Geological disasters occur frequently along the China-Pakistan Corridor, and the monitoring of small surface deformations can help discriminate and analyze the geological disasters in the study area, which is of great significance to the construction of the corridor and the protection of basic engineering facilities along the corridor. Based on a total of 30 Sentinel-1A radar images in the interference wide-range mode acquired from April 5, 2015 to December 9, 2018, the time-series surface deformation extraction of the Gaizi valley section of China-Pakistan Corridor was carried out using PS-InSAR and SBAS-InSAR technologies. The results show that the deformation information obtained by the two methods is rather consistent in the spatial variation trend of deformation rate, and the deformation rate map obtained by the SBAS-InSAR technology is relatively more continuous in spatial distribution. According to the SBAS-InSAR deformation results, during the analysis period, obvious surface deformation occurred in many places in the study area, and the relatively large line-of-sight deformation mainly distributed on the slopes on both sides of the China-Pakistan Highway and on the glacial front area northern to the Bulunkou. Using the extracted time series deformation information and with the help of optical images, the deformation characteristics of typical unstable slopes and glacial movements were analyzed. On unstable slope, the cumulative deformation of PS points on the upper part of the slope can reach -30mm during the monitoring period. In terms of glacier movement, many PS points with large positive and negative deformation values are concentrated on the front edge of the glacier, and the cumulative positive and negative deformations can reach +60 mm and -80 mm. The paper can accumulate preliminary experience for the detection of geological hazard related deformation in the alpine mountain area and benefit for its future applications to the China-Pakistan Corridor.
WANG Yuqing
,
TANG Lingli
,
WANG Xinhong
,
ZHOU Zengguang
,
LI Ziyang
,
LI Chuanrong
. Land surface deformation analysis based on time series InSAR technologies in the Gaizi valley section of China-Pakistan Corridor[J]. Journal of University of Chinese Academy of Sciences, 2022
, 39(3)
: 343
-351
.
DOI: 10.7523/j.ucas.2020.0046
[1] 李丹, 杨斌, 陈财. 基于Sentinel-1A数据反演九寨沟地震地表形变场[J]. 遥感技术与应用, 2018, 33(6): 1141-1148. DOI:10.11873/j.issn.1004-0323.2018.6.1141.
[2] Huang Q H, Wang Y A, Xu J, et al. Geo-hazard detection and monitoring using SAR and optical images in a snow-covered area: the Menyuan (China) test site[J]. ISPRS International Journal of Geo-Information, 2017, 6(10): 293. DOI:10.3390/ijgi6100293.
[3] Solaro G, Acocella V, Pepe S, et al. Anatomy of an unstable volcano from InSAR: multiple processes affecting flank instability at Mt. Etna, 1994-2008[J]. Journal of Geophysical Research: Solid Earth, 2010, 115(B10): B10405. DOI:10.1029/2009JB000820.
[4] Cheng X, Li X W, Shao Y, et al. DINSAR measurement of glacier motion in Antarctic Grove Mountain[J]. Chinese Science Bulletin, 2007, 52(3): 358-366. DOI:10.1007/s11434-007-0054-y.
[5] 张诗玉, 李陶, 夏耶. 基于InSAR技术的城市地面沉降灾害监测研究[J]. 武汉大学学报 ·信息科学版, 2008, 33(8): 850-853,858.
[6] Wang H, Wright T J, Yu Y P, et al. InSAR reveals coastal subsidence in the Pearl River Delta, China[J]. Geophysical Journal International, 2012, 191(3): 1119-1128. DOI:10.1111/j.1365-246X.2012.05687.x.
[7] Rizo V, Tesauro M. SAR interferometry and field data of Randazzo landslide (Eastern Sicily, Italy)[J]. Physics and Chemistry of the Earth Part B: Hydrology Oceans and Atmosphere, 2000, 25(9): 771-780. DOI:10.1016/S1464-1909(00)00100-3.
[8] 王志勇, 张金芝. 基于InSAR技术的滑坡灾害监测[J]. 大地测量与地球动力学, 2013, 33(3): 87-91. DOI:10.14075/j.jgg.2013.03.001.
[9] 秦晓琼, 杨梦诗, 王寒梅, 等. 高分辨率PS-InSAR在轨道交通形变特征探测中的应用[J]. 测绘学报, 2016, 45(6): 713-721. DOI:10.11947/j.AGCS.2016.20150440.
[10] Ferretti A, Prati C, Rocca F. Nonlinear subsidence rate estimation using permanent scatterers in differential SAR interferometry[J]. IEEE Transactions on Geoscience and Remote Sensing, 2000, 38(5): 2202-2212. DOI:10.1109/36.868878.
[11] 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. DOI:10.1109/TGRS.2002.803792.
[12] Werner C, Wegmuller U, Strozzi T, et al. Interferometric point target analysis for deformation mapping[ C ] // 2003 IEEE International Geoscience and Remote Sensing Symposium-IGARSS 2003. July 21-25, 2003, Toulouse, France. IEEE, 2003: 4362-4364. DOI:10.1109/IGARSS.2003.1295516.
[13] Hooper A. A multi-temporal InSAR method incorporating both persistent scatterer and small baseline approaches[J]. Geophysical Research Letters, 2008, 35(16): L16302. DOI:10.1029/2008GL034654.
[14] 赵峰, 汪云甲, 闫世勇. 时序InSAR技术地表沉降监测结果可靠性及沉降梯度分析[J]. 遥感技术与应用, 2015, 30(5): 969-979. DOI:10.11873/j.issn.1004-0323.2015.5.0969.
[15] 殷宗敏. 基于时序InSAR技术与地形特征的黄土高原潜在滑坡识别研究:以绥德县城为例[D]. 兰州: 兰州大学, 2018.
[16] 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, 36(1): 91-97. DOI:10.16089/j.cnki.1008-2786.000304.
[17] 李凌婧, 姚鑫, 张永双, 等. 基于SBAS-InSAR技术的中巴公路(公格尔—墓士塔格段)地质体缓慢变形识别研究[J]. 工程地质学报, 2014, 22(5): 921-927. DOI:10.13544/j.cnki.jeg.2014.05.022.
[18] 谷志文. 中国标准在中巴经济走廊地质灾害多发区公路改建工程的应用[J]. 筑路机械与施工机械化, 2018, 35(6): 151-156. DOI:10.3969/j.issn.1000-033X.2018.06.026.
[19] 朱颖彦, 杨志全, 廖丽萍, 等. 中巴喀喇昆仑公路冰川地貌地质灾害[J]. 灾害学, 2014, 29(3): 81-90. DOI:10.3969/j.issn.1000-811X.2014.03.016.
[20] 杨志全, 朱颖彦, 廖丽萍, 等. 中巴公路沿线溜石坡[J]. 地质科技情报, 2013, 32(6): 175-180.
[21] 王宗盛. "中巴经济走廊"(中国段)冰川地质灾害调查与评价[D]. 北京: 中国地质大学(北京), 2016.
[22] 杨魁, 杨建兵, 江冰茹. Sentinel-1卫星综述[J]. 城市勘测, 2015(2): 24-27. DOI:10.3969/j.issn.1672-8262.2015.02.006.
