Authors
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Varun Ramachandran
Department of Engineering Management & Systems Engineering, Missouri University of Science and Technology
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Suzanna K Long
Department of Engineering Management & Systems Engineering, Missouri University of Science and Technology
https://orcid.org/0000-0001-6589-5528
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Tom Shoberg
U.S. Geological Survey, Center for Geospatial Information Science (CEGIS)
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Steven M Corns
Department of Engineering Management & Systems Engineering, Missouri University of Science and Technology
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Héctor J Carlo
Department of Industrial Engineering, University of Puerto Rico at Mayaguez
Keywords:
GIS, Extreme Events, Critical Infrastructure, Urban Supply Chain, Logistics Network
Abstract
The majority of restoration strategies in the wake of large-scale disasters have focused on short-term emergency response solutions. Few consider medium- to long-term restoration strategies to reconnect urban areas to national supply chain interdependent critical infrastructure systems (SCICI). These SCICI promote the effective flow of goods, services, and information vital to the economic vitality of an urban environment. To re-establish the connectivity that has been broken during a disaster between the different SCICI, relationships between these systems must be identified, formulated, and added to a common framework to form a system-level restoration plan. To accomplish this goal, a considerable collection of SCICI data is necessary. The aim of this paper is to review what data are required for model construction, the accessibility of these data, and their integration with each other. While a review of publically available data reveals a dearth of real-time data to assist modeling long-term recovery following an extreme event, a significant amount of static data does exist and these data can be used to model the complex interdependencies needed. For the sake of illustration, a particular SCICI (transportation) is used to highlight the challenges of determining the interdependencies and creating models capable of describing the complexity of an urban environment with the data publically available. Integration of such data as is derived from public domain sources is readily achieved in a geospatial environment, after all geospatial infrastructure data are the most abundant data source and while significant quantities of data can be acquired through public sources, a significant effort is still required to gather, develop, and integrate these data from multiple sources to build a complete model. Therefore, while continued availability of high quality, public information is essential for modeling efforts in academic as well as government communities, a more streamlined approach to a real-time acquisition and integration of these data is essential.
Author Biographies
Varun Ramachandran, Department of Engineering Management & Systems Engineering, Missouri University of Science and Technology
Varun Ramachandran is a postdoctoral fellow in the Department of Engineering Management and Systems Engineering, Missouri University of Science and Technology. His research interests include disaster restoration modeling.
Suzanna K Long, Department of Engineering Management & Systems Engineering, Missouri University of Science and Technology
Suzanna Long is Associate Professor and Interim Chair with the Department of Engineering Management and Systems Engineering at Missouri University of Science & Technology (formerly University of Missouri-Rolla). She holds a PhD and an M.S. in engineering management, B.S. in physics and a B.A. in history from the University of Missouri-Rolla (UMR) and an M.A. in history from the University of Missouri-St. Louis. Her research interests include strategic management of critical infrastructure systems, disaster restoration of supply chain networks, and organizational analysis. Previously, she was Assistant Professor and Director of the Transportation-Logistics Program at Missouri Southern State University, the Director of Academic Programs at Pittsburg State University, and has over 15 years of industry experience in federal records management.
Tom Shoberg, U.S. Geological Survey, Center for Geospatial Information Science (CEGIS)
Tom Shoberg is a Research Geographer with the U.S. Geological Survey. He holds a PhD from Northwestern University in Geophysics, an MS in Earth and Planetary Sciences from Washington University, an MS in Physics from University of Texas-Dallas, and a BS in earth science and a BS in physics from the University of Nebraska-Omaha. His research interests include Big Data Integration and Analytics for Critical Infrastructures; plate tectonics, history of the Pacific Ocean Basin, borehole geophysics, paleomagnetism, mineral physics, geoinformatics, potential field geophysics, planetary geophysics, and science education. Previously, he was Associate Professor and Director of Science Education at Pittsburg State University, a research geophysicist with ARCO Oil and Gas, and a geodesist with the Defense Mapping Agency.
Steven M Corns, Department of Engineering Management & Systems Engineering, Missouri University of Science and Technology
Steven Corns is an Associate Professor of engineering management and systems engineering at Missouri S&T. Dr. Corns earned his Ph.D. in Mechanical Engineering and his M.S. in Mechanical Engineering with a minor in Complex Adaptive Systems, both from Iowa State University. He has several years of experience in thermal systems, virtual engineering, and artificial intelligence research. His research interests include Model Based Systems Engineering and Computational Intelligence techniques, both applied to the modeling of complex systems ranging from controllers for virtual robots to bacteria modeling in biological systems.
Héctor J Carlo, Department of Industrial Engineering, University of Puerto Rico at Mayaguez
Hector Carlo is an Associate Professor of Industrial Engineering at University of Puerto Rico-Mayagüez. Dr. Carlo earned a Doctor of Philosophy degree (2007) and a Master of Science in Engineering degree (2003) from the Industrial and Operations Engineering department at The University of Michigan, and a Bachelor’s of Science degree (2001) from the Industrial Engineering department at the University of Puerto Rico-Mayagüez. His research interests include Material Handling & Logistics, supply chain sustainability, and Operations Research applications to non-traditional environments such as National Security and Emergency Planning and Management.
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