A first approach for displacement analysis in Lisbon Downtown using PS-InSAR

被引:5
|
作者
Roque, Dora [1 ]
Fonseca, Ana Maria [1 ]
Henriques, Maria Joao [1 ]
Falcao, Ana Paula [2 ]
机构
[1] Lab Nacl Engn Civil, P-1700066 Lisbon, Portugal
[2] Univ Lisbon, Inst Super Tecn, P-1049001 Lisbon, Portugal
关键词
Permanent Scatterers; subsidence; seasonal trend; Lisbon downtown; INTERFEROMETRY; DEFORMATION; SCATTERERS; SHANGHAI;
D O I
10.1016/j.protcy.2014.10.094
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Lisbon Downtown presents unique geomorphologic properties which makes it an area prone to terrain instability. Serious accidents have occurred there, namely, during the 1755 earthquake and a flooding event at the extension of a subway line, demanding a frequent monitorization for safety reasons and expense minimization. In this study, Permanent Scatterers technique is applied. The calculated displacement velocities are compared to those obtained from levelling operations. Possible causes for the discrepancy are presented in the paper. Besides a subsidence trend, a seasonal behaviour is also detected, probably related to aquifer recharge or tides. (C) 2014 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:288 / 293
页数:6
相关论文
共 50 条
  • [41] Mapping slow deformation of the middle segment of the West Qinling fault using the combined algorithm of CR-InSAR and PS-InSAR
    Xu Xiao-Bo
    Qu Chun-Yan
    Shan Xin-Jian
    Zhang Gui-Fang
    Ma Chao
    Yu Lu
    Meng Xiu-Jun
    CHINESE JOURNAL OF GEOPHYSICS-CHINESE EDITION, 2016, 59 (08): : 2796 - 2805
  • [42] Deep Learning Improves Point Density in PS-InSAR Data Toward Finer-Scale Land Surface Displacement Detection
    Safonova, Anastasiia
    Ryo, Masahiro
    IEEE ACCESS, 2024, 12 : 132754 - 132762
  • [43] Monitoring of millimeter-scale deformations in Tallinn using repeated leveling and PS-InSAR analysis of Sentinel-1 data
    Oja, Tonis
    Gruno, Anti
    ADVANCES IN GEODESY AND GEOINFORMATION, 2023, 72 (01)
  • [44] Study the land subsidence along JingHu highway (Beijing-Hebei) using PS-InSAR technique
    China University of Mining and Technology , 100083, Beijing, China
    不详
    不详
    Dig Int Geosci Remote Sens Symp (IGARSS), 2011, (1608-1611):
  • [45] Assessing Land Subsidence-Inducing Factors in the Shandong Province, China, by Using PS-InSAR Measurements
    Li, Fengkai
    Liu, Guolin
    Gong, Huili
    Chen, Beibei
    Zhou, Chaofan
    REMOTE SENSING, 2022, 14 (12)
  • [46] Subsidence Due to Groundwater Withdrawal in Kathmandu Basin Detected by Time-series PS-InSAR Analysis
    Krishnan, P. V. Suresh
    Kim, Duk-jin
    KOREAN JOURNAL OF REMOTE SENSING, 2018, 34 (04) : 703 - 708
  • [47] A New Method for Continuous Track Monitoring in Regions of Differential Land Subsidence Rate Using the Integration of PS-InSAR and SBAS-InSAR
    Zhang, Peng
    Qian, Xiaqing
    Guo, Shuangfeng
    Wang, Bikai
    Xia, Jin
    Zheng, Xiaohui
    REMOTE SENSING, 2023, 15 (13)
  • [48] STUDY THE LAND SUBSIDENCE ALONG JINGHU HIGHWAY (BEIJING-HEBEI) USING PS-INSAR TECHNIQUE
    Zhang Xuedong
    Ge Daqing
    Ma Weiyu
    Zhang Ling
    Wang Yan
    Guo Xiaofang
    2011 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2011, : 1608 - 1611
  • [49] Multivariate Outlier Detection in Postprocessing of Multi-temporal PS-InSAR Results using Deep Learning
    Aguiar, Pedro
    Cunha, Antonio
    Bakon, Matus
    Ruiz-Armenteros, Antonio M.
    Sousa, Joaquim J.
    INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS / INTERNATIONAL CONFERENCE ON PROJECT MANAGEMENT / INTERNATIONAL CONFERENCE ON HEALTH AND SOCIAL CARE INFORMATION SYSTEMS AND TECHNOLOGIES 2020 (CENTERIS/PROJMAN/HCIST 2020), 2021, 181 : 1146 - 1153
  • [50] Land Surface Deformation Mapping Method using PS-InSAR on ALOS/PALSAR Data in Bandung Region
    2017, Association for Computing Machinery, 2 Penn Plaza, Suite 701, New York, NY 10121-0701, United States