A Byte of my 2.2-lb Brain

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Assessing the Feasibility of Relief Operations

 

Natural Disasters and The Philippines

The Philippines is a country vulnerable to natural disasters. To give the readers an idea of what this means, I reproduce in this post the table that Rappler.com prepared that provides us with a good summary of the worst disasters in the country in terms of casualties.

disasters_rappler

Given the level of risk that we, as a country, are exposed to (e.g. from earthquakes and typhoons), it is easy to see that there is a compelling need for our government to set up effective disaster preparedness and relief response plans, especially considering the fact that we can never be immune to natural disasters.

The Decision-Support Tool

From a few days before Typhoon Haiyan (local name: Yolanda) hit Central Visayas (Philippines) to a few weeks after, my colleagues and I closely kept up with both local and international news on the management of the disaster caused by Yolanda and the relief efforts coming from both the government and non-government organizations—the challenges they had to overcome to reach and attend to the affected. That’s when we realized that there’s a need to develop a model/framework that can aid relief workers in their efforts to distribute food and medical assistance to the devastated, among others. The problem that we saw was that most of the affected barangays and villages were unreachable (literally)—roads were rendered impassable (damaged and blocked). Unfortunately, most of the time, the aid providers would be unaware of these road blockages until they reach the scene, which can be a bit too late.

The tool that we developed aims to help address this issue on mapping and assessing the accessibility and reachability of key locations. Using open data from (Humanitarian) OpenStreetMap and ideas from network science, the platform can provide rescuers and relief workers with a list of possible/alternate routes, categorized by time (to reach) and distance, for use in case the usual or more familiar highways and pathways are impassable.

The details of our model are published in the International Journal of Modern Physics C in early 2014. Below is an overview of our work:

We report a procedure to evaluate centralized, land-bound relief efforts in a disaster-struck region with a model of road network damage. The procedure extracts a region’s road network from map data on OpenStreetMap (OSM). Damage is represented as a reduction in the average speed (and thus, lengthening the needed time) in traversing road segments, each of which had been assigned base speeds in accordance with their respective road types. The average time needed to reach locations on the road network from a designated starting point (the relief center) are then computed.

tacloban

Figure 1. Tacloban City mapped using OpenStreetMap. The map doesn’t only show the morphology of the city, but also information on damages.

In Fig. 1 above, I show a map of Tacloban including some information on infrastructure damages. Just to emphasize, the data is provided by OSM. In Fig. 2, the converted map of Tacloban is shown. From the geoinformation obtain from OSM, we wrote an algorithm that automatically converts a map of a city or any administrative region to a network of roads and intersections. This step is necessary for us to perform some quantitative analytics on the system. Note that complex networks (e.g. road networks) are just mathematical abstractions of complex systems (e.g. cities).

tacloban_road_net

Figure 2. Converting actual road configuration to a road network of nodes and edges.

OpenStreetMap

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I cannot overemphasize the importance of OpenStreetMap data in this research. So, it was a welcome development to see this video prepared by DOST Project NOAH. It provides us with a step-by-step procedure for contributing more data/information to OpenStreetMap.

OpenStreetMap (OSM) is a tool that is an integral part in creating a disaster resilient environment. By identifying points of interest, critical facilities (e.g. health centers, schools, town halls), buildings, and other infrastructures in the community, areas vulnerable to disaster can be easily identified, and risk and exposure details (number of affected houses, commercial buildings, evacuation centers) would be readily estimated.

If the locals will map their own communities, disaster preparedness measures will be more engaged and effective, especially in identifying hazards and risk exposure in the community. – DOST Project NOAH

As a final note, the framework developed is not only useful during and after disasters; it can also serve as a decision-support tool to plan for future disasters. It can be employed to play out scenarios and subsequently provide quantitative assessments of proposed plans (where to place health centers, evacuation centers, warehouses, etc.) and other strategies.


To learn more about our work:

  1. J.F. Valenzuela, E.F. Legara, X. Fu, S.M. Goh, R. de Souza, and C. Monterola, “A network perspective on the calamity, induced inaccessibility of communities and the robustness of centralized, land-bound relief efforts,” Int. J. Mod. Phys. C 25, 1450047 (2014) [16 pages] DOI: 10.1142/S0129183114500478.
  2. Mapping a tool to guide rescuers in disaster zones. The Straits Times. Wednesday, Apr 30, 2014.

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This entry was posted on March 23, 2016 by in Blog, Philippines, Publications, Uncategorized and tagged , , , , , , .
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