Abstract
Geographical mapping of disaster risk is an important task in disaster planning and preparedness. Heterogeneous data from various sources are integrated to identify regions having high probability of disasters. The nature of data and work-flow for risk assessment are however varying in nature in each scenario. In this work we propose a service oriented architecture to automate the process of disaster mapping. Open Geospatial Consortium Standards are implemented for this purpose. The framework can aid automated risk assessment under complex multi-modal disasters over large scale geospatial locations by integrating heterogeneous data sources. A Case study is presented for flood risk assessment for a coastal region in West Bengal, in Eastern India.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Pourtaghi, Z.S., Pourghasemi, H.R., Rossi, M.: Forest fire susceptibility mapping in the Minudasht forests, Golestan province, Iran. Environ. Earth Sci. 73, 1515–1533 (2015)
Jaiswal, R.K., Mukherjee, S., Raju, K.D., Saxena, R.: Forest fire risk zone mapping from satellite imagery and gis. Int. J. Appl. Earth Obs. Geoinf. 4, 1–10 (2002)
Youssef, A.M., Pradhan, B., Sefry, S.A.: Flash flood susceptibility assessment in Jeddah city (kingdom of Saudi Arabia) using bivariate and multivariate statistical models. Environ. Earth Sci. 75, 1–16 (2016)
Nishiyama, K., Moriyama, T., Morishita, K., Izumi, S., Yokota, I., Tsukahara, K.: Risk analysis of heavy rainfall and associated disaster occurrence based on pattern recognition of meteorological fields using self-organizing map. In: E-proceedings of the 36th IAHR World Congress, The Hague, the Netherlands, 28 June – 3 July, 2015 (2015)
Shahid, S., Behrawan, H.: Drought risk assessment in the western part of bangladesh. Nat. Hazards 46, 391–413 (2008)
Pourvali, M., Liang, K., Feng, G., Bai, H., Shaban, K., Khan, S., Ghani, N.: Progressive recovery for network virtualization after large-scale disasters. In: International Conference on Computing, Networking and Communications (ICNC), Kauai, HI, pp. 1–5. IEEE (2016)
Kavitha, R., Anuvelavan, S.: Weather master: mobile application of cyclone disaster refinement forecast system in location based on gis using geo-algorithm. Int. J. Sci. Eng. Res. 6, 88–93 (2015)
Hsu, Y.-T., Peeta, S.: Risk-based spatial zone determination problem for stage-based evacuation operations. Transp. Res. Part C: Emerg. Technol. 41, 73–89 (2014)
Nitu, C., Dumitrascu, A., Krapivin, V.F., Mkrtchyan, F.A.: Reducing risks in agriculture. In: 20th International Conference on Control Systems and Computer Science (CSCS), pp. 941–945. IEEE (2015)
Shao, Y., Lunetta, R.S., Wheeler, B., Iiames, J.S., Campbell, J.B.: An evaluation of time-series smoothing algorithms for land-cover classifications using modis-ndvi multi-temporal data. Remote Sens. Environ. 174, 258–265 (2016)
Costa, J.R.S, De Almedia Filgueria, H.J., Moreira Da Silva, F.: Application of the analytic hierarchy process as tool to flood risk management in Carnaubais, Rio Grande Do Norte State, Brazil. In: E-Proceedings of the 36th IAHR World Congress, The Hague, the Netherlands, 28 June–3 July 2015 (2015)
Salgado-Gálvez, M.A., Romero, D.Z., Velásquez, C.A., Carreño, M.L., Cardona, O.-D., Barbat, A.H.: Urban seismic risk index for MedellÃn, Colombia, based on probabilistic loss and casualties estimations. Nat. Hazards 80(3), 1995–2021 (2016)
Cardona, O.D.: The need for rethinking the concepts of vulnerability and risk from a holistic perspective: a necessary review and criticism for effective risk management. In: Mapping vulnerability: Disasters, Development and People, vol. 17. Earthscan Publishers, London (2004)
Tao, K., Wang, L., Qian, X.: Multi-factor constrained analysis method for geological hazard risk. Int. J. Eng. Technol. 8(3), 198 (2016)
Erl, T.: Soa: Principles of Service Design, vol. 1. Prentice Hall, Upper Saddle River (2008)
Foerster, T., Stoter, J.: Establishing an OGC web processing service for generalization processes. In: ICA workshop on Generalization and Multiple Representation (2006)
Hahn, M.B., Riederer, A.M., Foster, S.O.: The livelihood vulnerability index: a pragmatic approach to assessing risks from climate variability and change? a case study in Mozambique. Glob. Environ. Change 19(1), 74–88 (2009)
de Vreede, E., Seib, J., Voidrot-Martinez, M.-F.: Open Geospatial Consortium (2014)
Vretanos, P.A.: Web feature service implementation specification. Open Geospatial Consortium Specification, pp. 4–94 (2005)
Longley, P.A., Goodchild, M.F., Maguire, D.J., Rhind, D.W.: Geographic Information System and Science. Wiley, New York (2001)
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
Chakraborty, O., Das, J., Dasgupta, A., Mitra, P., Ghosh, S.K. (2016). A Geospatial Service Oriented Framework for Disaster Risk Zone Identification. In: Gervasi, O., et al. Computational Science and Its Applications -- ICCSA 2016. ICCSA 2016. Lecture Notes in Computer Science(), vol 9788. Springer, Cham. https://doi.org/10.1007/978-3-319-42111-7_5
Download citation
DOI: https://doi.org/10.1007/978-3-319-42111-7_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-42110-0
Online ISBN: 978-3-319-42111-7
eBook Packages: Computer ScienceComputer Science (R0)