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首页> 外文期刊>Remote Sensing >ALOS/PALSAR InSAR Time-Series Analysis for Detecting Very Slow-Moving Landslides in Southern Kyrgyzstan
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ALOS/PALSAR InSAR Time-Series Analysis for Detecting Very Slow-Moving Landslides in Southern Kyrgyzstan

机译:ALOS / PALSAR InSAR时间序列分析,用于检测吉尔吉斯斯坦南部极缓慢移动的滑坡

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摘要

This study focuses on evaluating the potential of ALOS/PALSAR time-series data to analyze the activation of deep-seated landslides in the foothill zone of the high mountain Alai range in the southern Tien Shan (Kyrgyzstan). Most previous field-based landslide investigations have revealed that many landslides have indicators for ongoing slow movements in the form of migrating and newly developing cracks. L-band ALOS/PALSAR data for the period between 2007 and 2010 are available for the 484 km2 area in this study. We analyzed these data using the Small Baseline Subset (SBAS) time-series technique to assess the surface deformation related to the activation of landslides. We observed up to ±17 mm/year of LOS velocity deformation rates, which were projected along the local steepest slope and resulted in velocity rates of up to −63 mm/year. The obtained rates indicate very slow movement of the deep-seated landslides during the observation time. We also compared these movements with precipitation and earthquake records. The results suggest that the deformation peaks correlate with rainfall in the 3 preceding months and with an earthquake event. Overall, the results of this study indicated the great potential of L-band InSAR time series analysis for efficient spatiotemporal identification and monitoring of slope activations in this region of high landslide activity in Southern Kyrgyzstan.
机译:这项研究的重点是评估ALOS / PALSAR时间序列数据在分析天山南部(吉尔吉斯斯坦)高山Alai山脉山麓带深层滑坡活化作用方面的潜力。以前的大多数基于现场的滑坡调查都显示,许多滑坡都以移动和新出现的裂缝的形式指示着正在进行的缓慢运动。本研究可获得484 km 2 地区2007年至2010年期间的L波段ALOS / PALSAR数据。我们使用小型基线子集(SBAS)时间序列技术分析了这些数据,以评估与滑坡激活相关的表面变形。我们观察到的LOS速度变形率高达±17 mm /年,这是沿着局部最陡的坡度投影的,并且导致的速度率高达-63 mm / year。所获得的速率表明深层滑坡在观测时间内的移动非常缓慢。我们还将这些运动与降水和地震记录进行了比较。结果表明,变形峰值与前三个月的降雨和地震事件有关。总的来说,这项研究的结果表明,L波段InSAR时间序列分析对于有效地识别和监测吉尔吉斯斯坦南部高滑坡活动地区的斜坡活化具有巨大潜力。

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