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FLOODED AREAS EXTRACTION DUE TO THE 2011 THAILAND FLOOD USING RADARSAT-2 AND THAICHOTE IMAGERY DATA

机译:由于2011年泰国洪水采用了雷达拉特 - 2和泰国图像的洪水泛滥

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This paper examines an extraction method of widespread flooded areas occurred in the Chao Phraya River basin, central Thailand, in the rainy season of 2011. RADARSAT-2 imagery data have been mainly used to extract affected areas, while THAICHOTE imagery data have been used as optical supporting data for the Thai Government. In this study, the same data were used in a somewhat different method with more deeply in detail. ScanSAR Narrow-mode imagery with cross-polarization of RADARSAT-2 was introduced to improve the accuracy and get more information on the ground surface. The SAR intensity images, which can be acquired also in the nighttime or under bad weather conditions, were found to be the most effective because the smoothness of water surface always shows low backscatter values. In the same way, the NDVI values calculated from the THAICHOTE images could also recognize flooded areas form open space under a clear sky condition. However, both of these sensors could not discriminate flooded urban areas easily because of the limitation of their spatial resolutions. Backscatter values still kept high although buildings were surrounded by water. The extracted results were validated by a high-resolution optical satellite image, water height data from gaging stations and a digital surface model (DEM) from LiDAR.
机译:本文探讨的普遍受灾地区的提取方法发生在湄南河流域,泰国中部,雨季2011年RADARSAT-2图像数据已经被主要用于提取受影响的地区,而THAICHOTE图像数据已被用作对于泰国政府的光学数据支持。在这项研究中,将相同的数据在一个稍微不同的方法进行详细使用更深入。与RADARSAT-2的交叉极化扫描SAR窄模式图像被引入,以提高精确度,并得到在地面上的详细信息。特区强度图像,这也可以在夜间或恶劣天气条件下获得的,被认为是最有效的,因为水表面的平滑性总是显示出低的后向散射值。以同样的方式,从THAICHOTE图像计算也可以识别NDVI值受灾地区形成了晴空条件下的开放空间。然而,这两种传感器无法判别,因为他们的空间分辨率的限制,淹没市区容易。反向散射值仍然保持较高,虽然建筑被水包围。通过从量具站的高分辨率光学卫星图像,水高度数据和从激光雷达的数字表面模型(DEM)将提取的结果进行了验证。

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