By Ms Chang Liu

Journal articles

Bai T; Stütz D; Liu C; Bulatov D; Hacker J; Ge L, 2024, 'Unsupervised Bushfire Burn Severity Mapping Using Aerial and Satellite Imagery', ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences, 10, pp. 29 - 36, http://dx.doi.org/10.5194/isprs-annals-X-4-2024-29-2024

Zhang Q; Liu C; Zhu W; Mei S, 2024, 'Demystifying the Influencing Factors of Construction 4.0 Technology Implementation from a Sustainability Starting Point: Current Trends and Future Research Roadmap', Buildings, 14, http://dx.doi.org/10.3390/buildings14020552

Liu C; Ge L; Xiang W; Du Z; Zhang Q, 2024, 'Channel Attention and Normal-Based Local Feature Aggregation Network (CNLNet): A Deep Learning Method for Predisaster Large-Scale Outdoor Lidar Semantic Segmentation', IEEE Transactions on Geoscience and Remote Sensing, 62, pp. 1 - 12, http://dx.doi.org/10.1109/TGRS.2023.3339475

Liu C; Zhang Q; Ge L; Sepasgozar SME; Sheng Z, 2023, 'Dielectric Fluctuation and Random Motion over Ground Model (DF-RMoG): An Unsupervised Three-Stage Method of Forest Height Estimation Considering Dielectric Property Changes', Remote Sensing, 15, http://dx.doi.org/10.3390/rs15071877

Zhang Q; Hensley S; Zhang R; Liu C; Ge L, 2022, 'Improved Model-Based Forest Height Inversion Using Airborne L-Band Repeat-Pass Dual-Baseline Pol-InSAR Data', Remote Sensing, 14, http://dx.doi.org/10.3390/rs14205234

Liu C; Sepasgozar SME; Zhang Q; Ge L, 2022, 'A novel attention-based deep learning method for post-disaster building damage classification', Expert Systems with Applications, 202, http://dx.doi.org/10.1016/j.eswa.2022.117268

Zhang Q; Ge L; Hensley S; Isabel Metternicht G; Liu C; Zhang R, 2022, 'PolGAN: A deep-learning-based unsupervised forest height estimation based on the synergy of PolInSAR and LiDAR data', ISPRS Journal of Photogrammetry and Remote Sensing, 186, pp. 123 - 139, http://dx.doi.org/10.1016/j.isprsjprs.2022.02.008

Liu C; M.E. Sepasgozar S; Shirowzhan S; Mohammadi G, 2022, 'Applications of object detection in modular construction based on a comparative evaluation of deep learning algorithms', Construction Innovation, 22, pp. 141 - 159, http://dx.doi.org/10.1108/CI-02-2020-0017

Wu Y; Liu C; Zhang Q; Ge L, 2022, 'Bibliometric Analysis of Interferometric Synthetic Aperture Radar (InSAR) Application in Land Subsidence from 2000 to 2021', Journal of Sensors, 2022, http://dx.doi.org/10.1155/2022/1027673

Zhang Q; Ge L; Zhang R; Metternicht GI; Liu C; Du Z, 2021, 'Towards a deep-learning-based framework of sentinel-2 imagery for automated active fire detection', Remote Sensing, 13, http://dx.doi.org/10.3390/rs13234790

Liu C; Shirowzhan S; Sepasgozar S; Kaboli S, 2019, 'Evaluation of Classical Operators and Fuzzy Logic Algorithms for Edge Detection of Panels at Exterior Cladding of Buildings', Buildings, 9, pp. 40 - 40, http://dx.doi.org/10.3390/buildings9020040

Sun T; Xu Z; Yuan J; Liu C; Ren A, 2017, 'Virtual experiencing and pricing of room views based on BIM and oblique photogrammetry', CREATIVE CONSTRUCTION CONFERENCE 2017, CCC 2017, 196, pp. 1122 - 1129, http://dx.doi.org/10.1016/j.proeng.2017.08.071

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