Integration and Application of a Fiber-Optic Sensing System for Monitoring Debris Flows

This study presents an innovative fiber-optic sensing system for monitoring debris flows. The system mainly comprises an interrogator and four fiber Bragg grating accelerometers. The field tests show that signal-to-noise-ratio (SNR) of the fiber-optic sensor is 10 dB higher than that of a geophone. Following confirmation of the reliability of the proposed sensing system, the systems are deployed along the Ai-Yu-Zi and Chu-Shui Creeks in Nautou County, Taiwan, for monitoring debris flows. The four accelerometers are installed in series. The systems have detected several debris flows in 2012. The monitored data reveal that the frequency range of the acceleration of ground vibration is 10-150 Hz, which is the same as that of the velocity of ground vibration detected by a sensing system that includes geophones. Because the fiber-optic sensing system is more sensitive than the geophone system, the proposed fiber-optic sensing system is highly promising for use in monitoring natural disasters that generate ground vibrations.本研究藉由組合光纖光柵加速度計、解調儀、及其他相關元件，發展一套可偵測土 石流之光纖感測系統。現地測試結果顯示，與目前常用含地聲檢知器的土石流感測系統相較， 本系統所測得地表振動訊號之訊雜比比前者高10 dB。在測試系統量測效能後，將此系統分別 架設於南投縣信義鄉神木村之愛玉子溪及出水溪上。系統中採串連方式配置四個光纖加速度 計，並於2012 年監測到多場土石流。觀測結果顯示，光纖感測系統所測得土石流所造成地表 振動之加速度，與過去地聲檢知器所測得土石流地表振動速度，兩者頻率一樣，均為10–150 Hz。由於光纖光柵加速度計相較於地聲檢知器更為靈敏，因此，除了可應用於偵測土石流外， 也可應用於監測會產生地表振動的其他坡地災害，如：落石及山崩等

天空開闊度與局部立體模型於山崩判釋及地形變異評估： 以台東縣紅葉村為例

This study integrates pre-landslide high-resolution digital elevation model (DEM), digital surface model (DSM) produced using post-landslide drone photography, and geomorphometric analysis to explore the effectiveness of landslide interpretation and fast assessment of geomorphic change. In this study, the large-scale landslide that occurred in Hongye Village, Taitung County in Eastern Taiwan, on September 15, 2016, was investigated. We combined both the microtopography features from the DEM and canopy openness in the DSM to establish an assessment procedure for landslide hotspot extraction. Drone photography and three-dimensional modeling techniques were used to measure the sediment transportation process and conduct postdisaster influence area mapping. The results showed that the landslide area, mean sliding depth, and volume of the landslide in Hongye Village were approximately 4.5 ha, 5.1 m, and 22.8·104 m3, respectively. The runout distance of the initial landslide was 960 m and increased to 1.23 km when the landslide transformed into debris flow in the village. Field validation indicated that the landslideprone area and subsidence features on the forest canopy could be recognized using a sky-view factor relief and local relief model. Moreover, a complete landslide susceptibility assessment approach suitable for the catchment scale is presented.本研究結合山崩災前高精度數值地型與災後無人機攝影測量技術產製之地表數值模型，以地形計 測學常用之立體陰影圖，探討集水區內山崩判釋可行性及災後快速地貌變遷評估。本文以 2016 年 9 月 15 日 莫蘭蒂颱風誘發臺東縣延平鄉紅葉村山崩為例，萃取災前 DEM 山崩微地形判釋及 DSM 樹冠開闊度特徵，以 建立潛在山崩發生區判釋評估分析流程。另應用災後無人機拍攝影像之三維建模，配合災後地貌可研析山崩 土砂運移歷程及土石流影響範圍。地形變異分析顯示紅葉村崩塌區面積約 4.5 公頃，平均崩滑深度 5.1 公尺， 總崩塌量體約 22.8 萬立方公尺，山崩運移距離約為 957 公尺，轉化為土石流之總流動距離達 1.23 公里。由現 場調查與災後三維地形之驗證，崩塌邊界及林冠陷落特徵可於災前分別透過天空開闊度立體圖及局部立體模 型圖予以判釋。本研究最後提出適於潛在土砂災害識別之地形計測學指標與災害潛勢評估建議

愛玉子溪土石流之地動訊號特性與警戒方法之探討

Ground vibrations provide relevant flow conditions and may be used to warn of potential debris flow. To construct warning methods for debris flow, geophone ground vibration recordings from four debris flows at Ai-YuZi creek were analyzed. Based on time-frequency analysis, the effect of time span and frequency band were examined, and the representative indexes of accumulated power and accumulated power slope were extracted. With extracted indexes, we used ambient noise and scale factors to define warning thresholds. The warning times for debris flows were calculated with floating warning thresholds and then successfully validated by two events with a maximum error of 4.2 s.由地聲去監測土石流，除了可反應流況的特性也可用於事件的判釋。為了透過地聲訊號建立土石 流的判釋或警戒方式，本文以四場愛玉子溪的土石流為例，探討土石流事件的訊號特性，並依此有系統的建 立判釋指標與警戒門檻值。透過比較能量的平均延時及特徵頻率，本研究萃取出適用於判釋土石流的累積能 量與累積能量斜率指標，並由事件前的環境雜訊去建立該指標的警戒門檻值。透過浮動式門檻值計算的警戒 時間中，本文成功的透過兩場事件驗證土石流的到時，其最大誤差僅 4.2 秒