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  • 學位論文

高精度山坡地變形變異分析初探

Preliminary Study of High Accuracy Landslide Deformation Analysis

指導教授 : 王國隆

摘要


台灣位在菲律賓海板塊和歐亞板塊交界,處於環太平洋地震帶,屬於副熱帶季風氣候區,頻繁的板塊運動使全台灣有百分之七十以上的面積是山坡地,高聳的山區地形受到強烈的風化作用影響,加上夏、秋兩季豐沛的降雨及颱風的侵襲,山區邊坡容易發生崩塌或地滑;然而多處崩塌地位置偏遠,傳統的監測方式需要到現地進行測量,並換取現地儀器的SD卡,取回資料進行分析,耗時耗力,遇到狀況無法即時反應,甚至因為SD卡滿載導致資料蒐集不全,精度更是一大考驗,故本研究將探討運用現地靜態測量結合靜態基線解算監測邊坡的可行性。 相較於傳統的測量方法,靜態基線測量配合無線網路的傳輸,能有效的減少時間成本及人力成本且安全,不用到現地就能取得即時且高精度的位移資料,再定期以無人飛行載具進行航拍,搭配軟體進行建模,產製正射影像圖及數值地形圖,並利用粒子影像分析,嘗試觀察邊坡滑動的情形。 本研究以廬山為研究區域,廬山位於南投縣仁愛鄉精英村內,歷年來發生多次降雨導致邊坡滑動。研究結果顯示,在2017年6月1日豪雨過後各測站都量測到5到20公分不等的位移。本研究以2017年6月1日前後的正射影像進行粒子影像分析,經粒子影像分析顯示幾乎整個坡體都處於滑移狀態,本研究區應持續進行追蹤監測。

並列摘要


Taiwan is located on Pacific Rim seismic area where between Eurasian Plate and Philippine Sea Plate. Typhoons usually attack during summer and steep mountains are highly weathered, which induces landslide in mountain area. However, most landslides are not east to access. Field investigation is time consuming, high budget, limited data collected and dangerous. Traditional GPS monitoring methods need to be measured locally, and exchange SD card for the local equipment. Even when the SD card is full, the data collection is not complete, and the accuracy also is a big challenge. Thus the possibility for high accuracy slope monitoring with static GPS measurement is proposed and discussed in this research. Compared with the traditional measurement, static baseline measurement with wireless network transmission can effectively reduce the time cost and labor costs.We can get immediate and accurate displacement data without go to GPS stations. Moreover, using aerial photos to build orthophoto and digital terrain mode, we try to observe the deformation behavior of the slope slides with Particle Image Velocimetry.In this study, the scope of this research is Lu-Shan Mountain, located in Ren-ai town Nantou County. The result shows that each stations measured 5 to 20 cm displacement after the heavy rain in June, 2017. Particle image displacement was analyzed with orthophoto images before and after June, 2017. Both GPS derived data and particle image displacements show that Lu-Shan Mountain is still not stable and deforming. Continuous monitoring should be carried on in this study area.

並列關鍵字

static GPS UAV Slope Stability PIV

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