Assessment of the Number of Damaged Buildings from a Flood Event Using Remote Sensing Technique
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Assessment of the Number of Damaged Buildings from a Flood Event Using Remote Sensing Technique

Authors: Jaturong Som-ard


The heavy rainfall from 3rd to 22th January 2017 had swamped much area of Ranot district in southern Thailand. Due to heavy rainfall, the district was flooded which had a lot of effects on economy and social loss. The major objective of this study is to detect flooding extent using Sentinel-1A data and identify a number of damaged buildings over there. The data were collected in two stages as pre-flooding and during flood event. Calibration, speckle filtering, geometric correction, and histogram thresholding were performed with the data, based on intensity spectral values to classify thematic maps. The maps were used to identify flooding extent using change detection, along with the buildings digitized and collected on JOSM desktop. The numbers of damaged buildings were counted within the flooding extent with respect to building data. The total flooded areas were observed as 181.45 These areas were mostly occurred at Ban khao, Ranot, Takhria, and Phang Yang sub-districts, respectively. The Ban khao sub-district had more occurrence than the others because this area is located at lower altitude and close to Thale Noi and Thale Luang lakes than others. The numbers of damaged buildings were high in Khlong Daen (726 features), Tha Bon (645 features), and Ranot sub-district (604 features), respectively. The final flood extent map might be very useful for the plan, prevention and management of flood occurrence area. The map of building damage can be used for the quick response, recovery and mitigation to the affected areas for different concern organization.

Keywords: Flooding extent, Sentinel-1A data, JOSM desktop, damaged buildings.

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[1] Asia and the Pacific (2017, January, 9). Asia and the Pacific: Weekly Regional Humanitarian Snapshot (3 - 9 January 2017) (Online). Retrieved from
[2] Balaji, T., & Sumathi, D. M. (2014). Effective Features of Remote Sensing Image Classification Using Interactive Adaptive Thresholding Method. arXiv preprint arXiv:1401.7743.
[3] Chaouch, N., Temimi, M., Hagen, S., Weishampel, J., Medeiros, S., & Khanbilvardi, R. (2012). A synergetic use of satellite imagery from SAR and optical sensors to improve coastal flood mapping in the Gulf of Mexico. Hydrological Processes, 26(11), 1617-1628.
[4] Earth observatory (2017, January, 13). Flood Swamp Southern Thailand (Online). Retrieved from
[5] European Space Agency (2013, September, 1). Sentinel 1 User Hand book. Available from
[6] Haraguchi, M., & Lall, U. (2015). Flood risks and impacts: A case study of Thailand’s floods in 2011 and research questions for supply chain decision making. International Journal of Disaster Risk Reduction, 14, 256-272.
[7] Jan Stefanski (2015, October, 9). Step by Step: Recommended Practice Flood Mapping (Online). Retrieved from
[8] Long, S., Fatoyinbo, T., and Policelli, F.: Flood extent mapping for Namibia using change detection and thresholding with SAR, Environ. Res. Lett., 9, 035002, doi:10.1088/1748-9326/9/3/035002, 2014.
[9] Lu, D., Mausel, P., Brondizio, E., & Moran, E. (2004). Change detection techniques. International journal of remote sensing, 25(12), 2365-2401.
[10] Musa, Z. N., Popescu, I., & Mynett, A. (2015). A review of applications of satellite SAR, optical, altimetry and DEM data for surface water modelling, mapping and parameter estimation. Hydrology and Earth System Sciences, 19(9), 3755-3769.
[11] Nazir, F., Riaz, M. M., Ghafoor, A., & Arif, F. (2014). Flood detection/monitoring using adjustable histogram equalization technique. The Scientific World Journal, 2014.
[12] OpenStreetMap contributors (2017, February, 17). Open Street Map (Online). Retrieved from /#map.
[13] Owe, M., Brubaker, K., Ritchie, J., and Albert, R.: Remote sensing and Hydrology, 2000, IAHS, Wallingford, OX, UK, 2001.
[14] PPTV (2016, December, 8). Flooding in Songhla province (Online). Retrieved from
[15] Refice, A., Capolongo, D., Pasquariello, G., D’Addabbo, A., Bovenga, F., Nutricato, R.... & Pietranera, L. (2014). SAR and InSAR for flood monitoring: Examples with COSMO-SkyMed data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(7), 2711-2722.
[16] Rémi, A., & Hervé, Y. (2007). Change detection analysis dedicated to flood monitoring using ENVISAT wide swath mode data.
[17] Rosin, P. L., Hervás, J., & Barredo, J. I. (2000). Remote sensing image thresholding for landslide motion detection. In 1st Int. Workshop on Pattern Recognition Techniques in Remote Sensing (pp. 10-17).
[18] Singh, A. (1989). Review article digital change detection techniques using remotely-sensed data. International journal of remote sensing, 10(6), 989-1003.
[19] Sunkpho, J., & Ootamakorn, C. (2011). Real-time flood monitoring and warning system. Sonklanakarin Journal of Science and Technology, 33(2), 227.
[20] TATNEWS (2017, January, 9). Southern Thailand Floods Situation Update as of 9 January 2017 (Online). Retrieved from
[21] ThaiTambon (2015, December, 18). OTOP One Tambon One Product (Online). Retrieved from
[22] The Ministry of Finance, Royal Thai Government and The World Bank (2012). Introduction of the disaster. Thailand Flooding 2554 Rapid Assessment for Resilient Recovery and Reconstruction Planning.
[23] Torres, R., Snoeij, P., Geudtner, D., Bibby, D., Davidson, M., Attema, E., ... & Traver, I. N. (2012). GMES Sentinel-1 mission. Remote Sensing of Environment, 120, 9-24.
[24] Trinh, L. H. (2013). Remote sensing techniques for flood monitoring using Envisat Asar data. Federal State Budget Educational Establishment of Higher Professional Education "Pskov State University, (3).
[25] Twele, A., Martinis, S., Cao, W., & Plank, S. (2016). Automated flood mapping and monitoring using Sentinel-1 data.
[26] Voigt, S., Martinis, S., Zwenzner, H., Hahmann, T., Twele, A., & Schneiderhan, T. (2008, May). Extraction of flood masks using satellite based very high resolution SAR data for flood management and modeling. In Proceedings of the 4th International Symposium on Flood Defence, Managing Flood Risk, Reliability & Vulnerability, Toronto, Canada.
[27] Weng, Q. (2012). An introduction to contemporary remote sensing. McGraw Hill Professional.