single-dr.php

JDR Vol.14 No.3 pp. 445-455
(2019)
doi: 10.20965/jdr.2019.p0445

Paper:

Extraction of Inundation Areas Due to the July 2018 Western Japan Torrential Rain Event Using Multi-Temporal ALOS-2 Images

Wen Liu, Fumio Yamazaki, and Yoshihisa Maruyama

Graduate School of Engineering, Chiba University
1-33 Yayoi-cho, Inage-ku, Chiba 263-8522, Japan

Corresponding author

Received:
November 12, 2018
Accepted:
February 22, 2019
Published:
March 28, 2019
Keywords:
ALOS-2 PALSAR-2, backscattering intensity, coherence, land-cover map, flood
Abstract

A series of heavy rainfalls hit the western half of Japan from June 28 to July 8, 2018. Increased river water overflowed and destroyed river banks, causing flooding over vast areas. In this study, two pre-event and one co-event ALOS-2 PALSAR-2 images were used to extract inundation areas in Kurashiki and Okayama Cities, Okayama Prefecture, Japan. First, water regions were extracted by threshold values from three-temporal intensity images. The increased water regions in July 2018 were obtained as inundation. Inundated built-up areas were identified by the increase of backscattering intensity. Differences between the pre-and co-event coherence values were calculated. The area with decreased coherence was extracted as a possible inundation area. The results of a field survey conducted on July 16, 2018 were used to estimate the optimal parameters for the extraction. Finally, the results from the intensity and coherence images were verified by making comparisons between a web-based questionnaire survey report and the visual interpretation of aerial photographs.

