Abstract
Since the late 1990 s, the intensity of tropical cyclones have increased over time, causing massive flooding and landslides in thePhilippines. Nationwide Operational Assessment of Hazards or Project NOAH was put in place as a responsive program for disaster prevention and mitigation. Part of the solution was to set up nababaha.com(www.nababaha.com) and FloodPatrol which provided the public with a web and mobile phone based application for reporting flood height. This paper addresses the problem of providing an interactive and visual method of validating crowdsourced flood reports for the purpose of helping frontline responders and decision makers in disaster management. The approach involves finding the neighborhood of the crowdsourced flood report and weather station data based on their geospatial proximity and time record. A report is classified as correct if it falls within the obtained confidence interval of the crowdsourced flood report neighborhood. The neighborhood of crowdsourced flood reports are correlated with weather station data, which serves as the ground truth in the validation process. Use cases are presented to provide examples of automatic validation. The results of this study is beneficial to disaster management coordinators, first-line responders, government unit officials and citizens. The system provides an interactive approach in validating reports from the crowd, aside from providing an avenue to report flood events in an area. Overall, this contributes to the study of how crowdsourced reports are verified and validated.
Keywords
- Crowdsourcing
- Validation
- Verification
- Disaster informatics
This is a preview of subscription content, access via your institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Andrews, L.: A Template for the Nearest Neighbor Problem (2001). http://www.drdobbs.com/cpp/a-template-for-the-nearest-neighbor-prob/184401449, Accessed 29 March 2016
Bentley, J.L.: Survey of techniques for Fixed radius near neighbor searching. Technicalreport, Stanford Linear Accelerator Center, California, USA (1975)
Brown, S.: The Philippines Is the Most Storm-Exposed Country on Earth (2013). http://world.time.com/2013/11/11/the-philippines-is-the-most-storm-exposed-country-on-earth/, Accessed 29 March 2016
Chazelle, B.: An improved algorithm for the fixed-radius neighbor problem. Inf. Process. Lett. 16(4), 193–198 (1983)
Degrossi, L.C., de Albuquerque, J.P., Fava, M.C., Mendiondo, E.M.: Flood Citizen Observatory: a crowdsourcing-based approach for flood risk management in Brazil. In: Reformat, M. (ed.) The 26th International Conference on Software Engineering and Knowledge Engineering, Hyatt Regency, Vancouver, BC, Canada, July 1–3, 2013, pp. 570–575. Knowledge Systems Institute Graduate School (2014)
Duncan, A., Hogarth, P., Paringit, E., Lagmay, A.: Sharing UK LIDAR and flood mapping experience with the Philippines. In: International Conference on Flood Resilience: Experiences in Asia and Europe, pp. 73–75
Gao, H., Barbier, G., Goolsby, R., Zeng, D.: Harnessing the crowdsourcing power of social media for disaster relief. Technical report, DTIC Document (2011)
Goolsby, R.: Social media as crisis platform: The future of community maps/crisis maps. ACM Trans. Intell. Syst. Technol. 1(1), 7:1–7:11 (2010). http://doi.acm.org/10.1145/1858948.1858955
Howe, J.: Crowdsourcing: Why the Power of the Crowd Is Driving the Future of Business, 1st edn. Crown Publishing Group, New York, NY, USA (2008)
Lagmay, A.: Disseminating near-real time hazards information and flood maps in the philippines through web-gis. Proj. NOAH Open File Rep. 1, 21–36 (2012)
McDougall, K.: Using volunteered information to map the queensland floods. In: Proceedings of the 2011 Surveying and Spatial Sciences Conference: Innovation in Action: Working Smarter (SSSC 2011), pp. 13–23. Surveying and Spatial Sciences Institute (2011)
Schlieder, C., Yanenko, O.: Spatio-temporal Proximity and Social Distance: A Confirmation Framework for Social Reporting. In: Proceedings of the 2Nd ACM SIGSPATIAL International Workshop on Location Based Social Networks, pp. 60–67. LBSN 2010, NY, USA (2010). http://doi.acm.org/10.1145/1867699.1867711
Surowiecki, J.: The wisdom of crowds: Why the many are smarter than the few and how collective wisdom shapes business. Economies, Soc. Nations xxi, 296 (2004)
Virola, R.: Statistically Speaking.. Climate Change - Will the Poor Suffer More? (2009). http://www.nscb.gov.ph/headlines/StatsSpeak/2009/030909_rav_climatechange.asp#1, Accessed 29 March 2016
Virola, R.: Statistically Speaking.. The Devastation of Ondoy and Pepeng! (2009). http://www.nscb.gov.ph/headlines/StatsSpeak/2009/110909_rav_mrsr_typhoons.asp#table1, Accessed 29 March 2016
Whiteman, H.: Philippines gets more than its share of disasters (2014). http://edition.cnn.com/2013/11/08/world/asia/philippines-typhoon-destruction/, Accessed 29 March 2016
Zook, M., Graham, M., Shelton, T., Gorman, S.: Volunteered geographic information and crowdsourcing disaster relief: a case study of the Haitian earthquake. World Med. Health Policy 2(2), 7–33 (2010)
Acknowledgments
Acknowledgment is given to Philippine Council for Industry, Energy and Emerging Technologies Research and Development (PCIEERD), Department of Science and Technology (DOST), for funding this research; Project NOAH, Ateneo Java Wireless Competency Center and the Ateneo Social Computing Science Laboratory for providing the needed assistance and support for this paper.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Victorino, J.N.C., Estuar, M.R.J.E., Lagmay, A.M.F.A. (2016). Validating the Voice of the Crowd During Disasters. In: Xu, K., Reitter, D., Lee, D., Osgood, N. (eds) Social, Cultural, and Behavioral Modeling. SBP-BRiMS 2016. Lecture Notes in Computer Science(), vol 9708. Springer, Cham. https://doi.org/10.1007/978-3-319-39931-7_29
Download citation
DOI: https://doi.org/10.1007/978-3-319-39931-7_29
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-39930-0
Online ISBN: 978-3-319-39931-7
eBook Packages: Computer ScienceComputer Science (R0)