image: The degree of blockage of the city's road network and the status of its buildings (which, prior to cleaning efforts, may be used to approximate the degree of blockage of road segments due to debris from buildings beside them) were extracted from OpenStreetMap's data using the Overpass Turbo online data mining tool. The red shapes represent damaged or collapsed buildings as mapped by OpenStreetMap's Humanitarian team. view more
Credit: Christopher Monterola
The United Nations Office for Disaster Risk Reduction reported that disasters have affected around 2.9 billion people worldwide from 2000-2012— killing more than a million, and damaging around 1.7 trillion US dollars in estimates. Moreover, natural disasters and their damages have been documented to occur with increasing intensity. Given the staggering numbers, effective disaster preparedness and relief response plans are compelling, especially considering the fact that natural disasters are usually unpredictable and damage cannot be avoided.
Implementing a speedy and effectual outreach post-disaster is a nontrivial challenge "due to potential infrastructural changes such as destruction of road systems that make some highways impassable, and damage to the facilities and/or warehouses that serve as storage for relief supplies." A Singapore-based team of scientists from the Institute of High Performance Computing, A*STAR and The Logistics Institute-Asia Pacific has presented a model that looks into the logistics of disaster relief using open data and tools and measures developed in the field of network science. The work was recently published in the International Journal of Modern Physics C.
Based on OpenStreetMap— a collaborative project that provides open geodata to the world, the team reported a procedure that automatically converts a road map system into a road network of nodes and edges. It then utilizes contemporary tools in complex networks to assess several dynamics on the system, particularly, the flow of goods and other relief efforts, and quantify the reachability of critical loci within a geographic area where a disaster has struck. The proposed model is highly-flexible— allowing for inclusion of damage information, such as information coming from the Humanitarian OpenStreetMap team, in the analyses. The procedure developed also enables evaluation of the various effects of a range of possible hypothetical infrastructure destruction scenarios even before a disaster strikes a region—this was shown to be crucial in formulating contingency plans for the logistics of disaster response and relief operations.
To illustrate the utility of the methodology developed, the team considered the roadmap of the city of Tacloban in the central Philippines that was hit by Typhoon Haiyan, which claimed 6000 lives and displaced around 4.1 million more. Among others, the work quantifies the extent at which the inherent structure of the road network plays a role in facilitating, or hindering, landbound relief efforts, especially in the critical hours and days immediately following a disaster event. It also discusses the inaccuracy of assuming that road networks follow a structure similar to the more commonly studied scale-free, random, and/or grid (regular) network configurations.
This research was supported by Singapore A*STAR Complex Systems Programme research grant (# 1224504056 for EFL, CM) A*STAR SERC research grant (#1121790043 for JFV, XF, RG, RdS).
Corresponding author for this study is Christopher Monterola, monterolac@ihpc.a-star.edu.sg.
The article can be found at http://www.worldscientific.com/doi/abs/10.1142/S0129183114500478, from the IJMPC journal - http://www.worldscientific.com/worldscinet/ijmpc
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ABOUT THE AUTHORS
Jesus Felix Valenzuela obtained his Ph.D. in Physics in 2011 at the National Institute of Physics at the University of the Philippines, Diliman (UP Diliman). He was an Assistant Professor at the UP Diliman before he joined the Institute of High Performance Computing in A*STAR Singapore in 2013 as a Scientist. His dissertation was on techniques to quantify spatial segregation and aggregation, as applied to the convection of a suspension. Felix's research interests are in statistical mechanics, complex systems, distributed computing, and logistics and supply chain networks. For details, visit his homepage: http://www.ihpc.a-star.edu.sg/jesus-valenzuela.php?display=1
Erika Fille Legara, a former scholar at the Santa Fe Institute Complex Systems Summer School, studied Physics at the National Institute of Physics at the University of the Philippines, Diliman. Bulk of her work was on the diverse applications of statistical mechanics and network theory in understanding the mechanisms behind various socio-economic systems and paradigms such as multi-level markets, telecommunication companies, and news and media framing. She is currently a Scientist at the A*STAR Institute of High Performance Computing (IHPC) working on big data and visualization, urban complexity, and complex networks. More details on her research can be found at: http://www.erikalegara.com
Xiuju Fu received her BS and MS degrees from Beijing Institute of Technology (China) and Ph.D degree from Nanyang Technological University (Singapore). She joined Institute of High Performance Computing as a Postdoc first and worked as a scientist and program manager in the institute at present. Dr. Fu's research interests are in data analytics, network analysis, modeling and simulation, and their applications in multiple domains like public health, logistics and supply chain management, and others. For details, visit her homepage: http://www.ihpc.a-star.edu.sg/fuxj.php?display=1
Rick Siow Mong Goh is the Director of the Computing Science Department at the A*STAR Institute of High Performance Computing (IHPC). At IHPC, he leads a team of more than 70 scientists in performing world-leading scientific research, developing technologies to commercialization, and engaging and collaborating with industry. The research focus areas include high performance computing (HPC), distributed computing, data analytics, interactive interaction technologies, and computational social cognition. His expertise is in discrete event simulation, parallel and distributed computing, and performance optimization and tuning of applications on large-scale computing platforms. Rick received his Ph.D. in Electrical and Computer Engineering from the National University of Singapore. More details on Rick can be found at: http://ihpc.a-star.edu.sg/gohsm.php?display=1
Robert de Souza is the Executive Director and Chief Executive of The Logistics Institute – Asia Pacific. Robert is a Chartered Engineer and serves on multiple industry, government and academic committees. He is a Senior Fellow at NUS and also holds adjunct Professorships at the Georgia Institute of Technology in Atlanta and the City University in Hong Kong. Robert is also the Program Manager for ASTARs national Urban Solutions logistics and SCM multi-institution program. Dr. de Souza is well published and is an internationally sought speaker and was recently conferred the IEOM 2014 Distinguished Service Award. For more details, please visit http://www.tliap.nus.edu.sg
Christopher Monterola is a Senior Scientist at the A*STAR Institute of High Performance Computing (IHPC). He is the Capability Group Manager of the Complex Systems Group (CxSy) at the IHPC, and the Principal Investigator of the Complexity Science Programme (CSP) under A*STAR's Urban Systems Initiative. Prior to Singapore, Chris was a postdoctoral fellow at the Max Planck Institute for the Physics of Complex Systems. He obtained a Ph.D. in Physics in 2002 from the National Institute of Physics, University of the Philippines, Diliman where he was an Associate Professor. Chris's research expertise involve: the study of complex systems including urban and bio complexity, computational and statistical physics, complex networks, and machine learning. More details on his research can be found at: http://www.chrismonterola.com
Journal
International Journal of Modern Physics C