average annual loss. Constructing them well, with consistent taxonomy, credible values, and validated counts, is foundational to all downstream disaster risk analysis.

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出典

  1. Yepes-Estrada, C., Silva, V., Valcárcel, J., Acevedo, A. B., Tarque, N., Hube, M. A., Coronel, G., & Santa María, H. (2017). Modeling the Residential Building Inventory in South America for Seismic Risk Assessment. Earthquake Spectra, 33(1), 299-322. DOI: 10.1193/101915EQS155DP
  2. Silva, V., Amo-Oduro, D., Calderon, A., Costa, C., Dabbeek, J., Despotaki, V., et al. (2020). Development of a global seismic risk model. Earthquake Spectra, 36(1_suppl), 372-394. DOI: 10.1177/8755293019899953

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ScholarGate. (2026, June 23). Exposure Modeling (Spatial Inventory of Assets, Values and Occupants at Risk). ScholarGate. https://scholargate.app/ja/disaster-studies/exposure-modeling

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ScholarGateExposure Modeling (Disaster Risk) (Exposure Modeling (Spatial Inventory of Assets, Values and Occupants at Risk)). 2026-06-24に以下より取得 https://scholargate.app/ja/disaster-studies/exposure-modeling · データセット: https://doi.org/10.5281/zenodo.20539026