Rapid Change Detection of Flood Affected Area after Collapse of the Laos Xe-Pian Xe-Namnoy Dam Using Sentinel-1 GRD Data
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 fl...
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| Format: | Article |
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MDPI AG
2020-06-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/12/12/1978 |
| _version_ | 1797564756942389248 |
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| author | Yunjee Kim Moung-Jin Lee |
| author_facet | Yunjee Kim Moung-Jin Lee |
| author_sort | Yunjee Kim |
| collection | DOAJ |
| description | 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 <inline-formula> <math display="inline"> <semantics> <mi mathvariant="sans-serif">α</mi> </semantics> </math> </inline-formula>-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 <inline-formula> <math display="inline"> <semantics> <mrow> <mo>×</mo> </mrow> </semantics> </math> </inline-formula> 10<sup>8</sup> m<sup>3</sup> water overflowed from the Xe-Namnoy reservoir, and a flooded area of about 28.1 km<sup>3</sup> 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. |
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| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T19:01:25Z |
| publishDate | 2020-06-01 |
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| spelling | doaj.art-9b36adc99e9e497f90a71e440168dfbf2023-11-20T04:23:40ZengMDPI AGRemote Sensing2072-42922020-06-011212197810.3390/rs12121978Rapid Change Detection of Flood Affected Area after Collapse of the Laos Xe-Pian Xe-Namnoy Dam Using Sentinel-1 GRD DataYunjee Kim0Moung-Jin Lee1Environmental Assessment Group, Korea Environment Institute, Sejong 30147, KoreaCenter for Environmental Data Strategy, Korea Environment Institute, Sejong 30147, KoreaWater-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 <inline-formula> <math display="inline"> <semantics> <mi mathvariant="sans-serif">α</mi> </semantics> </math> </inline-formula>-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 <inline-formula> <math display="inline"> <semantics> <mrow> <mo>×</mo> </mrow> </semantics> </math> </inline-formula> 10<sup>8</sup> m<sup>3</sup> water overflowed from the Xe-Namnoy reservoir, and a flooded area of about 28.1 km<sup>3</sup> 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.https://www.mdpi.com/2072-4292/12/12/1978Sentinel-1change detectionSARfloodXe-Pian Xe-Namnoy |
| spellingShingle | Yunjee Kim Moung-Jin Lee Rapid Change Detection of Flood Affected Area after Collapse of the Laos Xe-Pian Xe-Namnoy Dam Using Sentinel-1 GRD Data Remote Sensing Sentinel-1 change detection SAR flood Xe-Pian Xe-Namnoy |
| title | Rapid Change Detection of Flood Affected Area after Collapse of the Laos Xe-Pian Xe-Namnoy Dam Using Sentinel-1 GRD Data |
| title_full | Rapid Change Detection of Flood Affected Area after Collapse of the Laos Xe-Pian Xe-Namnoy Dam Using Sentinel-1 GRD Data |
| title_fullStr | Rapid Change Detection of Flood Affected Area after Collapse of the Laos Xe-Pian Xe-Namnoy Dam Using Sentinel-1 GRD Data |
| title_full_unstemmed | Rapid Change Detection of Flood Affected Area after Collapse of the Laos Xe-Pian Xe-Namnoy Dam Using Sentinel-1 GRD Data |
| title_short | Rapid Change Detection of Flood Affected Area after Collapse of the Laos Xe-Pian Xe-Namnoy Dam Using Sentinel-1 GRD Data |
| title_sort | rapid change detection of flood affected area after collapse of the laos xe pian xe namnoy dam using sentinel 1 grd data |
| topic | Sentinel-1 change detection SAR flood Xe-Pian Xe-Namnoy |
| url | https://www.mdpi.com/2072-4292/12/12/1978 |
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