Flood Vulnerability Analysis Using Remote Sensing and GIS: A Case Study of Sidoarjo Regency

Hery Setiawan Purnawali, Teguh Hariyanto, Danar Guruh Pratomo, Nurin Hidayati

Abstract


Sidoarjo Regency is one of the regencieslocatedin East Java Province Indonesia.Topography of some area in Sidoarjocan be categorized asin low altitude topography, so it makes this regency haspotential risk for flood disaster. Flood incident in Sidoarjo occurs almost every year. The cause of flooding in this district is an accumulation of several factors, such as heavy rainfall in the rainy season for every year, the low altitude areas in several sub-districts, land cover dominated roads and buildings in the some sub-districts, and the existence of several rivers flowing through the district. Application of Geographic Information System (GIS) and remote sensing is generated in this study to present information on the mapping of flood vulnerability zones in Sidoarjo. Integration of satellite and GIS datasets are carried out to prepare the flood zonation mapping of Sidoarjo Regency. Rainfall data fromTropical Rainfall Measuring Mission (TRMM), topographic map, land coverand the distance to main channel data are the datasetsused to identify the flood vulnerability. Flood vulnerability information includes the spatial distribution of flood hazard vulnerability in all sub-districs of Sidoarjo Regency. Spatial information is represented in the form of a map image. By knowing the spatial distribution, it can be known the level of vulnerability of areas to flooding. Most of Sidoarjo regency is flood vulnerable area, which is 76.24% or 658,702,719.91 sqm. It consist of 33.14% very high vulnerable area and 43.10% high vulnerable area. Very high vulnerable flood-prone areas in Sidoarjo Regency  include most area of Jabon, Porong, Tanggulangin, Balongbendo, Krembung, Taman, and Waru sub-districts, while others are some parts of Candi, Sidoarjo, Buduran, and Gedangan sub-districts. High vulnerable flood-prone area include Tarik, Prambon, Tulangan, Wonoayu, and Sukodono sub-districts. The most dominant factors causing flooding in Sidoarjo Regency is the change of land cover, heavy rainfall, and high drainage density, while other factor also contributing to future flood vulnerability are land subsidence.


Keywords


flood; Sidoarjo; GIS; Remote Sensing

Full Text:

PDF

References


V.

] Balai Besar Wilayah Sungai Brantas, “Lima Pilar BBWS Brantas”, Surabaya, Indonesia, 2011

] Badan Nasional Penanggulangan Bencana,“ Data dan Informasi Bencana Indonesia”, 2016. Available at: http://dibi.bnpb.go.id/data-bencana. Accessed 17 November 2016.

] Berita Jatim, "Banjir Porong Terus Naik, BPLS Tambah Pompa Sedot Air", 2016. Available at: http://beritajatim.com/peristiwa/259315/banjir_porong_terus_naik,_bpls_tambah_pompa_sedot_air.html

] Udani, P.M. and Mathur D.K., ” Flood Hazard Vulnerability Mapping Using Remote Sensing & GIS: A Case Study Along the Villages of Anand Taluka”, Pelagia Research Library, advances in Applied Science Research, 2016, 7(3): 214-221

] Elkhrachy, Ismail ,“Flash Flood Hazard Mapping Using Satellite Images and GIS Tools: A Case Study of Najran City, Kingdom of Saudi Arabia (KSA)”. The Egyptian Journal of Remote Sensing and Space Sciences. Vol. 18, 2015, pp. 261-278.

] Haryanto, T., C. B. Pribadi, U. W. Defiantari, H. Hidayat, A. Kurniawan, M. Yusfania, A. Basofi dan M. Hamza. 2016. “Kajian Penurunan Tanah Di Kawasan Tanggulangin Dan Sekitarnya Kabupaten Sidoarjo (Kelurahan Kalidawir, Kelurahan Banjarasri, dan Kelurahan Kedungbanteng)”. Pusat Studi Kebencanaan Lembaga Penelitian dan Pengabdian Kepada Masyarakat Institut Teknologi Sepuluh Nopember, Surabaya.

] Rimba, Andi Besse; Setiawati, Martiwi Diah; Sambah, Abu Bakar; and Miura, Fusanori. (2017). "Physical Flood Vulnerability Mapping Applying Geospatial Techniques in Okazaki City, Aichi Prefecture, Japan". Urban Science. Vol. 1, No. 7, hal. 1-22.

] BMKG (2010). “Kondisi Cuaca Ekstrem dan Iklim Tahun 2010-2011”. Badan Meteorologi Klimatologi dan Geofisika. (BMKG). http://data.bmkg.go.id/Share/Dokumen/press%20release%20kondisi%20cuaca%20ekstrim%20dan%20iklim%20tahun%202010-2011.pdf

] Anderson, J. R., Hardy, E.E., Roach, J.T., dan Witmer, R.E. (1976), “A Land Use and Land Cover Classification System for Use With Remote Sensor Data”. Geological Survey Professional Paper 964. United States Government Printing Office, Washington.

] Geokov. Geokov Education. Available online at http://geokov.com/education/slope-gradient-topographic.aspx (accessed on 15 March 2017)

] Haynes, R.H. (1998). The Canadian System of Soil Classification, 3rd ed.; NRC Research Press: Ottawa, ON, Canada.

] Kodoatie Robert J. dan Sugiyanto, ”Banjir: Beberapa Penyebab dan Metode Pengendaliannya Dalam Perspektif Lingkungan”, Gadjah Mada University Press, Yogyakarta, 2002.

] Saaty, Thomas L. (2008). "Decision making with the analytic hierarchy process". International Journal of Services Sciences, Vol. 1, No. 1, hal. 83-98.

] Saaty, Thomas L. (1990). "How to make a decision: The Analytic Hierarchy Process". European Journal of Operational Research, Vol. 48, hal. 9-26.




DOI: http://dx.doi.org/10.12962/j23546026.y2017i6.3305

Refbacks

  • There are currently no refbacks.


View my Stat: Click Here

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.