Rapid Flood Mapping Using Statistical Sampling Threshold Based on Sentinel-1 Imagery in the Barito Watershed, South Kalimantan Province, Indonesia

Authors

  • Muhammad Priyatna Research Center for Remote Sensing Technology, Research Organization for Aeronautics and Space, National Research and Innovation Agency, East Jakarta, 13710, Indonesia
  • Muhammad Rokhis Khomarudin Research Center for Remote Sensing Technology, Research Organization for Aeronautics and Space, National Research and Innovation Agency, East Jakarta, 13710, Indonesia
  • Sastra Kusuma Wijaya Physics Department, Faculty of Mathematics and Natural Sciences, University of Indonesia, Depok, 16424, Indonesia
  • Fajar Yulianto Research Center for Remote Sensing Technology, Research Organization for Aeronautics and Space, National Research and Innovation Agency, East Jakarta, 13710, Indonesia
  • Gatot Nugroho Research Center for Remote Sensing Technology, Research Organization for Aeronautics and Space, National Research and Innovation Agency, East Jakarta, 13710, Indonesia
  • Pingkan Mayestika Afgatiani Research Center for Remote Sensing Technology, Research Organization for Aeronautics and Space, National Research and Innovation Agency, East Jakarta, 13710, Indonesia
  • Anisa Rarasati Research Center for Remote Sensing Technology, Research Organization for Aeronautics and Space, National Research and Innovation Agency, East Jakarta, 13710, Indonesia
  • Muhammad Arfin Hussein Instrumentation Electronics Study Program, Indonesian Nuclear Technology Polytechnic, Yogyakarta, Indonesia

DOI:

https://doi.org/10.5614/j.eng.technol.sci.2023.55.1.10

Keywords:

flood, Barito watershed, Sentinel-1, statistical sampling, threshold

Abstract

Flood disasters occur frequently in Indonesia and can cause property damage and even death. This research aimed to provide rapid flood mapping based on remote sensing data by using a cloud platform. In this study, the Google Earth Engine cloud platform was used to quickly detect major floods in the Barito watershed in South Kalimantan province, Indonesia. The data used in this study were Sentinel-1 images before and after the flood event, and surface reflectance of Sentinel-2 images available on the Google Earth Engine platform. Flooding is detected using the threshold method. In this study, we determined the threshold using the Otsu method and statistical sampling thresholds (SST). Four SST scenarios were used in this study, combining the mean and standard deviation of the difference backscatter of Sentinel-1 images. The results of this study showed that the second SST scenario could classify floods with the highest accuracy of 73.2%. The inundation area determined by this method was 4,504.33 km2. The first, third and fourth SST scenarios and the Otsu method could reduce the flood load with an overall accuracy of 48.37%, 43.79%, 55.5% and 68.63%, respectively. The SST scenario is considered to be a reasonably good method for rapid flood detection using Sentinel-1 satellite imagery. This rapid detection method can be applied to other areas to detect flooding. This information can be quickly produced to help stakeholders determine appropriate flood management strategies.

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References

Patel, D.P. & Srivastava, P.K., Flood Hazards Mitigation Analysis Using Remote Sensing And GIS: Correspondence with Town Planning Scheme, Water Resources Management, 27, pp. 2353-2368, 2013.

Rizkiah, R., Poli, H. & Supardjo, H., Analysis of Factors Causing Floods in Tikala District, Manado City, Journal SPASIAL: Perencanaan Wilayah dan Kota, 1(1), pp. 105-112, 2015.

Savitri, E. & Pramono, I.B., Upper Cimanuk Flood Analysis of 2016, Jurnal Penelitian Pengelolaan Daerah Aliran Sungai, 1(2), pp. 97?110, 2017.

Hamdani, H., Permana, S. & Susetyaningsih, S., Analysis of Flood-Prone Areas Using Geographic Information System Applications (Case Study of Bangka Island), Jurnal Konstruksi Sekolah Tinggi Teknologi Garut, 12(1), pp.1-13, 2014. (Text in Indonesian)

Yulianto, F., Suwarsono, Sulma, S. & Khomarudin, M.R., Observing the Inundated Area Using Landsat-8 Multitemporal Images and Determination of Flood-Prone Area in Bandung Basin, International Journal Remote Sensing and Earth Sciences, 15(2), pp. 131-140, 2018.

