{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T15:14:29Z","timestamp":1770909269058,"version":"3.50.1"},"reference-count":44,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2020,6,19]],"date-time":"2020-06-19T00:00:00Z","timestamp":1592524800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003654","name":"Korea Environmental Industry and Technology Institute","doi-asserted-by":"publisher","award":["2019002650001"],"award-info":[{"award-number":["2019002650001"]}],"id":[{"id":"10.13039\/501100003654","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Korea Ministry of Environment","award":["2019002650001"],"award-info":[{"award-number":["2019002650001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Water-related disasters occur frequently worldwide and are strongly affected by a climate. Synthetic aperture radar (SAR) satellite images can be effectively used to monitor and detect damage because these images are minimally affected by weather. This study analyzed changes in water quantity and flooded area caused by the collapse of the Xe-Pian Xe-Namnoy Dam in Laos on 23 July 2018, using Sentinel-1 ground range detected (GRD) images. The collapse of this dam gained worldwide attention and led to a large number of casualties at least 98 people, as well as enormous economic losses. Thus, it is worth noting that this study quantitatively analyzed changes in both the Hinlat area, which was flooded, and the Xe-Namnoy reservoir. This study aims to suggest a practical method of change detection which is to simply compute flood extent and water volume in rapidly analysis. At first, a    \u03b1   -stable distribution was fitted to intensity histogram for removing the non-water-affected pixels. This fitting differs from other typical histogram fitting methods, which is applicable to histograms with two peaks, as it can be applied to histograms with not only two peaks but also one peak. Next, another type of threshold based on digital elevation model (DEM) data was used to correct for residual noise, such as speckle noise. The results revealed that about 2.2     \u00d7     108 m3 water overflowed from the Xe-Namnoy reservoir, and a flooded area of about 28.1 km3 was detected in the Hinlat area shortly after the dam collapse. Furthermore, the water quantity and flooded area decreased in both study areas over time. Because only SAR GRD images were used in this study for rapid change detection, it is possible that more accurate results could be obtained using other available data, such as optical images with high spatial resolution like KOMPSAT-3, and in-situ data collected at the same time.<\/jats:p>","DOI":"10.3390\/rs12121978","type":"journal-article","created":{"date-parts":[[2020,6,19]],"date-time":"2020-06-19T10:43:58Z","timestamp":1592563438000},"page":"1978","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Rapid Change Detection of Flood Affected Area after Collapse of the Laos Xe-Pian Xe-Namnoy Dam Using Sentinel-1 GRD Data"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6440-3007","authenticated-orcid":false,"given":"Yunjee","family":"Kim","sequence":"first","affiliation":[{"name":"Environmental Assessment Group, Korea Environment Institute, Sejong 30147, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1226-3460","authenticated-orcid":false,"given":"Moung-Jin","family":"Lee","sequence":"additional","affiliation":[{"name":"Center for Environmental Data Strategy, Korea Environment Institute, Sejong 30147, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2020,6,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"816","DOI":"10.1038\/nclimate1911","article-title":"Global flood risk under climate change","volume":"3","author":"Hirabayashi","year":"2013","journal-title":"Nat. Clim. Chang."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1007\/s11069-004-4547-6","article-title":"Summer floods in Central Europe\u2013climate change track?","volume":"36","author":"Kundzewicz","year":"2005","journal-title":"Nat. Hazards"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3625","DOI":"10.1175\/1520-0442(2000)013<3625:PADFTI>2.0.CO;2","article-title":"Precipitation and damaging floods: Trends in the United States, 1932\u20131997","volume":"13","author":"Pielke","year":"2000","journal-title":"J. Clim."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1111\/jfr3.12045","article-title":"An algorithm for rapid flood inundation mapping from optical data using a reflectance differencing technique","volume":"7","author":"Amarnath","year":"2013","journal-title":"J. Flood Risk Manag."