Võrdle meetodeid
Vaata valitud meetodeid kõrvuti; erinevad read on esile tõstetud.
| Vulnerability and Damage Function Analysis× | HAZUS Loss Estimation× | |
|---|---|---|
| Valdkond | Disaster Studies | Disaster Studies |
| Perekond | Process / pipeline | Process / pipeline |
| Tekkeaasta≠ | 2003 | 2006 |
| Looja≠ | Tiziana Rossetto & Amr Elnashai; Charles Kircher, Robert Whitman & William Holmes | Federal Emergency Management Agency; Charles Kircher, Robert Whitman & William Holmes |
| Tüüp≠ | Loss-ratio estimation pipeline conditional on hazard intensity | Standardized GIS-based multi-hazard loss-estimation pipeline |
| Algallikas≠ | Rossetto, T., & Elnashai, A. (2003). Derivation of vulnerability functions for European-type RC structures based on observational data. Engineering Structures, 25(10), 1241-1263. DOI ↗ | Kircher, C. A., Whitman, R. V., & Holmes, W. T. (2006). HAZUS Earthquake Loss Estimation Methods. Natural Hazards Review, 7(2), 45-59. DOI ↗ |
| Rööpnimetused | Damage Function Estimation, Loss Ratio Curves, Mean Damage Ratio Functions, Stage-Damage Functions | Hazus-MH Loss Estimation, FEMA Hazus Methodology, Standardized Regional Loss Estimation, Hazus Earthquake Model |
| Seotud | 4 | 4 |
| Kokkuvõte≠ | Vulnerability and damage function analysis estimates the expected loss ratio, the repair or replacement cost expressed as a fraction of an asset's value, as a continuous function of hazard intensity. It is the loss-facing counterpart to fragility analysis: where fragility gives the probability of physical damage states, a vulnerability function gives money, translating intensity directly into expected fractional loss together with its uncertainty. Tiziana Rossetto and Amr Elnashai's 2003 derivation of vulnerability functions for European reinforced-concrete buildings from observed damage is a canonical empirical example, while Charles Kircher, Robert Whitman, and William Holmes's 2006 description of HAZUS earthquake methods shows the standard route of combining fragility curves with damage-state loss factors to build them analytically. The output is the per-typology relationship that, multiplied by exposed value, yields scenario and probabilistic loss. Because it bridges engineering damage and economic consequence, it is the single most influential ingredient in catastrophe and loss models. Getting the mean and the spread of the loss ratio right is what makes a risk model usable for insurance, mitigation, and policy. | 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. |
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