Monitoring of sluice subsidence along the Yangtze River based on time-series InSAR technology

doi:10.13474/j.cnki.11-2246.2025.1020

Abstract

Abstract: Sluice play an important role in disaster prevention and mitigation, shipping and transportation, as well as agricultural irrigation.It is significant to strengthen the settlement monitoring of sluice to ensure their safe and stable operation.The settlement monitoring of Dongxingang sluice and Dongjiajiang sluice was carried out using PS-InSAR technology to extract the time-series settlement results of the sluices from 2016 to 2020.The results were then compared with those obtained using the SBAS-InSAR method.Finally, the causes of sluice settlement were discussed.The results indicated that Dongxingang sluice and Dongjiajiang sluice settled at a rate of -5.00 and -3.37 mm/a, respectively; By comparing the monitoring results of PS-InSAR and SBAS-InSAR, it can be seen that the annual deformation rate differences for both sluice gates are within 2 mm, and the coefficient of determination for the time-series settlement monitoring results of both methods is above 0.77, indicating a high degree of consistency and reliability between the two methods.The soil texture type dominated by powdery loam and the special topographic features of Hissing Horse Bend may affected the stability of the sluice.Decreases in groundwater levels and sluice water levels may aggravate the settlement of the sluice.Additionally, high-density urban development impacted soil stress, potentially causing settlement in the sluice area.

Key words: sluice, land subsidence, time-series InSAR, Sentinel-1A

CLC Number:

P237

WANG Yihong, SHI Yifan, WU Yongfeng, LIANG Wenguang. Monitoring of sluice subsidence along the Yangtze River based on time-series InSAR technology[J]. Bulletin of Surveying and Mapping, 2025, 0(10): 119-126.

References

[1] 卢旺达,韩春明,岳昔娟,等. 基于Sentinel-1A数据的天津地区PS-InSAR地面沉降监测与分析[J]. 遥感技术与应用,2020,35(2):416-423. [2] 罗文林,侯伟,韩煊,等. 北京东部区域地面沉降现状及其发展趋势预测[J]. 湖南科技大学学报(自然科学版),2015,30 (2):52-59. [3] 邱志伟,岳建平,汪学琴,等. 基于短基线集技术的城市地表沉降监测研究[J]. 测绘通报,2016 (7):25-29. [4] 张又又. 基于时序InSAR技术的天津郊区地面沉降监测应用[J]. 城市勘测,2016(6):65-69. [5] 金亚秋. 微波遥感及其在中国的发展[J]. 微波学报,2020,36(1):1-6. [6] 何平,许才军,温扬茂,等. 时序InSAR的误差模型建立及模拟研究[J]. 武汉大学学报(信息科学版),2016,41(6):752-758. [7] 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. [8] 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. [9] 陈媛媛,朱晨玮,郑加柱,等. 基于PS-InSAR与SBAS-InSAR的地面沉降监测分析:以长江南京段沿江区域为例[J]. 人民长江,2023,54(8):160-165. [10] 陈媛媛,赵秉琨,王慧,等. 基于LSTM模型的时序InSAR地表形变预测[J]. 人民长江,2024,55(3):146-152. [11] 陈艳青,赵景堂. 基于时序InSAR技术监测大桥历史形变[J]. 测绘工程,2021,30(2):50-54. [12] 段伟,吕孝雷. 一种新的桥梁区域时序InSAR相位解缠方法[J]. 中国科学院大学学报,2019,36 (2):251-258. [13] 朱茂,沈体雁,吕凤华,等. 青岛胶州湾跨海大桥InSAR形变数据分解和信息提取[J]. 遥感学报,2020,24 (7):883-893. [14] 肖儒雅,何秀凤. 时序InSAR水库大坝形变监测应用研究[J]. 武汉大学学报(信息科学版),2019,44(9):1334-1341. [15] 张红忠,黄静,崔龙,等. 基于SBAS-InSAR技术的新疆WLL水库沉降监测与分析[J]. 大地测量与地球动力学,2022,42(6):601-605. [16] 杨星,肖怀前,侯苗,等. 基于InSAR技术的江苏水闸垂直位移监测方法可行性探讨[J]. 大地测量与地球动力学,2021,41(9):895-898. [17] 管飞,叶明亮,马友华. 江淮丘陵区土壤可蚀性K值研究:以肥东县为例[J]. 中国农学通报,2020,36(1):105-111. [18] 戚海博,顾凯,张博,等. 基于单孔热响应测试的地下水渗流场评价—以扬中指南村崩岸场地为例[J]. 工程地质学报,2022,30(5):1713-1720. [19] 陶虹,丁佳. 关中城市群开采地下水有关环境地质问题及其防治对策建议[J]. 地质论评,2014,60(1):231-235. [20] 刘刚,徐成华,施威,等. 南京河西地区地面沉降成因分析[J]. 地质论评,2023,69(2):639-647. [21] 贾茹雪. 基于时空特性的大堤变形智能预测及多源评价方法[D]. 长沙:中南大学,2023. [22] 高二涛,范冬林,付波霖,等. 基于PS-InSAR和SBAS技术监测南京市地面沉降[J]. 大地测量与地球动力学,2019,39(2):158-163.