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Li, J., Yang, X., Ma_ei, C., Tooth, S., and Yao, G. (2018). Applying Independent Component Analysis on Sentinel-2 Imagery to Characterize Geomorphological Responses to an Extreme Flood Event near the Non-Vegetated. R\u00edo Colorado Terminus, Salar de Uyuni, Bolivia. Remote Sens., 10.","DOI":"10.3390\/rs10050725"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"368","DOI":"10.1016\/j.jhydrol.2015.01.036","article-title":"Decadal monitoring of the Niger Inner Delta flood dynamics using MODIS optical data","volume":"523","author":"Ogilvie","year":"2015","journal-title":"J. Hydrol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"4173","DOI":"10.3390\/rs6054173","article-title":"Water feature extraction and change detection using multitemporal landsat imagery","volume":"6","author":"Rokni","year":"2014","journal-title":"Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"814","DOI":"10.1109\/JSTARS.2011.2125778","article-title":"Deriving water fraction and flood maps from MODIS images using a decision tree approach","volume":"4","author":"Sun","year":"2011","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_9","first-page":"117","article-title":"Evaluation of polarimetric parameters for flood detection using PALSAR-2 quad-pol data","volume":"34","author":"Jung","year":"2018","journal-title":"Korean J. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Kussul, N., Shelestov, A., and Skakun, S. (2011). Flood monitoring from SAR data. Use of Satellite and In-Situ Data to Improve Sustainability, Springer.","DOI":"10.1007\/978-90-481-9618-0_3"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1109\/TGRS.2010.2052816","article-title":"Unsupervised extraction of flood-induced backscatter changes in SAR data using Markov image modeling on irregular graphs","volume":"49","author":"Martinis","year":"2010","journal-title":"IEEE Trans. Geosci. Remote. Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"2711","DOI":"10.1109\/JSTARS.2014.2305165","article-title":"SAR and InSAR for flood monitoring: Examples with COSMO-SkyMed data","volume":"7","author":"Refice","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens."},{"key":"ref_13","first-page":"15","article-title":"Flood detection from multi-temporal SAR data using harmonic analysis and change detection","volume":"38","author":"Schlaffer","year":"2015","journal-title":"Int. J. Appl. Earth Obs."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"4478","DOI":"10.1109\/JSTARS.2017.2717039","article-title":"Effect of the vegetation fire on backscattering: An investigation based on Sentinel-1 observations","volume":"10","author":"Imperatore","year":"2017","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Martinis, S., Plank, S., and \u0106wik, K. (2018). The use of Sentinel-1 time-series data to improve flood monitoring in arid areas. Remote Sens., 10.","DOI":"10.3390\/rs10040583"},{"key":"ref_16","first-page":"97","article-title":"Evaluation of forest fire on Madeira Island using Sentinel-2A MSI imagery","volume":"58","author":"Navarro","year":"2017","journal-title":"Int. J. Appl. Earth Obs."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2990","DOI":"10.1080\/01431161.2016.1192304","article-title":"Sentinel-1-based flood mapping: A fully automated processing chain","volume":"37","author":"Twele","year":"2016","journal-title":"Int. J. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"3290","DOI":"10.1109\/TGRS.2018.2797536","article-title":"Unsupervised Rapid Flood Mapping Using Sentinel-1 GRD SAR Images","volume":"56","author":"Amitrano","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Bioresita, F., Puissant, A., Stumpf, A., and Malet, J.-P. (2018). A Method for Automatic and Rapid Mapping of Water Surfaces from Sentinel-1 Imagery. Remote Sens., 10.","DOI":"10.3390\/rs10020217"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"575","DOI":"10.5194\/isprs-archives-XLII-5-575-2018","article-title":"Considerations on the use of Sentinel-1 data in flood mapping in urban areas: Ankara (Turkey) 2018 floods","volume":"XLII-5","author":"Tavus","year":"2018","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Carre\u00f1o Conde, F., and De Mata Mu\u00f1oz, M. (2019). Flood Monitoring Based on the Study of Sentinel-1 SAR Images: The Ebro River Case Study. Water, 11.","DOI":"10.3390\/w11122454"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Tsyganskaya, V., Martinis, S., and Marzahn, P. (2019). Flood Monitoring in Vegetated Areas Using Multitemporal Sentinel-1 Data: Impact of Time Series Features. Water, 11.","DOI":"10.3390\/w11091938"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"567","DOI":"10.1111\/j.1752-1688.2009.00326.x","article-title":"Satellite Precipitation Measurements for Water Resource Monitoring 1","volume":"45","author":"Kidd","year":"2009","journal-title":"J. Am. Water Resour."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"105","DOI":"10.11614\/KSL.2018.51.1.105","article-title":"Present Status and Future Prospect of Satellite Image Uses in Water Resources Area","volume":"51","author":"Kim","year":"2018","journal-title":"Korean J. Ecol. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1439","DOI":"10.1080\/014311698215559","article-title":"Orbital SAR remote sensing of a river flood wave","volume":"19","author":"Brakenridge","year":"1998","journal-title":"Int. J. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1111\/jfr3.12303","article-title":"Multi-temporal synthetic aperture radar flood mapping using change detection","volume":"11","author":"Clement","year":"2018","journal-title":"J. Flood Risk Manag."