Catastrophic risk management using spatial adaptive Monte Carlo optimization

Ermolieva, T., Fischer, G., & Obersteiner, M. ORCID: https://orcid.org/0000-0001-6981-2769 (2010). Catastrophic risk management using spatial adaptive Monte Carlo optimization. In: Risk Management. Eds. Jordão, B. & Sousa, E., pp. 307-326 UK: Nova Science Publishers, Inc.. ISBN 978-160876011-4

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Abstract

In this chapter, the authors present an integrated approach of catastrophic risk management based on data from geographic information systems (GIS). The methodology enables the analysis of the spatial and temporal heterogeneity of various agents (stakeholders) and offers solutions for coherent, comprehensive and robust policy responses. Using the spatial adaptive Monte Carlo (stochastic) optimization procedure allows to analyze a variety of complex interactions between decisions and risks in order to find robust optimal portfolios of risk management measures for decreasing regional vulnerability with regard to economic, financial, and human losses. The model addresses the specifics of catastrophic risks, including the lack of information, the need for long-term perspectives and geographically explicit models, and a multi-agent decision making structure. The approach is illustrated with a case study of earthquake risk management in the Tuscany region of Italy.

Item Type:	Book Section
Research Programs:	Ecosystems Services and Management (ESM) Water (WAT)
Depositing User:	Luke Kirwan
Date Deposited:	07 Jun 2017 14:08
Last Modified:	27 Aug 2021 17:29
URI:	https://pure.iiasa.ac.at/14651

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