@article{27171,
  author = {Chung Yan Shih and Corinne D Scown and Lucio Soibelman and H. H Scott Matthews and James H Garrett and Keith Dodrill and Sandra McSurdy},
  title = {Data Management for Geospatial Vulnerability Assessment of Interdependencies in U.S. Power Generation},
  abstract = {<p>Critical infrastructures maintain our society’s stability, security, and quality of life. These systems are also interdependent, which means that the disruption of one infrastructure system can significantly impact the operation of other systems. Because of the heavy reliance on electricity production, it is important to assess possible vulnerabilities. Determining the source of these vulnerabilities can provide insight for risk management and emergency response efforts. This research uses data warehousing and visualization techniques to explore the interdependencies between coal mines, rail transportation, and electric power plants. By merging geospatial and nonspatial data, we are able to model the potential impacts of a disruption to one or more mines, rail lines, or power plants, and visually display the results using a geographical information system. A scenario involving a severe earthquake in the New Madrid Seismic Zone is used to demonstrate the capabilities of the model when given input in the form of a potentially impacted area. This type of interactive analysis can help decision makers to understand the vulnerabilities of the coal distribution network and the potential impact it can have on electricity production.</p>},
  year = {2009},
  journal = {Journal of Infrastructure Systems},
  volume = {15},
  pages = {179-189},
  month = {09/2009},
  doi = {10.1061/(ASCE)1076-0342(2009)15:3(179)},
}