Methoden vergleichen

	HAZUS Loss Estimation	Exposure Modeling (Disaster Risk)
Fachgebiet	Disaster Studies	Disaster Studies
Familie	Process / pipeline	Process / pipeline
Entstehungsjahr	2006	2017
Urheber	Federal Emergency Management Agency; Charles Kircher, Robert Whitman & William Holmes	Catalina Yepes-Estrada & Vitor Silva (GEM); GEM Foundation global exposure program
Typ	Standardized GIS-based multi-hazard loss-estimation pipeline	Spatial-inventory construction pipeline for elements at risk
Wegweisende Quelle	Kircher, C. A., Whitman, R. V., & Holmes, W. T. (2006). HAZUS Earthquake Loss Estimation Methods. Natural Hazards Review, 7(2), 45-59.	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.
Aliasnamen	Hazus-MH Loss Estimation, FEMA Hazus Methodology, Standardized Regional Loss Estimation, Hazus Earthquake Model	Exposure Database Development, Asset Inventory Modeling, Building Exposure Model, Elements at Risk Mapping
Verwandt	4	4
Zusammenfassung	HAZUS loss estimation is FEMA's standardized, GIS-based methodology for estimating the physical, social, and economic consequences of earthquakes, floods, hurricanes, and tsunamis across a region. It chains together four conceptual modules, potential hazard, inventory of the built environment, direct physical damage, and induced and economic losses, so that a consistent national framework can produce comparable loss estimates anywhere in the United States. Charles Kircher, Robert Whitman, and William Holmes's 2006 paper documents the earthquake methodology, including its use of capacity-spectrum demand estimation and lognormal fragility curves, and FEMA's technical manuals specify every default inventory, fragility, and loss parameter. The system is distinguished less by methodological novelty than by standardization: it packages decades of earthquake and flood loss science into reproducible software with vetted defaults. Planners, emergency managers, and policymakers use it for scenario planning, mitigation prioritization, and disaster response. Because its defaults are transparent and documented, HAZUS is both a working tool and a reference implementation of regional loss estimation.	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.