Physical Vulnerability Modeling Based On Flood Inundation Model and Image Mining

  • Maulana Ibrahim Rau Bogor Agricultural University
  • Guruh Samodra
  • Hendra Pachri
  • Edy Irwansyah
  • Muhammad Subair

Abstract

Flash flood disaster occurred within the City of Garut, West Java, Indonesia, on 20th September 2016, which caused many casualties and damages. Flood model could be performed to model the already-occurring disaster, as well as to depict future events that may occur to overcome any potential disasters, where the inundation flood model depicted the element at risk. In order to assist the analysis for the damages occurred, image mining could be used as part of the approach, where online media was utilized as well. The image mining resulted information about building damages caused by the flood. Afterwards, the physical vulnerability (buildings/residents) model could be further performed. Finally, the relationship between vulnerability and the flood inundation were portrayed. The resulted physical vulnerability model showed that larger height of the flood water caused higher degree of loss of the building, in which portrayed the need for total rebuild of houses as well. Considering available open source data and fast data acquisition, the approach showed such efficient approaches, where the results could be used in order to establish recommendation for building reinforcement, spatial planning, or protection wall in flood prone areas within the future time.

Downloads

Download data is not yet available.

Author Biography

Maulana Ibrahim Rau, Bogor Agricultural University
Department of Civil and Environmental Engineering, Faculty of Agricultural Technology

References

Al-Mashidani, G., Pande, B. B., Mujda, M. F. (1978) A simple version of Gumbel's method for flood estimation / Version simplifiée de la méthode de Gumbel pour l'estimation des crues, Hydrological Sciences Bulletin, 23:3, 373-380.

Bo, L., Quan, Y., Gao, C., and Dong, X. (2014) Where your photo is taken: Geolocation Prediction for Social Images. Journal of the American Society for Information Science and Technology (JASIST), Volume 65 Issue 6, pages 1232-1243, June 2014.

Departemen Pekerjaan Umum. (2006) Program Rehabilitasi Gempa D.I. Yogyakarta dan Jawa Tengah. http://ciptakarya.pu.go.id/dok/gempa/main.htm. Accessed on 17 March 2016.

Douglas, J. (2007) Physical Vulnerability Modelling in Natural Hazard Risk Assessment,Natural Hazards and Earth System Sciences , 7, 283–288.

Ebert, A., Kerle, N., and Stein, A. (2008) Urban Social Vulnerability Assessment with Physical Proxies and Spatial Metrics derived from Air- and Spaceborne Imagery and GIS Data. Nat Hazards 48:275-294.

ISDR (2004) Living with Risk: A global review of disaster reduction initiatives. International Strategy for Disaster Reduction. Switzerland: United Nations.

Kuichling, E. (1889). The relation between the rainfall and the discharge of sewers in populous districts. Transactions, American Society of Civil Engineers 20, 1–56.

Rijal, S. S. (2012) Analisis Kerusakan Permukiman Akibat Banjir Lahar Pasca Erupsi Gunungapi Merapi 2010 Di Sebagian Kabupaten Magelang (in Bahasa). Un-Publised Thesis.

UNDRO (1984) Disaster prevention and mitigation-a compendium of current knowledge. Preparedness aspects, vol 11, New York

Villagrán de León, J. C. (2006b) Vulnerability. A Conceptual and Methodological Review Studies of the University: Research, Counsel, Education -Publication Series of UNI-EHS, 4, Bonn, Germany

Yoon, T., Rhodes, C., Shah, F. A. (2015) Upstream water resource management to address downstream pollution concerns: A policy framework with application to the Nakdong River basin in South Korea, Water Resour. Res., 51, 787–805

Published
2017-03-12
How to Cite
1.
Rau MI, Samodra G, Pachri H, Irwansyah E, Subair M. Physical Vulnerability Modeling Based On Flood Inundation Model and Image Mining. J-Sil [Internet]. 2017Mar.12 [cited 2024Mar.29];1(3):137-46. Available from: https://jurnal.ipb.ac.id/index.php/jsil/article/view/15298
Section
Research Articles