地形計測方法應用於潛在大規模崩塌之判釋

Potential Catastrophic Landslides Mapping by Using Geomorphometric analysis

謝有忠(Yu-Chung Hsieh) ； 侯進雄(Chin-Shyong Hou) ； 胡植慶(Jyr-Ching Hu) ； 費立沅(Li-Yuan Fei) ； 陳宏仁(Hung-Jen Chen) ； 邱禎龍(Cheng-Lung Chiu) ； 詹瑜璋(Yu-Chang Chan)

《航測及遙測學刊》 20卷4期 (2016/06) Pp. 263-277

https://doi.org/10.6574/JPRS.2016.20(4).3

摘要

莫拉克風災後，針對大規模崩塌的研究顯得刻不容緩。本研究利用中央地質調查所現有之1米數值地形資料，有別於傳統判釋方法，空載光達資料更能應用於坡地災害的分析。本研究以不同之地形計測方法來進行資料分析，其中透過融合坡度、地形陰影、地形開闊度等方法之結果，可以突顯細微地形特徵或變化處，此法不僅可提升崩塌地特徵之判釋速度，也能減少人為誤判而有效找出潛在大規模崩塌的位置，確實對潛在大規模崩塌的判釋和調查有很大的助益。未來搭配後續調查研究，進一步探討坡面地質災害的可能成因和規模或影響範圍，可為現今防救災策略上必需的重要資訊。

關鍵字

數值地形模型 ； 空載光達 ； 地形測計學 ； 大規模崩塌 ； 自然災害

並列摘要

Extreme weather events have induced more frequent geological hazards in Taiwan. The heavy rainfall brought by the Typhoon Morakot has triggered a large amount of landslides including the Xiaolin village which was demolished by a catastrophic Landslides. The study of such catastrophic landslides is urgently needed. It is considered that the creep phase of a landslides is a preparatory stage of progressive failure and gives enough signals before turning into a catastrophic landslides. This study used high-resolution airborne LiDAR-derived DEM data from the Central Geological Survey, MOEA. We used different geomorphometric analyses to process the high resolution and high accuracy DEM data including the hillshade, aspect, slope, eigenvalue ratio & openness. Among these geomorphometric analyses, which to converged openness, slope and hillshade method of the results, the capacity to discuss the possible cause and the influence analysis of the catastrophic Landslides in view of the slight terrain features has increased drastically through DEM processing. Our results indicate that over hundreds potential catastrophic landslides may present in southern Taiwan after the Typhoon Morakot event. The quantitative methods used in this study highlight the terrain features of the creep phase of catastrophic landslides and is helpful for landslide feature interpretation and hazard assessment.

並列關鍵字

airborne LiDAR ； DEM ； catastrophic landslides ； Geomorphometry ； natural hazard