Christopher W. Zobel. (2013). Analytically comparing disaster recovery following the 2012 derecho. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 678–682). KIT; Baden-Baden: Karlsruher Institut fur Technologie. Abstract: This work in progress paper discusses analytically characterizing nonlinear recovery behavior through the context of the derecho windstorm that struck the mid-Atlantic United States in the summer of 2012. The focus is on the recovery efforts of the Appalachian Power Company, and the discussion includes a look at the need for communicating the progress of such recovery efforts to the public. Publicly available recovery data is analyzed and compared with respect to the relative behaviors exhibited by two different nonlinear recovery processes, and some of the implications for understanding the efficiency of different disaster recovery operations are discussed. Keywords: Disasters; Electric utilities; Information systems; Appalachian; Derecho; Disaster recovery; Mid-Atlantic; Power company; Quantitative modeling; Recovery process; Work in progress; Recovery Track: Analytical Modelling and Simulation Share to FB \| Save citation: RTF PDF LaTeX \| Export record: Atom XML MODS XML OAI_DC XML ODF XML SRW_DC XML SRW_MODS XML
Diana Contreras, Thomas Blaschke, Stefan Kienberger, & Peter Zeil. (2011). Spatial vulnerability indicators: Measuring recovery processes after earthquakes. In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM. Abstract: In order to analyze and evaluate any post-disaster phases it is necessary to address the pre-existent vulnerability conditions. The methodology consists of four steps: the first step comprises of a review of vulnerability and recovery indicators; the second step is to identify indicators based on spatial variables; the third step is to find the common variables among the subsets of spatial variables from vulnerability and recovery indicators; and the fourth step more pragmatic, is an investigation of the availability of data. The initial results are the set of vulnerability and recovery indicators. Reducing the set of indicators to the indicators represented in a spatial context and the indicators with common features of vulnerability and recovery indices bears the risk to ignore some important single indicators; nevertheless, the added value of the on-going research is to show the advantages of using indicators based on spatial variables. Keywords: Earthquakes; Indicators (instruments); Information systems; Common features; Post disasters; Recovery process; Spatial; Spatial context; Spatial variables; Vulnerability; Vulnerability indicators; Recovery Track: Planning and Foresight Share to FB \| Save citation: RTF PDF LaTeX \| Export record: Atom XML MODS XML OAI_DC XML ODF XML SRW_DC XML SRW_MODS XML

Abstract: This work in progress paper discusses analytically characterizing nonlinear recovery behavior through the context of the derecho windstorm that struck the mid-Atlantic United States in the summer of 2012. The focus is on the recovery efforts of the Appalachian Power Company, and the discussion includes a look at the need for communicating the progress of such recovery efforts to the public. Publicly available recovery data is analyzed and compared with respect to the relative behaviors exhibited by two different nonlinear recovery processes, and some of the implications for understanding the efficiency of different disaster recovery operations are discussed.

Abstract: In order to analyze and evaluate any post-disaster phases it is necessary to address the pre-existent vulnerability conditions. The methodology consists of four steps: the first step comprises of a review of vulnerability and recovery indicators; the second step is to identify indicators based on spatial variables; the third step is to find the common variables among the subsets of spatial variables from vulnerability and recovery indicators; and the fourth step more pragmatic, is an investigation of the availability of data. The initial results are the set of vulnerability and recovery indicators. Reducing the set of indicators to the indicators represented in a spatial context and the indicators with common features of vulnerability and recovery indices bears the risk to ignore some important single indicators; nevertheless, the added value of the on-going research is to show the advantages of using indicators based on spatial variables.

Keywords: Earthquakes; Indicators (instruments); Information systems; Common features; Post disasters; Recovery process; Spatial; Spatial context; Spatial variables; Vulnerability; Vulnerability indicators; Recovery

Track: Planning and Foresight

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