Cite this article as:
W. Liu, F. Yamazaki, and Y. Maruyama, “Extraction of Inundation Areas Due to the July 2018 Western Japan Torrential Rain Event Using Multi-Temporal ALOS-2 Images,” J. Disaster Res., Vol.14, No.3, pp. 445-455, 2019.
Data files:
References
  1. [1] National Research Institute of Earth Science and Disaster Resilience (NIED), Storm, Flood and Landslide Reseach Division, “The characteristics of accumulated rainfall of the July 2018 Western Japan torrential rain,” 2018, http://mizu.bosai.go.jp/key/RainJulyH30Accu (in Japanese) [accessed November 6, 2018]
  2. [2] Cabinet Office, Government of Japan, Disaster Mangement, “Damage situation due to the July 2018 Western Japan torrential rain,” 2018, http://www.bousai.go.jp/updates/h30typhoon7/pdf/301009_1700_h30typhoon7_01.pdf (in Japanese) [accessed November 6, 2018]
  3. [3] S. Martinis, A. Twele, and S. Voigt, “Towards operational near-real time flood detection using a split-based automatic thresholding procedure on high resolution TerraSAR-X data,” Natural Hazards and Earth System Sciences, Vol.9, pp. 303-314, doi: 10.5194/nhess-9-303-2009, 2009.
  4. [4] S. Martinis, A. Twele, and S. Voigt, “Unsupervised extraction of flood-induced backscatter changes in SAR data using Markov image modeling on irregular graphs,” IEEE Trans. on Geoscience and Remote Sensing, Vol.49, No.1, pp. 251-263, doi: 10.1109/TGRS.2010.2052816, 2011.
  5. [5] L. Pulvirenti, N. Pierdicca, G. Boni, M. Fiorini, and R. Rudari, “Flood damage assessment through multitemporal COSMO-SkyMed data and hydrodynamic models: The Albania 2010 case study,” IEEE J. of Selected Topics in Applied Earth Observations and Remote Sensing, Vol.7, pp. 2848-2855, doi: 10.1109/JSTARS.2014.2328012, 2014.
  6. [6] F. Yulianto, P. Sofan, A. Zubaidah, K. A. D. Sukowati, and J. M. Pasaribu, “Detecting areas affected by flood using multi-temporal ALOS PALSAR remotely sensed data in Karawang, West Java, Indonesia,” Natural Hazards, Vol.77, No.2, pp. 959-985, doi: 10.1007/s11069-015-1633-x, 2015.
  7. [7] M. Arri, “Sensitivity study of ALOS-2 data to floodwaters in Joso City in 2015 and its application,” J. of The Remote Sensing Society of Japan, Vol.38, No.4, pp. 325-336, 2018
  8. [8] P. Nakmuenwai, F. Yamazaki, and W. Liu, “Automated extraction of inundation areas from multi-temporal dual-polarization RADARSAT-2 images of the 2011 Central Thailand Flood,” Remote Sensing, Vol.9, Issue 1, No.78, doi: 10.3390/rs9010078, 2017.
  9. [9] W. Liu and F. Yamazaki, “Detection of inundation areas due to the 2015 Kanto and Tohoku torrential rain in Japan based on multi-temporal ALOS-2 imagery,” Natural Hazards and Earth System Sciences, Vol.18, pp. 1905-1918, doi: 10.5194/nhess-18-1905-2018, 2018.
  10. [10] L. Pulvirenti, N. Pierdicca, M. Chini, and L. Guerriero, “An algorithm for operational flood mapping from Synthetic Aperture Radar (SAR) data using fuzzy logic,” Natural Hazards and Earth System Sciences, Vol.11, pp. 529-540, doi: 10.5194/nhess-11-529-2011, 2011.
  11. [11] L. Giustarini, R. Hostache, P. Matgen, G. J. P. Schumann, P. D. Bates, and D. C. Mason, “A change detection approach to flood mapping in urban areas using TerraSAR-X,” IEEE Trans. on Geoscience and Remote Sensing, Vol.51, pp. 2417-2430, doi: 10.1109/TGRS.2012.2210901, 2013.
  12. [12] D. C. Mason, R. Speck, B. Devereux, G. J.-P. Schumann, J. C. Neal, and P. D. Bates, “Flood detection in urban areas using TerraSAR-X,” IEEE Trans. on Geoscience and Remote Sensing, Vol.48, pp. 882-894, doi: 10.1109/TGRS.2009.2029236, 2009.
  13. [13] D. C. Mason, I. J. Davenport, C. N. Neal, Schumann, G. J.-P. Schumann, and P. D. Bates, “Near real-time flood detection in urban and rural areas using high-resolution synthetic aperture radar images,” IEEE Trans. on Geoscience and Remote Sensing, Vol.50, pp. 3041-3052, doi: 10.1109/TGRS.2011.2178030, 2012.
  14. [14] G. Nico, M. Pappalepore, G. Pasquarie, A. Refice, and S. Smare, “Comparison of SAR amplitude vs. coherence flood detection method – A GIS application,” Int. J. of Remote Sensing, Vol.21, pp. 1619-1631, doi: 10.1080/014311600209931, 2000.
  15. [15] M. Chini, L. Pulvirenti, and N. Pierdicca, “Analysis and interpretation of the COSMO-SkyMed observation of the 2011 Tsunami,” IEEE Trans. on Geoscience and Remote Sensing, Vol.9, pp. 467-571, doi: 10.1109/LGRS.2011.2182495, 2012.
  16. [16] L. Pulvirenti, M. Chini, N. Pierdicca, and G. Boni, “Use of SAR data for detecting floodwater in urban and agricultural areas: the role of the interferometric coherence,” IEEE Trans. on Geoscience and Remote Sensing, Vol.54, pp. 1532-1544, doi: 10.1109/TGRS.2015.2482001, 2016.
  17. [17] A. B. Rimba and F. Miura, “Evaluating the extraction approaches of flood extended area by using ALOS-2/PALSAR-2 images as a rapid response to flood disaster,” J. of Geoscience and Environment Protection, Vol.5, pp. 40-61, doi: 10.4236/gep.2017.51003, 2017.
  18. [18] Y. Kwak, S. H. Yun, and Y. Iwami, “A new approach for rapid urban flood mapping using ALOS-2/PALSAR-2 in 2015 Kinu river flood, Japan,” Proc. 2017 IEEE Int. Geoscience and Remote Sensing Symp., pp. 1880-1883, doi: 10.1109/IGARSS.2017.8127344, 2017.
  19. [19] Japan Meteorological Agency (JMA), “Weather bulletins of Okayama Prefecture on July 10, 2018,” 2018, https://www.jma-net.go.jp/okayama/topix/20180710.pdf (in Japanese) [accessed November 6, 2018]
  20. [20] Okayama Prefectural Government, “About damage conditions until August 23, 2018 due to the July 2018 Western Japan torrential rain,” 2018, http://www.pref.okayama.jp/uploaded/life/574060_4675221_misc.pdf (in Japanese) [accessed November 6, 2018]
  21. [21] Geospatial Information Authority of Japan (GSI), “Digital country map web,” 2018, https://maps.gsi.go.jp/ (in Japanese) [accessed November 6, 2018]
  22. [22] Geospatial Information Authority of Japan (GSI), “Base map information,” http://fgd.gsi.go.jp/download/menu.php (in Japanese) [accessed November 6, 2018]
  23. [23] Japan Aerospace Exploration Agency (JAXA), “ALOS Research and Application Project of EORC,” 2017, https://www.eorc.jaxa.jp/ALOS-2/en/calval/calval_index.htm [accessed November 6, 2018]
  24. [24] S. Hashimoto, T. Tadono, M. Onosata, M. Hori, and K. Shiomi, “A new method to derive precise land-use and land-cover maps using multi-temporal optical data,” J. of The Remote Sensing Society of Japan, Vol.34, No.2, pp. 102-112, doi: 10.11440/rssj.34.102, 2014 (in Japanese).
  25. [25] Japan Aerospace Exploration Agency (JAXA), “High-resolution land-use and land-cover maps,” 2016, http://www.eorc.jaxa.jp/ALOS/lulc/jlulc_jpn.htm (in Japanese) [accessed November 6, 2018]
  26. [26] D. M. W. Powers, “Evaluation: from precision, recall and F-measure to ROC, informedness, markedness & correlation,” J. of Machine Learning Technologies, Vol.2, No.1, pp. 37-63, 2011.
  27. [27] K. Ouchi, N. Ishitsuka, and H. Wang, “On the Bragg Scattering observed in L-Band synthetic aperture radar images of flooded rice fields,” IEICE Trans. on Communications, Vol.89-B, No.8, pp. 2218-2225, doi: 10.1093/ietcom/e89-b.8.2218, 2006.
  28. [28] Weathernews Inc., “Indundation conditions in the maximum of flood depths,” 2018, https://weathernews.jp/s/gensai/rain_enq201807/map.html (in Japanese) [accessed November 6, 2018]
  29. [29] Geospatial Information Authority of Japan (GSI), “Information for the July 2018 Western Japan torrential rain,” 2018, http://www.gsi.go.jp/BOUSAI/H30.taihuu7gou.html (in Japanese) [accessed November 6, 2018]

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, IE9,10,11, Opera.

Last updated on Jun. 20, 2019