台灣受地震與強降雨所造成的地質災害頻傳，2009 年造成小林村滅村的莫拉克風災、1998 年因921 地震造成草嶺和九份二山大崩塌，以及林肯大郡的崩塌皆是受到地震或降雨促崩導致的深層滑動。
深層滑動為深度大於3 公尺之塊體滑動，屬於長時間、大範圍的活動，事先並不容易預測。目前已有研究證明大規模崩塌在破壞前會有細微的地形特徵產生，如裂隙、崩崖等。光達為新興的測繪技術，可快速地進行大範圍、高精度的掃描，其雷射光束能穿透樹層到達地面，目前已廣泛被應用於製作高精度的DEM 或DSM。
本研究即以具深層滑動的台18 線阿里山公路之五彎仔地區為測試區域，利用空載光達點雲製作DEM 並進行分析，另外以DSM、航拍影像套疊、比對來判釋可能的地形特徵線，再進行現場調查，驗證其關聯性。最後，透過研究整合判釋結果推估五彎仔滑動體的崩塌趨勢，提出以空載光達判釋之特徵線與深層滑動之關聯性並討論其適用性。五彎仔地區當地面點雲密度大於1 pts/m2 時，以空載光達產製1m × 1m DEM 並進行相關分析與圖層套疊、比對，可判釋出尺度大於0.5m × 12 m 之微地形特徵線。利用室內判釋與現場調查結果結合前人研究及監測資料，可知五彎仔崩塌上緣侵蝕速率平均每年約往東11 公尺，推估若於崩塌上緣約10 公尺距離內發現綿延長達數十公尺之特徵線時，極有可能在未來一年左右產生新的破壞。

Due to the climate change, geological hazards triggered by earthquake or rainfall are increased recently in Taiwan. Deep seated landslide is concerned with a slide surface deeper than 3 m. There are several large scale deep seated landslide cases in Taiwan, such as the Hsiaolin village destroyed by Typhoon Morakot in 2009, the Tsaolin and Jiu‐fen‐er Mountain Landslides caused by Chi‐chi earthquake in 1999. Several studies have noted that the precursors of deep seated landslide are micro geomorphology characters (scarps, cracks, etc.) resulted from the associating mass deformation. However, these characters are too small to be interpreted from the aerial or satellite photographs.
Airborne laser scanning, an up‐to‐date measurement technique, could cover a large area quickly and the data acquired have high level of accuracy. It has been widely employed to generate high precision DEM or DSM for various applications.
The aim of this study is to ascertain whether using LiDAR‐derived DEM would help to improve the interpretation of the micro geomorphology to the identification of the precursor from deep seated landslide. The LiDAR data was collected at Woo Wan Chai, which is a deep seated landslide region at Alishan, Southern Taiwan. The interpretation was carried out with LiDAR‐derived DEM, DSM and aerial photography. For verifying the feasibility, in‐situ investigation was conducted to examine the interpretation in the laboratory. Results of this study shown the linkage of micro geomorphology characters derived by LiDAR DEM to the deep seated landslide is highly related, and the distribution of the characters was consistent to the local historical events. In the region with no less than 1 pts/m2 ground LiDAR point, this method is applicable to interpret the micro geomorphology characters if it is larger than 0.5m × 12 m based on 1m × 1 m LiDAR‐derived DEM. In addition, these results implied that the failure plane may occur about a year at the micro geomorphology characters while they appear continuously within approximately 10m from the scarp for this particular example case.

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