Detecting areas affected by flood using multi-temporal ALOS PALSAR remotely sensed data in Karawang, West Java, Indonesia

Fajar Yulianto (), Parwati Sofan, Any Zubaidah, Kusumaning Sukowati, Junita Pasaribu and Muhammad Khomarudin

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2015, vol. 77, issue 2, 959-985

Abstract: The normalized change index and split-based approach methods have been applied in this research to create the semiautomatic unsupervised change-detection areas affected by flood using multi-temporal Advanced Land Observing Satellite Phased Array L-band Synthetic Aperture Radar (ALOS PALSAR) remotely sensed data. This research is focused to provide information related to the flood inundation event that occurred in March 2010, in Karawang, West Java, Indonesia. The objectives of this research are as follows: (1) to generate a flood inundation map as rapid mapping steps in disaster mitigation effort and (2) to identify and assess the environmental damage caused by flood inundation event in the research area. ALOS PALSAR remotely sensed data with the acquisition pre-flood (March 09, 2010) and post-flood (March 26, 2010) were used for mapping flood inundation event. Flood inundation map and land-use data are used for the identification and assessment of the environmental damage caused by flood inundation event, which is done with GIS environment tools. The flood inundation event is estimated to have an impact of 7,158 ha for settlements; 20,039 ha for paddy fields; 668 ha for plantations; 1,641 ha for farms; 198 ha for agricultural cultivations; 1,161 ha for shrubberies; 1,022 ha for industrials; and 1,019 ha for road areas. The total number of building damages is estimated to be around 16,350 units. In general, this method can be used to assist emergency response efforts, through an inventory of areas affected by floods. In addition, the use of this method can be applied and it is recommended for future research in different locations, which are consistent and reliable to detect areas affected by other disasters such as flash floods, landslide, tsunami, volcano eruptions, and forest fire. Copyright Springer Science+Business Media Dordrecht 2015

Keywords: Remote sensing; ALOS PALSAR; Change detection; Flood inundations; Karawang; Indonesia (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/s11069-015-1633-x

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