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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/65865


    Title: 龜山島周圍海域熱液與地震的關係
    Authors: 李聿文;Li,Yu-wen
    Contributors: 遙測科技碩士學位學程
    Keywords: 龜山島;SPOT;熱液;地震
    Date: 2014-07-24
    Issue Date: 2014-10-15 17:16:06 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 沖繩海槽南端的擴張處於萌芽階段,海槽底部熱液活動十分活躍,且微震活動平凡,龜山島就位於沖繩海槽最南端,熱螢光定年法顯示島上擄獲岩的形成年代約在7000±700年前,可以將龜山島視為一座活火山,未來有再噴發的可能性。龜山島的後火山活動包含熱液和地震,熱液變化可能反應出活動的劇烈程度,目前島上沒有熱液的長期監測,所以本研究將地震當作活動指標,比對熱液變化與地震,借此得出熱液變化與火山活動之間的關係。
    龜山島東側的熱液因含有硫,使熱液顏色與周圍海水不同,用肉眼即可分辨,熱液導致海水顏色的變化也可由衛星影像偵測到,所以可以利用衛星影像對龜山島做長期監測。本文配合地震資料,針對2008年熱液進行研究,衛星影像分析有三個的步驟:(1)去除陸地的千擾;(2)去除雲的干擾;(3)進行影像分類。第一步的遮罩是由ENVI建立,能涵蓋每張影像中的陸地區域,遮罩除了可以移除陸地區域還可以必免近岸海浪的影響。去除陸地區域之後,第二步是用自動閥值選取去除雲,可以明確的區分背景與雲層,自動閥值選取非常適合拿來去除厚雲,但是無法去除薄雲。第三步是影像分類,完全限制最小平方法可以讓值控制在0到1之間,在熱液這分類中取值大於0.5的區域作為熱液面積,將面積內的值加總可粗略獲得熱液量,趨勢和面積差不多。
    2008年的地震大致上分為三群,1月、8月和12月,從結果的整體來看時間序列上熱液面積較大的時候多發生在群震的周圍,仔細針對熱液前後發生的地震做分析,結果顯示不管是熱液面積還是量都與前後1天有最大的相關,最高的相關係數是0.698,照相關係數來看比起前幾天的地震,後幾天發生的地震與熱液面積的關聯比較大。雖然地震數量與影像數量落差很大,而且無實際資料比對,使結果不夠準確,但是在直接的長期監測出現之前,遙測是最好的長期監測方式。
    ;Guishan Island is located at north eastern Taiwan belongs to Yilan County. According to geophysical and geochemical studies, Guishan Island is an active volcano, and the latest eruption occurred in the Holocene (7 ka). The active hydrothermal vents and earthquake can be considered as manifestations of volcanic activity. There are some hydrothermal vents at eastern offshore, and the fluids from the vents are mostly made up of sulfur, which cause the discoloration of the ocean around Guishan Island. The discolored area is called plume which can be easily detected by satellite image. The shape and size of plume are disturbed by ocean currents or winds. In this study, we detect the plume area by three steps: (1) remove land area; (2) remove cloud area; (3) classification. First, ENVI is used to build a mask and remove land area. Followed by a fully constrained least squares approach, it is a mixed pixel classification method for concentration estimation in each pixel. Finally, the area of plume is calculated from the result of least square approach, and then compare with the number of earthquake events to find the relationship between them. In our experiment, 36 SPOT images in 2008 are adopted, and the result shows that the larger area of plume was occurred around the large cluster of events. The area of plume is related to earthquake but there isn′t clear. After the correlation coefficient is calculated, the result shows the area of plume is related to the number of earthquake events. The highest correlation coefficient is 0.68 in ±1day. It means maybe the earthquakes can cause the area of plume become larger.
    The number of earthquake event is 425 and the number of image is 36. Although the number is uneven, the best way for long term monitor is satellite image until there is a direct measurement.
    Appears in Collections:[遙測科技碩士學位學程] 博碩士論文

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