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1007\/s11269-005-3281-5","article-title":"Delineation of flood-prone areas using remote sensing techniques","volume":"19","author":"Jain","year":"2005","journal-title":"Water Resour. Manag."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1023\/B:NHAZ.0000037035.65105.95","article-title":"Application of remote sensing in flood management with special reference to monsoon Asia: A review","volume":"33","author":"Sanyal","year":"2004","journal-title":"Nat. Hazards"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Cheng, S., Zhao, W., and Yin, Z. (2019, January 20\u201322). PS-InSAR Analysis of Collapsed Dam and Extraction of Flood Inundation Areas in Laos Using Sentinel-1 SAR Images. Proceedings of the 2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), Chengdu, China.","DOI":"10.1109\/IAEAC47372.2019.8997848"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2417","DOI":"10.1109\/TGRS.2012.2210901","article-title":"A change detection approach to flood mapping in urban areas using TerraSAR-X","volume":"51","author":"Giustarini","year":"2012","journal-title":"IEEE Trans. Geosci. Remote. Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"6958","DOI":"10.1109\/TGRS.2016.2592951","article-title":"Probabilistic flood mapping using synthetic aperture radar data","volume":"54","author":"Giustarini","year":"2016","journal-title":"IEEE Trans. Geosci. Remote. Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1016\/j.pce.2010.12.009","article-title":"Towards an automated SAR-based flood monitoring system: Lessons learned from two case studies","volume":"36","author":"Matgen","year":"2011","journal-title":"Phys. Chem. Earth"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"539","DOI":"10.7780\/kjrs.2016.32.5.11","article-title":"Detection of water bodies from Kompsat-5 SAR data","volume":"32","author":"Park","year":"2016","journal-title":"Korean J. Remote Sens."},{"key":"ref_34","unstructured":"Ulaby, F.T.M. (1981). Microwave Remote Sensing: Active and Passive. Volume 1-Microwave Remote Sensing Fundamentals and Radiometry, Addison-Wesley."},{"key":"ref_35","unstructured":"Bourbigot, M., Johnsen, H., Piantanida, R., and Hajduch, G. (2016). Sentinel-1 product definition. MDA Document Number: SEN-RS-52\u20137440, ESA. Reference S1-RS-MDA-52-7440."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"6633","DOI":"10.1364\/AO.39.006633","article-title":"Noise and speckle reduction in synthetic aperture radar imagery by nonparametric Wiener filtering","volume":"39","author":"Caprari","year":"2000","journal-title":"Appl. Opt."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1219","DOI":"10.1109\/TGRS.2007.912718","article-title":"A stationary wavelet-domain wiener filter for correlated speckle","volume":"46","author":"Solbo","year":"2008","journal-title":"IEEE Trans. Geosci. Remote. Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1137\/040616024","article-title":"A review of image denoising algorithms, with a new one","volume":"4","author":"Buades","year":"2005","journal-title":"Multiscale Model. Simul."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Chini, M., Pelich, R., Pulvirenti, L., Pierdicca, N., Hostache, R., and Matgen, P. (2019). Sentinel-1 InSAR coherence to detect floodwater in urban areas: Houston and Hurricane Harvey as a test case. Remote Sens., 11.","DOI":"10.3390\/rs11020107"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1016\/j.sigpro.2012.07.035","article-title":"A survey on computing L\u00e9vy stable distributions and a new MATLAB toolbox","volume":"93","author":"Liang","year":"2013","journal-title":"Signal Process."},{"key":"ref_41","unstructured":"Nolan, J. (2003). Stable Distributions: Models for Heavy-Tailed Data, Birkhauser."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"4001","DOI":"10.1080\/01431160500176788","article-title":"Analysis of the water volume, length, total area and inundated area of the Three Gorges Reservoir, China using the SRTM DEM data","volume":"26","author":"Wang","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"4591","DOI":"10.1109\/TGRS.2013.2265413","article-title":"Information content of very high resolution SAR images: Study of feature extraction and imaging parameters","volume":"51","author":"Dumitru","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1080\/2150704X.2018.1530481","article-title":"The effects of orbit type on synthetic aperture RADAR (SAR) backscatter","volume":"10","author":"Mahdavi","year":"2019","journal-title":"Remote Sens. Lett."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/12\/1978\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:40:56Z","timestamp":1760175656000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/12\/1978"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6,19]]},"references-count":44,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2020,6]]}},"alternative-id":["rs12121978"],"URL":"https:\/\/doi.org\/10.3390\/rs12121978","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,6,19]]}}}