Priya, M.G. & Divya, N., Measurement to Management: Study of Remote Sensing Techniques for Flood Disaster Management, Journal of Remote Sensing and GIS, 10(1), pp.40-57, 2019.

Putri, Y.P., Barlian, E., Dewata, I. & Tanto, T.A., Policy Direction on Flash Floods Disaster Mitigation in Kuranji Watershed, Padang City, Majalah Ilmiah Globe, 20(2), pp. 87-98, 2018.

Prastica, R.M.S., Maitri, C., Nugroho, P.C. & Hermawan, A., Flood Analysis and River Transportation Design Planning in Bojonegoro City, Media Komunikasi Teknik Sipil, 23(2), pp. 91-101, 2017.

Findayani. A., Community Readiness in Flood Management in the City of Semarang, Jurnal Geografi, 12(1), pp. 102-114, 2015.

Maulana, E. & Wulan, T.R., Multi-hazard Mapping of Southern Malang Regency Using a Landscape Approach, National Symposium of Geoinformation Science IV 2015, pp. 526-534, 2015. (Text in Indonesian)

Westen, C.V., Remote Sensing for Natural Disaster Management, International Archives of Photogrammetry and Remote Sensing, XXXIII(B7), pp. 237-245, 2000.

Kader, M.A. & Jahan, I., A Review of the Application of Remote Sensing Technologies in Earthquake Disaster Management: Potentialities and Challenges, International Conference on Disaster Risk Management, 2019.

Kaku, K., Satellite Remote Sensing for Disaster Management Support: A Holistic and Staged Approach Based on Case Studies in Sentinel Asia, International Journal of Disaster Risk Reduction, 33, pp. 417-432, 2019.

Sarkar, D. & Mondal, P., Flood Vulnerability Mapping Using Frequency Ratio (FR) Model: A Case Study on Kulik River Basin, Indo-Bangladesh Barind Region, Applied Water Science, 10(17), 2020.

Saha, S., Sarkar, D. & Mondal, P., Efficiency Exploration of Frequency Ratio, Entropy and Weights of Evidence-Information Value Models in Flood Vulnerability Assessment: A Study of Raiganj Subdivision, Eastern India, Stochastic Environmental Research and Risk Assessment, 36, pp. 1721-1742, 2021.

Sarkar, D., Saha, S. & Mondal, P., GIS-Based Frequency Ratio and Shannon's Entropy Techniques for Flood Vulnerability Assessment in Patna District, Central Bihar, India, Int. J. Environ. Sci. Technol., 19, pp. 8911-8932, 2021.

Kusumawardani, K.P., Cahya, Z.I., Ananto, W.H.G. & Asri, G.H.M., Mapping and Analysis of Shoreline Change In West Coast Lombok Barat Using Normalized Difference Water Index on Landsat Imagery, Seminar Nasional Geomatika 2018, pp. 911-918, 2018.

Soltanian, F.K., Abbasi, M. & Bakhtyari, H.R.R., Flood Monitoring Using NDWI And MNDWI Spectral Indices: A Case Study of Aghqala Flood?2019, Golestan Province, Iran, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-4(W18), GeoSpatial Conference 2019 ? Joint Conferences of SMPR and GI Research, pp. 605-607, 2019.

Nasirzadehdizaji, R., Akyuz, D.E. & Cakir, Z., Flood Mapping and Permanent Water Bodies Change Detection Using Sentinel SAR Data, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-4(W18), GeoSpatial Conference 2019 ? Joint Conferences of SMPR and GI Research, pp. 797-801, 2019.

Sunuprapto, H. & Hussin, Y.A., A Comparison between Optical and Radar Satellite Images in Detecting Burnt Tropical Forest In South Sumatra, Indonesia, International Archives of Photogrammetry and Remote Sensing, XXXIII(B7), pp. 580-587, 2000.

Anusha, N. & Bharathi, B., Flood Detection and Flood Mapping Using Multi-Temporal Synthetic Aperture Radar and Optical Data, The Egyptian Journal of Remote Sensing and Space Science, 23(2), pp. 207-219, 2019.

