Identification of temporary surface water using sentinel-1 sar data, case study: Sentani flash flooding, Indonesia

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Abstract

Temporary surface water monitoring can provide accurate and reliable information about the spatio-temporal level of surface water. This is very important for various environmental applications, such as flood monitoring. Remote sensing data such as Synthetic Aperture Radar (SAR) is very useful for a large-scale flood monitoring. SAR sensors offer clear advantages by providing their own sources of illumination, thus being able to operate in nearly all-weather/day-night conditions. About 30% disasters which occurred in Indonesia are floods. This hazard has become a recurring disaster that takes place annually. A massive flash flood struck Sentani in the Jayapura Regency in the province of Papua, Indonesia on 16 March 2019, causing 104 deaths. The objective of this work is thus to map temporary surface water (flood) of the Sentani flash flooding event in Indonesia using Sentinel-1 SAR imagery. Sentinel-1 IW GRD and SLC (dual polarimetry) on the event period were used. With two types of Sentinel-1 data, this research produced temporary surface water map using rapid mapping method and SAR polarimetry method. Comparing the results, the similarity of SAR polarimetry method to rapid mapping method is about 39%. Based on reference data, rapid mapping result show better accuracy (82%) than SAR polarimetry method (62%). In addition, processing SLC data needs longer time and higher performance than processing GRD data. Thus, for rapid mapping, it is better to use only Sentinel-1 GRD data.

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APA

Gasica, T. A., Bioresita, F., & Murtiyoso, A. (2020). Identification of temporary surface water using sentinel-1 sar data, case study: Sentani flash flooding, Indonesia. In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives (Vol. 43, pp. 55–59). International Society for Photogrammetry and Remote Sensing. https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-55-2020

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