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Application of remote sensing in Coastal change detection after the Tsunami event in Indonesia

机译:遥感在印度尼西亚海啸事件发生后海岸变化检测中的应用

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Shoreline mapping and shoreline change detection are critical in many coastal zone applications. This study focuses on applying remote sensing technology to identify and assess coastal changes in the Banda Aceh, Indonesia. Major changes to land cover were found along the coastal line. Using remote sensing data to detect coastal line change requires high spatial resolution data. In this study, two high spatial data with 30 meter resolution of Landsat TM images captured before and after the Tsunami event were acquired for this purpose. The two satellite images was overlain and compared with pre-Tsunami imagery and with after Tsunami. The two Landsat TM images also were used to generate land cover classification maps for the 24 December 2004 and 27 March 2005, before and after the Tsunami event respectively. The standard supervised classifier was performed to the satellite images such as the Maximum Likelihood, Minimum Distance-to-mean and Parallelepiped. High overall accuracy (>80%) and Kappa coefficient (>0.80) was achieved by the Maximum Likelihood classifier in this study. Estimation of the damage areas between the two dated was estimated from the different between the two classified land cover maps. Visible damage could be seen in either before and after image pair. The visible damage land areas were determined and draw out using the polygon tool included in the PCI Geomatica image processing software. The final set of polygons containing the major changes in the coastal line. An overview of the coastal line changes using Landsat TM images is also presented in this study. This study provided useful information that helps local decision makers make better plan and land management choices.
机译:在许多沿海地区的应用中,海岸线测绘和海岸线变化检测至关重要。这项研究的重点是运用遥感技术来识别和评估印度尼西亚班达亚齐的沿海变化。在沿海地区发现了土地覆被的重大变化。使用遥感数据检测海岸线变化需要高空间分辨率数据。在这项研究中,为此目的,获取了两个海平面事件之前和之后捕获的30米分辨率Landsat TM图像的高空间数据。这两个卫星图像被覆盖,并与海啸之前和海啸之后的图像进行了比较。这两个Landsat TM影像还分别用于生成2004年12月24日和2005年3月27日海啸事件之前和之后的土地覆盖分类图。对卫星图像执行了标准监督分类器,例如最大似然,最小平均距离和平行六面体。在这项研究中,最大似然分类器实现了较高的总体准确性(> 80%)和Kappa系数(> 0.80)。根据两个分类的土地覆盖图之间的差异,估算了两个日期之间的损坏区域。在图像对之前和之后都可以看到可见的损坏。使用PCI Geomatica图像处理软件中包含的多边形工具确定并绘制可见的损坏区域。包含沿海线主要变化的多边形的最终集合。这项研究还概述了使用Landsat TM影像的沿海线变化。这项研究提供了有用的信息,可帮助当地决策者做出更好的计划和土地管理选择。

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