Wanqiu Li
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Wanqiu Li has a total of 17 co-authors. Here are the top co-authors by number of shared publications:
- Aihui Jiang
College of Geography and Environment, Shandong Normal University, Jinan 250358, China
1 shared publication - Fei Su
School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan 250101, China
1 shared publication - Guobiao Yao
School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan 250101, China
1 shared publication Guojian Zhang
Shandong Jianzhu Univ, Sch Surveying & Geoinformat, Jinan 250101, Peoples R China
1 shared publication- Guoqiang Zheng
School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan 250101, China
1 shared publication - Hongji Cao
Key Laboratory of Land Environment and Disaster Monitoring, MNR, China University of Mining and Technology, Xuzhou 221116, China
1 shared publication
Latest Publications
- 21 October 2024
- Published by Elsevier in Signal Processing
- Vol. 228
Exploiting high-precision AoA estimation method using CSI from a single WiFi station
- 21 October 2024
- Published by Elsevier in Signal Processing
- Vol. 228
Exploiting high-precision AoA estimation method using CSI from a single WiFi station
- Open Access
- 27 July 2023
- Published by MDPI AG in Applied Sciences
- Vol. 13 (15) , 8695
Monitoring Ground Displacement in Mining Areas with Time-Series Interferometric Synthetic Aperture Radar by Integrating Persistent Scatterer/Slowly Decoherent Filtering Phase/Distributed Scatterer Approaches Based on Signal-to-Noise Ratio
During the interferometric synthetic aperture radar (InSAR)-based ground displacement monitoring in mining areas, the overlying land is mainly covered by low vegetation and arable land, which makes interferograms acquired by InSAR techniques easily susceptible to decorrelation, resulting in the quantity and density of highly coherent points (CPs) are not enough to reflect the spatial location and spatio-temporal evolution process of ground displacement, which is hardly meeting requirements of high-precision ground displacement monitoring. In this study, we developed an approach for monitoring ground displacement in mining areas by integrating Persistent Scatterer (PS), Slowly Decoherent Filtering Phase (SDF), and Distributed Scatterer (DS) based on signal-to-noise ratio (SNR) to increase the spatial density of CPs. A case study based on a mining area in Heze was carried out to verify the reliability and feasibility of the proposed method in practical applications. Results showed that there were four significant displacement areas in the study area and the quantity of CPs acquired by the proposed method was maximum 6.7 times that of conventional PS-InSAR technique and maximum 2.3 times that of SBAS-InSAR technique. The density of CPs acquired by the proposed method increased significantly. The acquired ground displacement information of the study area was presented in more detail. Moreover, the monitoring results were highly consistent with ground displacement results extracted by PS-InSAR and SBAS-InSAR methods in terms of displacement trends and magnitudes.
- 27 July 2023
- Published by MDPI AG in Applied Sciences
- Vol. 13 (15) , 8695
Open AccessMonitoring Ground Displacement in Mining Areas with Time-Series Interferometric Synthetic Aperture Radar by Integrating Persistent Scatterer/Slowly Decoherent Filtering Phase/Distributed Scatterer Approaches Based on Signal-to-Noise Ratio
During the interferometric synthetic aperture radar (InSAR)-based ground displacement monitoring in mining areas, the overlying land is mainly covered by low vegetation and arable land, which makes interferograms acquired by InSAR techniques easily susceptible to decorrelation, resulting in the quantity and density of highly coherent points (CPs) are not enough to reflect the spatial location and spatio-temporal evolution process of ground displacement, which is hardly meeting requirements of high-precision ground displacement monitoring. In this study, we developed an approach for monitoring ground displacement in mining areas by integrating Persistent Scatterer (PS), Slowly Decoherent Filtering Phase (SDF), and Distributed Scatterer (DS) based on signal-to-noise ratio (SNR) to increase the spatial density of CPs. A case study based on a mining area in Heze was carried out to verify the reliability and feasibility of the proposed method in practical applications. Results showed that there were four significant displacement areas in the study area and the quantity of CPs acquired by the proposed method was maximum 6.7 times that of conventional PS-InSAR technique and maximum 2.3 times that of SBAS-InSAR technique. The density of CPs acquired by the proposed method increased significantly. The acquired ground displacement information of the study area was presented in more detail. Moreover, the monitoring results were highly consistent with ground displacement results extracted by PS-InSAR and SBAS-InSAR methods in terms of displacement trends and magnitudes.