Optimal Evacuation Routing Using LiDAR-Based Flood Models

  • Zarah Jean DicheEmail author
  • Cinmayii Manliguez
  • Maria Jezebel Jimenez
  • Maureen Agrazamendez
  • Joseph Acosta
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 936)


Flooding is one of the most recurring disasters. Evacuation planning is one of the fundamental instruments to mitigate negative impacts of this hazard to the community. Routing is part of evacuation planning that determines the best routes for relocating population. In this study, evacuation routing is focused to the output of the UP Mindanao Phil-LiDAR1. The Light Detection and Ranging (LiDAR) technology is an airborne mapping method that delivers geospatial data in the form of point clouds with high-accuracy elevation values and ground features. Building and road network features extracted from the LiDAR data were used to create network dataset. Flood hazard models were used to identify areas in the network that are at risk of flooding. Capacity Aware Shortest Path Evacuation Routing (CASPER) of the ArcGIS Network Analyst Tool’s extension was used to simulate evacuation routes. The tool uses the CASPER algorithm, a heuristic evacuation routing method that takes into account the capacity of the transportation network and the traffic flow in order to minimize traffic congestion. This study and the data it produced can help the local government units in their planning and disaster risk reduction management.


Flooding Lidar Evacuation Routing CASPER 



This study is under the Phil-Lidar 1.B.13 research project of the University of the Philippines Mindanao that is funded by the Department of Science and Technology (DOST) and the Philippine Council of Industry, Energy and Emerging Technology Research and Development (PCIEERD) of the Philippines.


  1. 1.
    Cole, J.W., et al.: GIS-Based emergency and evacuation planning for volcanic hazards in New Zealand. Bull. N. Z. Soc. Earthq. Eng. 38(3), 149–164 (2005)MathSciNetGoogle Scholar
  2. 2.
    Eguchi, R.T., Huyck, C.K., Ghosh, S., Adams, B.J.: The application of remote sensing technologies for disaster management. In: The 14th World Conference on Earthquake Engineering, Beijing, China (2008)Google Scholar
  3. 3.
    Linham, M.M., Nicholls, R.J.: Flood hazard mapping [WWW Document]. ClimateTechWiki (2010). Accessed 01 Oct 2016
  4. 4.
    Lue, E., Wilson, J.P., Curtis, A.: Conducting disaster damage assessments with spatial video, experts, and citizens. Appl. Geogr. 52, 46–54 (2014). Scholar
  5. 5.
    Mahmassani, H.S., Sbayti, H., Zhou, X.: DYNASMART-P version 1.0 user’s guide. Maryland Transportation Initiative, College Park, Maryland (2004)Google Scholar
  6. 6.
    Manliguez, C., Cuabo, P., Gamot, R., Ligue, K.: Solid waste collection routing optimization using hybridized modified discrete firefly algorithm and simulated annealing - a case study in Davao City, Philippines. In: Proceedings of the 3rd International Conference on Geographical Information Systems Theory, Applications and Management: GISTAM, vol. 1, pp. 50–61 (2017). ISBN 978-989-758-252-3
  7. 7.
    Manliguez, C., Diche, Z., Jimenez, M., Agrazamendez, M., Acosta, J.: GIS-based evacuation routing using capacity aware shortest path evacuation routing algorithm and analytic hierarchy process for flood prone communities. In: Proceedings of the 3rd International Conference on Geographical Information Systems Theory, Applications and Management: GISTAM, vol. 1, pp. 237–243 (2017). ISBN 978-989-758-252-3
  8. 8.
    NDRRMC: National Disaster Risk Reduction Management Council, Philippines (2014). Accessed 04 Sept 2016
  9. 9.
    Ortega, A.: Philippines’ Country Report 2014 [WWW Document]. Country report, Asian Disaster Reduction Center (ADRC) (2014). Accessed 31 Oct 2016
  10. 10.
    Shekhar, S., et al.: Experiences with evacuation route planning algorithms. Int. J. Geogr. Inf. Sci. 26(12), 2253–2265 (2012)CrossRefGoogle Scholar
  11. 11.
    Santos, E.I.: CNN Philippines: Philippines among world’s most disaster-prone countries (2016). Accessed 14 July 2016
  12. 12.
    Project NOAH: DOST - Nationwide Operational Assessment of Hazards (2016). Accessed 04 Sept 2016
  13. 13.
    Santos, G., Aguirre, B.E.: A critical review of emergency evacuation simulation models. In: Building Occupant Movement During Fire Emergencies. Disaster Research Center, University of Delaware (2004)Google Scholar
  14. 14.
    Shahabi, K.: Out of Harm’s Way: Enabling Intelligent Location-Based Evacuation Routing [WWW Document]. ArcUSER (2012). Accessed 02 Oct 2016
  15. 15.
    Shahabi, K., Wilson, J.P.: CASPER: intelligent capacity-aware evacuation routing. Comput. Environ. Urban Syst. 46, 12–24 (2014). Scholar
  16. 16.
    Shahabi, K.: Scalable evacuation routing in dynamic environments. University of Southern California (2015)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Zarah Jean Diche
    • 2
    Email author
  • Cinmayii Manliguez
    • 1
    • 2
  • Maria Jezebel Jimenez
    • 1
  • Maureen Agrazamendez
    • 1
    • 2
  • Joseph Acosta
    • 1
    • 2
  1. 1.Department of Mathematics, Physics, and Computer ScienceUniversity of the Philippines MindanaoDavao CityPhilippines
  2. 2.Phil-LiDAR 1.B.13 LiDAR Data Processing and Validation in Mindanao: Davao RegionUniversity of the Philippines MindanaoDavao CityPhilippines

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