Application of SBAS-InSAR technology in deformation monitoring of mountain in Kunming South Railway Station

doi:10.13474/j.cnki.11-2246.2024.0126

Abstract

Abstract: Landslide has a serious impact on human safety. The traditional landslide deformation monitoring has high cost, time consuming and low efficiency. The synthetic aperture radar interferometry (InSAR) landslide deformation monitoring technology can improve efficiency and save cost. Based on SBAS-InSAR technology, we process 24 sentinel-1 rail drop data from January 1,2019 to December 31,2019, obtained the deformation rate of the study area as -11.56~13.08 mm/a, processing of the sentinel 2 optical data using the pixel dichotomous model, obtained the vegetation coverage of the region in 2019.The deformation of the study area was combined with six typical deformation points. The results of the study show that, the west side of the mountain is the main deformation area, small area variable with high vegetation cover, large area shape variable with low vegetation cover. This study is of great significance for the safety monitoring of Kunming South Railway Station.

Key words: synthetic aperture radar interferometric measurement, deformation monitoring, deformation rate, dimidiate pixel model, vegetation coverage

CLC Number:

P258

LI Zerun, XI Wenfei, ZHAO Zilong, LIU Haihong, ZHANG Yuying, ZHANG Liting. Application of SBAS-InSAR technology in deformation monitoring of mountain in Kunming South Railway Station[J]. Bulletin of Surveying and Mapping, 2024, 0(1): 150-154.

References

[1] 喜文飞,赵子龙,李国柱,等.SBAS-InSAR技术与无人机影像融合的滑坡变形监测[J]. 测绘通报,2022(10): 1-6.
[2] 郭宁,张俊义,杨秀元,等. 云南昭通窝子箐滑坡稳定性分析[J]. 山地学报,2016,34(3): 305-309.
[3] 张勤,黄观文,杨成生. 地质灾害监测预警中的精密空间对地观测技术[J]. 测绘学报,2017,46(10): 1300-1307.
[4] 朱武,张勤,丁晓利. 多参考点的PS-InSAR变形监测数据处理[J]. 测绘学报,2012,41(6): 886-890.
[5] 何秀凤,高壮,肖儒雅,等. 多时相Sentinel-1A InSAR的连盐高铁沉降监测分析[J]. 测绘学报,2021,50(5): 600-611.
[6] 康亚,赵超英,张勤,等. InSAR滑坡探测技术研究: 以金沙江乌东德水电站段为例[J]. 大地测量与地球动力学,2018,38(10): 1053-1057.
[7] 朱建军,李志伟,胡俊. InSAR变形监测方法与研究进展[J]. 测绘学报,2017,46(10): 1717-1733.
[8] 孙倩,胡俊,陈小红. 多时相InSAR技术及其在滑坡监测中的关键问题分析[J]. 地理与地理信息科学,2019,35(3): 37-45.
[9] 戴可人,铁永波,许强,等. 高山峡谷区滑坡灾害隐患InSAR早期识别: 以雅砻江中段为例[J]. 雷达学报,2020,9(3): 554-568.
[10] 赵超英,刘晓杰,张勤,等. 甘肃黑方台黄土滑坡InSAR识别、监测与失稳模式研究[J]. 武汉大学学报(信息科学版),2019,44(7): 996-1007.
[11] 李梦华,张路,董杰,等. 四川茂县岷江河谷区段滑坡隐患雷达遥感识别与形变监测[J]. 武汉大学学报(信息科学版),2021,46(10): 1529-1537.
[12] DONG Jie,ZHANG Lu,TANG Minggao,et al. Mapping landslide surface displacements with time series SAR interferometry by combining persistent and distributed scatterers: a case study of Jiaju landslide in Danba,China[J]. Remote Sensing of Environment,2018,205: 180-198.
[13] 姚鑫,邓建辉,刘星洪,等. 青藏高原泛三江并流区活动性滑坡InSAR初步识别与发育规律分析[J]. 工程科学与技术,2020,52(5): 16-37.
[14] 葛大庆,王艳,郭小方,等. 利用短基线差分干涉纹图集监测地表形变场[J]. 大地测量与地球动力学,2008,28(2): 61-66.
[15] 杨正荣,喜文飞,史正涛,等. 复杂植被山区滑坡蠕变与植被覆盖度关系研究[J]. 测绘科学,2023,48(1): 157-165.
[16] LANARI R,CASU F,MANZO M,et al. An overview of the small baseline subset algorithm: a DInSAR technique for surface deformation analysis[J].Pure and Applied Geophysics,2007(4):164.
[17] 王霞迎,赵超英,尹慧芳. 地表形变时间序列InSAR监测法综述[J]. 地球物理学进展,2018,33(4): 1430-1437.
[18] KUZUOKA S,MIZUNO TApplications of PS-InSAR for non-urbanized area[J]. Journal of the Remote Sensing Society of Japan,2003,24(2):140-152.
[19] BERARDINO P,FORNARO G,LANARI R,et al. A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms[J]. IEEE Transactions on Geoscience and Remote Sensing,2002,40(11): 2375-2383.
[20] TIZZANI P,BERARDINO P,CASU F,et al. Surface deformation of Long Valley caldera and Mono Basin,California,investigated with the SBAS-InSAR approach[J]. Remote Sensing of Environment,2007,108(3): 277-289.
[21] 喜文飞,杨正荣,赵子龙,等. 基于SBAS-InSAR技术的小区域沉降监测研究[J]. 云南师范大学学报(自然科学版),2022,42(4): 41-44.