詹瑜璋:瞭解山崩和侵蝕作用:以多學科視角研究山崩偵測、坡體破壞和沈積物輸送 (Yu-Chang Chan:Understanding the Landslide and Erosion Processes: Multidisciplinary Research on Landslide Detection, Slope Failure, and Sediment Transport), 2019/01- 2021/12(3yrs)…
In this study, we combined satellite radar interferometry with satellite-derived soil moisture data to investigate two slow-moving landslides in different geological settings. The results show contrasting relationships between surface displacement and soil moisture. In sedimentary rocks, seasonal displacement is negatively correlated with soil moisture and is interpreted to be dominated by hydrological loading associated with water storage. In metamorphic rocks, the positive correlation suggests that increased pore-water pressure plays a more important role. The study demonstrates that integrating satellite displacement and soil moisture observations can help distinguish regular seasonal fluctuations from abnormal acceleration, improving the interpretation and early warning of slow-moving landslides.
本研究結合衛星雷達干涉技術與衛星土壤含水量資料,分析兩處位於不同地質環境中的緩慢移動型山崩。結果顯示,沉積岩區的地表位移與土壤含水量呈負相關,可能主要受到水分儲存所產生的水文負載影響;變質岩區則呈正相關,顯示孔隙水壓增加可能是控制位移的重要因素。研究說明,整合衛星地表位移與土壤含水量資料,可補充山區地面水文監測的不足,並協助區分正常的季節性波動與異常加速位移,提升緩慢移動型山崩監測與預警的判讀能力。
This study focuses on detecting and monitoring slow-moving landslides in Taiwan using a sophisticated radar technique. Identifying over 2500 pre-existing landslides is crucial for assessing their activity, especially before typhoon seasons. The proposed method, "multi-snap2stamps," effectively analyzes nine slow-moving landslides, revealing seasonal patterns in two sites and accelerated movement in one. The study showcases the potential of the method for large-scale landslide detection and monitoring.
A long-term landslide on the Huafan University campus in Taiwan, observed since 1990, lacks reliable monitoring data post-2018 due to equipment maintenance issues. This study employs multitemporal interferometry (MTI) using Sentinel-1 SAR images from 2014–2019 to monitor the landslide. MTI reveals consistent slow-moving areas with previous studies, indicating gravity-induced deformation and seasonal surface fluctuations linked to precipitation. This technique compensates for the lack of data and aids in evaluating and monitoring landslides for potential early warnings.