|
DS-InSAR技术在复杂艰险山区滑坡形变监测中的应用前景研究
|
Abstract:
分布式目标雷达干涉(DS-InSAR)技术既继承了传统InSAR技术观测范围广、自动化程度高等技术优势,又能提高复杂艰险山区时序InSAR相干点密度,可应用于滑坡形变监测。本文利用覆盖康定附近的Sentinel-1A升轨影像,基于KS统计检验方法和自适应滤波,提取出了位于岩屑区、裸露土坡的DS点,并进行滑坡形变分析,实验结果为:该滑坡区域在2017年3月~2018年10月的监测时间内,年平均沉降速率约为10.9 mm/y,最大沉降量达到21.0 mm;且发生较大沉降时间段主要集中于每年5~8月,与该区域集中降雨时间相符。实验表明DS-InSAR技术对复杂艰险山区进行滑坡形变监测具有重要的参考价值。
Distributed scatter InSAR (DS-InSAR) not only has the advantage of large scope of observation and high degree of automation in traditional InSAR technology, but also can increase the coherence point density of time series InSAR in complex and dangerous mountainous areas. Therefore, it could be used into landslide deformation monitoring. This paper used Sentinel-1A ascending images covering some areas of Kangding city as the experiment data. DS points located in debris and bare soil slope area were extracted by applying KS statistical test method and adaptive filtering. And then landslide deformation analysis is carried out. The result shows that the average annual subsidence velocity of the landslide area is about 10.9 mm/y and the maximum settlement is 21.0 mm. The large subsidence period is mainly concentrated from May to August each year, which coincides with the time of concentrated rainfall in this area. Experiment shows that DS-InSAR technology has important reference value for landslide deformation monitoring of complex and dangerous mountain area.
[1] | 刘国祥, 丁晓利, 陈永奇, 等. 极具潜力的空间对地观测新技术——合成孔径雷达干涉[J]. 地球科学进展, 2000, 15(6): 734-735. |
[2] | 王超, 张红, 刘智. 星载合成孔径雷达干涉测量[M]. 北京: 科学出版社, 2002. |
[3] | Ferretti, A., Prati, C. and Rocca, F.L. (2001) Permanent Scatterers in SAR Interferometry. IEEE Transactions on Geoscience and Remote Sensing, 39, 8-20. https://doi.org/10.1109/36.898661 |
[4] | 贾洪果, 刘国祥, 于冰. 基于超短基线PSInSAR的道路网沉降监测[J]. 测绘通报, 2012(5): 24-28. |
[5] | Werner, C., Wegmüller, U., Strozzi, T. and Wies-mann, A. (2003) Interferometric Point Target Analysis for Deformation Mapping. Proceedings of 2003 IEEE Interna-tional Geoscience and Remote Sensing Symposium (IGARSS2003), Toulouse, 21-25 July 2003, 4362-4364. |
[6] | 张海波, 李宗春, 许兵, 等. IPTA方法在地面沉降监测中的应用[J]. 测绘科学技术学报, 2016, 33(2): 145-149. |
[7] | 傅文学, 田庆久, 郭小方, 等. PS技术及其在地表形变监测中的应用现状与发展[J]. 地球科学进展, 2006, 21(11): 1193-1198. |
[8] | Kuzuoka, S., Ferretti, A. and Novali, F. (2013) An Advanced InSAR Algorithm for Surface Defor-mation Monitoring: SqueeSARTM. Conference Proceedings of 2013 Asia-Pacific Conference on Synthetic Aperture Ra-dar (APSAR), Tsukuba, 23-27 September 2013, 336-337. |
[9] | 李涛. 基于点面散射体的多时相雷达干涉模型与形变探测方法[D]: [博士学位论文]. 成都: 西南交通大学, 2014. |
[10] | Hooper, A. and Zebker, H.A. (2007) Phase Un-wrapping in Three Dimensions with Application to InSAR Time Series. Journal of the Optical Society of America A: Optics Image Science & Vision, 24, 2737. https://doi.org/10.1364/JOSAA.24.002737 |
[11] | Hooper, A., Zebker, H., Segall, P., et al. (2004) A New Method for Measuring Deformation on Volcanoes and Other Natural Terrains Using InSAR Persistent Scatterers. Geophysical Research Letters, 31, L23611. https://doi.org/10.1029/2004GL021737 |
[12] | 张诗茄, 蒋建军, 缪亚敏, 等. 基于SBAS技术的岷江流域潜在滑坡识别[J]. 山地学报, 2018(1): 91-97. |
[13] | 刘岁海, 刘爱平. 四川省康定县地质灾害特征及其形成机理研究[J]. 水土保持研究, 2006, 13(2): 226-229. |
[14] | 吴昆林. 四川康定县木洼沟泥石流成因机制及防治[J]. 山西建筑, 2015, 41(20): 70-72. |