000004575 001__ 4575
000004575 005__ 20141118192707.0
000004575 0177_ $$2doi$$a10.3850/978-981-07-2219-7_P349

000004575 0247_ $$210.3850/978-981-07-2219-7_P349
$$adoi
000004575 04107 $$aeng
000004575 046__ $$k2012-05-23
000004575 100__ $$aCuster, Rocco
000004575 24500 $$aProbabilistic Disaggregation Model with Application to Natural Hazard Loss Estimation of Portfolios

000004575 24630 $$n5.$$pProceedings of the 5th Asian-Pacific Symposium on Structural Reliability and its Applications
000004575 260__ $$bResearch Publishing, No:83 Genting Lane, #08-01, Genting Building, 349568 SINGAPORE
000004575 506__ $$arestricted
000004575 520__ $$2eng$$aIn natural hazard loss estimation, a resolution mismatch between hazard data and aggregated exposure data is often observed. A possible solution to this issue is the disaggregation of exposure data to match the spatial resolution of hazard data. Disaggregation models available in literature are usually deterministic and make use of auxiliary indicator, such as land cover, to spatially distribute exposures. As the dependence between auxiliary indicator and disaggregated number of exposures is generally imperfect, uncertainty arises in disaggregation. 
This paper proposes a probabilistic disaggregation model and illustrates its relevance in the context of natural hazard loss assessment. Whereas deterministic disaggregation models only consider one possible geographical distribution of exposures, a probabilistic disaggregation model accommodates uncertainty on spatial distribution of the exposures. This allows for assessing tail-risks of aggregated portfolios facing natural hazard more precisely.
 The proposed model utilizes auxiliary data and models the characteristics of uncertainty of the disaggregated variables through a scaled Dirichlet distribution. 
The performance of the model and its relevance to natural hazard risk assessment is illustrated at the example of a flood hazard scenario in the Canton Bern, Switzerland. The number of buildings is given aggregated at a communal level and is to be disaggregated to a 100m raster using land cover data as auxiliary information. The disaggregated portfolio is intersected with a recent flood scenario to determine the number of buildings affected by the flood.
 The probabilistic disaggregation model performs as expected and disaggregation uncertainty is reasonably reproduced. The relevance of the probabilistic disaggregation for natural hazard loss estimation is demonstrated; i.e. by considering disaggregation uncertainty, the risk tails of portfolios subject to natural hazard increase.


000004575 540__ $$aText je chráněný podle autorského zákona č. 121/2000 Sb.
000004575 653__ $$aDisaggregation, Probabilistic model, Dirichlet distribution, Compositional data, Indicator, Insurance portfolio, Natural hazard, Flood risk.

000004575 7112_ $$a5th Asian-Pacific Symposium on Structural Reliability and its Applications$$cSingapore (SG)$$d2012-05-23 / 2012-05-25$$gAPSSRA2012
000004575 720__ $$aCuster, Rocco$$iNishijima, Kazuyoshi
000004575 8560_ $$ffischerc@itam.cas.cz
000004575 8564_ $$s181893$$uhttps://invenio.itam.cas.cz/record/4575/files/P349.pdf$$yOriginal version of the author's contribution as presented on CD, .
000004575 962__ $$r4180
000004575 980__ $$aPAPER