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首页> 外文会议>Asian conference on remote sensing;ACRS >FLOOD MONITORING IN GAMPAHA DISTRICT USING SAR DATA AS A CASE STUDY IN THE LOWER BASIN IN ATTANAGALU OYA (RIVER)
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FLOOD MONITORING IN GAMPAHA DISTRICT USING SAR DATA AS A CASE STUDY IN THE LOWER BASIN IN ATTANAGALU OYA (RIVER)

机译：利用SAR数据监测加帕哈地区的洪水，以阿塔塔加卢大流域（河流）下流域为例

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Radar image data find special application in flood monitoring due to their properties of all weather, dayight and cloud-piercing capabilities. However, the classification and object extraction of radar image are very difficult because their imaging mechanism is quite different from that of multi spectral image. One of the largest limitations of radar automated classification is the occurrence of speckle noise. ALOS satellite obtained PALSAR radar data during floods by the emergency observation requests. The PALSAR data can easily detect the water surface because its wave length is L-band. Flood on 18m May 2010 at Attanagalu Ova basin in Gampaha District. Sri Lanka, shows the effectiveness and efficiency of this method. The results of the analysis were timely provided to the central and local governments to help them to make decision on the reduction of flood disasters. Remote sensing methods based on optical, medium resolution imagery, such as Landsat and SPOT, are limited in their applicability. This paper presents and compares a few techniques using remote sensing data which are used to flood mapping & eventually used to analyze flood propagation. Geometric correction and typical noise smoothing methods of the PALSAR data are used here and with the "not enough satisfaction" of speckle reduction, one more reduction method called wavelet thresholding was applied. The resulting images almost coincide with the reported flood regions. Fusion of satellite images with different spatial and spectral resolutions plays here an important role in visualizing information effectively. GIS relate technologies are very useful in flood monitoring and damage evaluation. In this study. GIS & Remote Sensing provide a better evaluation that useful for understanding overall situation & in an emergency rapid response to global disasters like flood is firmly established and flood monitoring has become an easy task with the advent of the said technology.
机译：雷达图像数据具有全天候，昼/夜和穿云能力，因此在洪水监控中具有特殊的应用。然而，雷达图像的分类和目标提取非常困难，因为它们的成像机理与多光谱图像完全不同。雷达自动分类的最大限制之一是斑点噪声的出现。 ALOS卫星根据紧急观察请求获得了洪水期间的PALSAR雷达数据。 PALSAR数据的波长为L波段，因此可以轻松检测到水面。 2010年5月18日在Gampaha区Attanagalu Ova盆地发生洪水。斯里兰卡显示了这种方法的有效性和效率。分析的结果及时提供给中央和地方政府，以帮助他们做出减少水灾的决定。基于光学，中分辨率图像（例如Landsat和SPOT）的遥感方法的适用性受到限制。本文介绍并比较了几种使用遥感数据的技术，这些技术用于洪水地图绘制并最终用于分析洪水传播。这里使用了PALSAR数据的几何校正和典型的噪声平滑方法，并且由于对斑点减少的“不够满意”，应用了另一种称为小波阈值的减少方法。生成的图像几乎与报告的洪水区域相吻合。在此，具有不同空间和光谱分辨率的卫星图像融合在有效地可视化信息方面起着重要作用。 GIS相关技术在洪水监测和破坏评估中非常有用。在这项研究中。 GIS和遥感技术提供了更好的评估方法，有助于了解全局，并在紧急情况下如洪水般稳固地建立了对全球灾难的快速响应，并且随着上述技术的出现，洪水监测已成为一项轻松的任务。

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