Abstract

Large-scale impacts from natural disasters suffered by society encourage researchers and public agencies to develop methods to evaluate, mitigate, respond, and recover from these events. A key aspect for the calculation of the potential earthquake losses is to properly describe the characteristics and value of assets exposed to seismic hazard. This article describes a methodology to develop an exposure model at a census-block resolution for residential structures in Chile using statistical data. The methodology is based on three steps: (1) obtaining dwelling count, construction material and location from census data, (2) defining classification rules for dwellings associated with houses and apartment buildings, and (3) assigning structural typologies and replacement cost. The resulting exposure model consists of a database with the number of residential structures classified into 18 structural typologies at each census block and the associated replacement cost. A total of 4,259,804 residential structures were identified in the national exposure model. Overall, clay brick and concrete block masonry account for 53.5 % of the structures of the country followed by timber (33.7 %), reinforced concrete (8.1 %), and adobe (4.6 %). Also, a methodology using remote digital survey techniques is proposed and used to obtain local exposure models for the cities of Iquique, Rancagua, and Osorno. The results of the national exposure model are compared with the local exposure models. An important feature of the proposed methodologies is that the building stock is classified into structural typologies, which is a key aspect for conducting seismic risk assessment. The methodologies used to construct the national and local exposure models may be extrapolated to other countries by adjusting the classification rules. The exposure models that were constructed represent an important input for risk calculations, by improving the technical capabilities for seismic risk management of the country.

Keywords

Exposure model, Seismic vulnerability, Residential building stock, Seismic risk, Digital surveys, Remote sensing

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