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Analysis of the Pyroclastic Flow Deposits of Mount Sinabung and Merapi Using Landsat Imagery and the Artificial Neural Networks Approach

机译:利用Landsat影像和人工神经网络方法分析Sinabung和Merapi山的火山碎屑流沉积物

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Volcanic eruptions cause pyroclastic flows, which can destroy plantations and settlements. We used image data from Landsat 7 Bands 7, 4 and 2 and Landsat 8 Bands 7, 5 and 3 to observe and analyze the distribution of pyroclastic flow deposits for two volcanos, Mount Sinabung and Merapi, over a period of 10 years (2001–2017). The satellite data are used in conjunction with an artificial neural network method to produce maps of pyroclastic precipitation for Landsat 7 and 8, then we calculated the pyroclastic precipitation area using an artificial neural network method after dividing the images into four classes based on color. Red, green, blue and yellow were used to indicate pyroclastic deposits, vegetation and forest, water and cloud, and farmland, respectively. The area affected by a volcanic eruption was deduced from the neural network processing, including calculating the area of pyroclastic deposits. The main differences between the pyroclastic flow deposits of Mount Sinabung and Mount Merapi are: the sediment deposits of the pyroclastic flows of Mount Sinabung tend to widen, whereas those of Merapi elongated; the direction of pyroclastic flow differed; and the area affected by an eruption was greater for Mount Merapi than Mount Sinabung because the VEI (Volcanic Explosivity Index) during the last 10 years of Mount Merapi was larger than Mount Sinabung.
机译:火山喷发导致火山碎屑流,可能破坏人工林和定居点。我们使用了来自Landsat 7波段7、4和2和Landsat 8波段7、5和3的图像数据,观察和分析了10年(2001年–锡那蓬山和默拉皮火山)的火山碎屑流沉积物的分布。 2017)。卫星数据与人工神经网络方法结合使用以生成Landsat 7和Landsat 8的火山碎屑降水图,然后根据图像将颜色分为四类,然后使用人工神经网络方法计算火山碎屑沉淀面积。红色,绿色,蓝色和黄色分别表示火山碎屑沉积,植被和森林,水和云以及农田。从神经网络处理中推导出受火山喷发影响的面积,包括计算火山碎屑沉积物的面积。锡纳蓬山和默拉皮山的火山碎屑流沉积物之间的主要区别是:锡纳蓬山的火山碎屑流的泥沙沉积趋于扩大,而默拉皮的沉积物拉长。火山碎屑流的方向不同;默拉皮火山的喷发影响面积大于锡那丰火山,因为默拉皮火山的最近十年的VEI(火山爆发指数)大于锡那蓬火山。

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