Waru, A.T., Bayanuddin, A.A., Nugroho, F.S. & Rukminasari, N., Temporal Analysis of Mangrove Forest Changes Using Sentinel-2 Satellite Imagery: Case Study in Tanakeke Island, Takalar District, Geomatics National Seminar 2020: Geospatial Information for Innovation to Accelerate Sustainable Development, pp. 777?786, 2020.

Cao, H., Zhang, H., Wang, C. & Zhang, B., Operational Flood Detection Using Sentinel-1 SAR Data Over Large Areas, Water, 11(4), 786, 2019.

Liang, J. & Liu, D., A Local Thresholding Approach to Flood Water Delineation Using Sentinel-1 SAR Imagery, ISPRS J. Photogramm, 159, pp. 53-62, 2019.

Berezowski, T., Bielinski, T. & Osowicki, J., Flooding Extent Mapping for Synthetic Aperture Radar Time Series Using River Gauge Observations, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, pp. 2626-2638, 2020.

Tiwari, V., Kumar, V., Matin, M.A., Thapa, A., Ellenburg, W.L., Gupta, N. & Thapa, S., Flood Inundation Mapping? Kerala 2018; Harnessing the Power of SAR, Automatic Threshold Detection Method and Google Earth Engine, PLoS ONE, 15(8), e0237324, 2020.

Martinis, S., Kersten, J. & Twele, A., A Fully Automated Terrasar-X Based Flood Service, ISPRS Journal of Photogrammetry and Remote Sensing, 104, pp. 203-212, 2014.

Puspitarini, R.C., Perspectives on South Kalimantan Floods in 2021, JISIP, 1(1), pp. 1-14, 2021.

Zhang, M., Chen, F., Liang, D., Tian, B. & Yang, A., Use of Sentinel-1 GRD SAR Images to Delineate Flood Extent in Pakistan, Sustainability, 12(14), pp. 1-19, 2020.

Zhang, M., Li, Z., Tian, B., Zhou, J. & Tang, P., The Backscattering Characteristics of Wetland Vegetation and Water-Level Changes Detection Using Multi-Mode SAR: A Case Study, International Journal of Applied Earth Observation and Geoinformation, 45, pp. 1?13, 2016.

Uddin, K., Matin, M.A. & Meyer, F.J., Operational Flood Mapping Using Multi-Temporal Sentinel-1 SAR Images: A Case Study from Bangladesh, Remote Sensing, 11(13), pp. 1-19, 2019.

Papila, I., Alganci, U. & Sertel, E., Sentinel-1 Based Flood Mapping Using Interferometric Coherence and Intensity Change Detection Approach, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLIII-B3-2020, XXIV ISPRS Congress (2020 edition), 2020.

Wurjanto, A., Tarigan, T.A. & Mukhti, J.A., Flood Routing Analysis of the Way Seputih River, Central Lampung, Indonesia, International Journal of GEOMATE, 17(63), pp. 307-314, 2019.

Formek, A., Silasari, R., Kusuma, M.S.B. & Kardhana, H., Two-Dimensional Model of Ciliwung River Flood in DKI Jakarta for Development of the Regional Flood Index Map, J. Eng. Technol. Sci., 45(3), pp. 307-325, 2013.

Susandi, A., Tamamadin, M., Pratama, A., Faisal, I., Wijaya, A.R., Pratama, A.F., Pandini, O.P. & Widiawan, D.A., Development of Hydro-Meteorological Hazard Early Warning System in Indonesia, J. Eng. Technol. Sci., 50(4), pp. 461-478, 2018.

Wurjanto, A., Mukhti, J.A. & Wirasti, H.D., Study of Pump and Retention Basin Requirement for Semarang-Demak Coastal Dike Plan, Central Java, International Journal of GEOMATE, 15(47), pp. 66-73, 2018

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Published

2023-03-31

How to Cite

Priyatna, M., Khomarudin, M. R., Wijaya, S. K., Yulianto, F., Nugroho, G., Afgatiani, P. M., Rarasati, A., & Hussein, M. A. (2023). Rapid Flood Mapping Using Statistical Sampling Threshold Based on Sentinel-1 Imagery in the Barito Watershed, South Kalimantan Province, Indonesia. Journal of Engineering and Technological Sciences, 55(1), 98-107. https://doi.org/10.5614/j.eng.technol.sci.2023.55.1.10

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