Results 101 to 110 of about 21,327 (190)

SBAS-InSAR Based Deformation Monitoring of Tailings Dam: The Case Study of the Dexing Copper Mine No.4 Tailings Dam. [PDF]

Sensors (Basel), 2023
Xie W, Wu J, Gao H, Chen J, He Y.
europepmc   +1 more source

Scale-Sensitive and Confounding-Audited SBAS-InSAR Evidence Representation for Landslide Susceptibility Mapping

Regional landslide susceptibility mapping commonly relies on static conditioning factors, including terrain, geology, hydrology, land cover and human activity.
Xiaohui Luo, Dong Sun, Xiao Hu, Jianbo Wu, Tao Yang   +4 more
core   +1 more source

Investigación en subsidencia minera con datos de Sentinel-1A por tecnología SBAS-InSAR: estudio de caso de Ningdong Coalfield, China

, 2020
Ground deformation characterization was difficult to obtain over large spatial areas before the invention of the Satellite radar interferometry (InSAR) technique.
Ma, Fei, Sui, Lichun
core   +1 more source

Analysis of land subsidence caused by hydrodynamic force in Loess Hilly and gully region based on SBAS-InSAR. [PDF]

PLoS One, 2023
Liu X, Ma C, Ling H, Yan W, Zhang H, Jiang X.   +5 more
europepmc   +1 more source

SBAS-InSAR based validated landslide susceptibility mapping along the Karakoram Highway: a case study of Gilgit-Baltistan, Pakistan. [PDF]

Sci Rep, 2023
Kulsoom I, Hua W, Hussain S, Chen Q, Khan G, Shihao D.   +5 more
europepmc   +1 more source

Joint PS–SBAS Time-Series InSAR for Sustainable Urban Infrastructure Management: Tunnel Subsidence Mechanisms in Sanya, China

Monitoring construction-phase settlement of estuary-crossing tunnels founded on coastal soft soils is critical for risk management, yet dense in situ measurements are often unavailable along linear corridors.
Jun Hu, Bing Liu, Yamin Zhao, Zihan Song, Kai Wei, Qiong Liu   +5 more
core   +1 more source

Dynamic Earth Observation for Landslide Susceptibility Mapping Using Machine Learning and InSAR-Derived Deformation

Applied Sciences
Landslide susceptibility assessment is essential for hazard mitigation and sustainable urban planning, yet many existing approaches rely primarily on static environmental predictors and often neglect active slope deformation.
Anna-Hajnalka Kerekes, Călin Baciu, Szilárd-Lehel Poszet   +2 more
doaj   +1 more source

Combined SBAS-InSAR and PSO-RF Algorithm for Evaluating the Susceptibility Prediction of Landslide in Complex Mountainous Area: A Case Study of Ludian County, China. [PDF]

Sensors (Basel), 2022
Xiao B, Zhao J, Li D, Zhao Z, Zhou D, Xi W, Li Y.   +6 more
europepmc   +1 more source

Identifying Potential Landslides in Low-Coherence Areas Using SBAS-InSAR: A Case Study of Ninghai County, China

The southeastern coastal regions of China are characterized by typical hilly terrain with abundant rainfall throughout the year, leading to frequent geological hazards.
Chunji Zhuang, Jianfeng Gu, Shijie Ge, Bingqiang Zhang, Jin Xu, Xixuan Bai   +5 more
core   +1 more source

Change detection of slow-moving landslide with multi-source SBAS-InSAR and Light-U2Net

Interferometric Synthetic Aperture Radar (InSAR) techniques are commonly used approach for identifying Slow-moving Landslide (SML). However, most SML boundary identification with deep learning are based on single-source InSAR data, which cannot fully ...
Lu Xu, Ningjie Liu, Dongping Ming, Feng Liu, Jianao Cai, Xiao Ling, Mengyuan Zhu, Liang Zhang, Yan Li   +8 more
core   +1 more source