EVACUATION ROUTING ASSESSMENT DURING EARTHQUAKE OCCURRENCE IN BUTUAN CITY USING GIS TECHNIQUES

Butuan City lies along and is being transected by the Philippine Fault: Surigao Segment. As earthquakes occur more recently, the city is more vulnerable to earthquake hazards, especially soil liquefaction. With the city proper situated mostly on areas susceptible to soil liquefaction and with no constructive evacuation plan against this kind of hazard, it puts the city at risk. This problem highlights the importance of vulnerability assessment for the identification of the road networks that would be most optimal to use in occurrence of an earthquake and an earthquake induced liquefaction. With seven parameters to consider for the assessment, it would be easier to assess by using the pairwise comparison technique of the Analytical Hierarchy Process (AHP) and Geographic Information System (GIS). The analysis was performed by using AHP to assign weights to the parameters and using these weights to classify the road networks into vulnerability classes. The result of the analysis yielded to 34.87% of the road networks with low vulnerability, 65.09% has medium vulnerability and 0.03% are considered to be highly vulnerable. Majority of the road networks especially in the city proper exhibit medium vulnerability in terms of earthquake occurrences. With unavoidable chances that this kind of disaster would happen, these results would benefit the decision makers involved in disaster risk reduction.

Planning for tourist urban evacuation routes: A framework for improving the data collection and evacuation processes

Tourism is one of the largest growing industries worldwide. As the number of tourists is rapidly increasing, so too are tourist safety concerns. The increasing frequency of natural disasters along with the growth of urban areas makes it even more complex to address the resilience of tourists during such events. This article proposes a framework for collecting information about tourist locations and flows within urban areas and how to use this information for more efficient and safe evacuation routing. We define population behavior models that can be obtained from gathering empirical data and categorize them into three groups. We review the different evacuation scenarios (divided into sudden and predictable scenarios) and the types of information needed in each case. Further, we discuss the complexity of monitoring and forecasting tourists’ movements in the long term and for short-term predictions including the available data sources for doing so. The data gathering and tourist behavior are explained with examples from Kyoto, Japan, a major tourist attraction and a location that is prone to disasters. Finally, technological solutions for better guidance during the evacuation process of the population are discussed, including low-tech ones and advanced options such as websites, apps and Bluetooth Low Energy sensors, where the last one is demonstrated by a navigation experiment in a 3D environment.

Three-Dimensional Indoor Fire Evacuation Routing

Traditional indoor navigation algorithms generally only consider the geometrical information of indoor space. However, the environmental information and semantic parameters of a fire are also important for evacuation routing in the case of a fire. It is difficult for traditional indoor navigation algorithms to dynamically find an indoor path when a fire develops. To address this problem, we developed a multi-semantic constrained three-dimensional (3D) indoor fire evacuation routing method that considers multi-dimensional indoor fire scene-related semantics, such as path accessibility, path recognition degree, and fire parameters. Our method enhances the navigation semantics of indoor space by extending the fire-related components of indoor model based on IndoorGML and integrating location semantics of IndoorLocationGML. We also propose quantifiable indoor fire-oriented routing semantics and establish a navigation cost function that evaluates semantic changes during a fire. We designed an indoor routing algorithm with multiple semantic constraints based on the A* algorithm. The indoor routing results were analyzed and compared in simulation experiments. The experimental results showed that the proposed model can remove unusable nodes and edges from the obtained navigation path and provides a safer and more effective evacuation route than traditional algorithms.