| Risk assessment for tailings dams in Brumadinho of Brazil using InSAR time series approach Z Du, L Ge, AHM Ng, Q Zhu, FG Horgan, Q Zhang Science of The Total Environment 717, 137125, 2020 | 79 | 2020 |
| Graph-based few-shot learning with transformed feature propagation and optimal class allocation R Zhang, S Yang, Q Zhang, L Xu, Y He, F Zhang Neurocomputing 470, 247-256, 2022 | 72 | 2022 |
| Deep-learning-based burned area mapping using the synergy of Sentinel-1&2 data Q Zhang, L Ge, R Zhang, GI Metternicht, Z Du, J Kuang, M Xu Remote Sensing of Environment 264, 112575, 2021 | 65 | 2021 |
| Analysis of the impact of the South-to-North water diversion project on water balance and land subsidence in Beijing, China between 2007 and 2020 Z Du, L Ge, AHM Ng, X Lian, Q Zhu, FG Horgan, Q Zhang Journal of Hydrology 603, 126990, 2021 | 49 | 2021 |
| PolGAN: A deep-learning-based unsupervised forest height estimation based on the synergy of PolInSAR and LiDAR data Q Zhang, L Ge, S Hensley, GI Metternicht, C Liu, R Zhang ISPRS Journal of Photogrammetry and Remote Sensing 186, 123-139, 2022 | 41 | 2022 |
| U2D2Net: Unsupervised Unified Image Dehazing and Denoising Network for Single Hazy Image Enhancement B Ding, R Zhang, L Xu, G Liu, S Yang, Y Liu, Q Zhang IEEE Transactions on Multimedia 26, 202-217, 2023 | 32 | 2023 |
| Towards a deep-learning-based framework of Sentinel-2 imagery for automated active fire detection Q Zhang, L Ge, R Zhang, GI Metternicht, C Liu, Z Du Remote Sensing 13 (23), 4790, 2021 | 26 | 2021 |
| Long‐term subsidence in Mexico City from 2004 to 2018 revealed by five synthetic aperture radar sensors Z Du, L Ge, AHM Ng, Q Zhu, Q Zhang, J Kuang, Y Dong Land Degradation & Development 30 (15), 1785-1801, 2019 | 26 | 2019 |
| A novel attention-based deep learning method for post-disaster building damage classification C Liu, SME Sepasgozar, Q Zhang, L Ge Expert Systems with Applications 202, 117268, 2022 | 21 | 2022 |
| Local fringe frequency estimation based on multifrequency InSAR for phase-noise reduction in highly sloped terrain Z Ding, Z Wang, S Lin, T Liu, Q Zhang, T Long IEEE Geoscience and Remote Sensing Letters 14 (9), 1527-1531, 2017 | 16 | 2017 |
| A modified three-stage inversion algorithm based on R-RVoG model for Pol-InSAR data Q Zhang, T Liu, Z Ding, T Zeng, T Long Remote Sensing 8 (10), 861, 2016 | 11 | 2016 |
| Assessment of the accuracy among the common persistent scatterer and distributed scatterer based on SqueeSAR method Z Du, L Ge, AHM Ng, Q Zhang, MM Alamdari IEEE Geoscience and Remote Sensing Letters 15 (12), 1877-1881, 2018 | 9 | 2018 |
| A novel DEM reconstruction strategy based on multi-frequency InSAR in highly sloped terrain T Zeng, T Liu, Z Ding, Q Zhang, Z Wang, T Long Science China. Information Sciences 60 (8), 088301, 2017 | 6 | 2017 |
| Improved Model-Based Forest Height Inversion Using Airborne L-Band Repeat-Pass Dual-Baseline Pol-InSAR Data Q Zhang, S Hensley, R Zhang, C Liu, L Ge Remote Sensing 14 (20), 5234, 2022 | 2 | 2022 |
| Quantitative, Near Real-Time Mapping of Bushfires Through Integration of Optical and SAR Remote Sensing Techniques L Ge, Y Wang, Q Zhang, Z Du, C Liu, Y Dong, T Sleigh, T Guo, X Lei, Z Ma 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 455-458, 2021 | 2 | 2021 |
| Towards a revised framework of modified time series InSAR for mapping land deformation Z Du, L Ge, AHM Ng, Q Zhang Journal of Geodesy 94, 1-13, 2020 | 2 | 2020 |
| Channel Attention and Normal-based Local Feature Aggregation Network (CNLNet): A Deep Learning Method for Pre-disaster Large-scale Outdoor Lidar Semantic Segmentation C Liu, L Ge, W Xiang, Z Du, Q Zhang IEEE Transactions on Geoscience and Remote Sensing, 2023 | 1 | 2023 |
| Flood Assessment and Mapping Based on SAR and QUAV Vertical Remote Sensing Framework: A Case Study of 2022 Australia Moama Floods Z Sheng, L Ge, C Li, T Bai, C Liu, Y Wu, Q Zhang IGARSS 2023-2023 IEEE International Geoscience and Remote Sensing Symposium …, 2023 | 1 | 2023 |
| Detection and Deformation Characterization of the 2020 Aniangzhai Landslide Using Time-Series Insar and Optical Datasets J Kuang, L Ge, AHM Ng, Q Zhang 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 6595 …, 2021 | 1 | 2021 |
| Detection of Pre-Failure Deformation of the 2017 Maoxian Landslide with Time-Series Insar and Multi-Temporal Optical Datasets J Kuang, L Ge, AHM Ng, Z Du, Q Zhang IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium …, 2020 | 1 | 2020 |
