BUILDING DAMAGE ASSESSMENT AFTER EARTHQUAKE USING POST-EVENT LiDAR DATA

12 citations as recorded by crossref.

1. Data Collection Using Terrestrial Laser Scanners from the Shake-Table Test of a Full-Scale Reinforced Concrete Building P. Calvi et al. 10.1061/JSENDH.STENG-12627
2. A Comparative Study of Texture and Convolutional Neural Network Features for Detecting Collapsed Buildings After Earthquakes Using Pre- and Post-Event Satellite Imagery M. Ji et al. 10.3390/rs11101202
3. Earthquake-induced building damage detection using the fusion of optical and radar data in intelligent systems M. Ghahrloo & M. Mokhtarzade 10.1007/s12145-024-01557-3
4. Semisupervised classification of hurricane damage from postevent aerial imagery using deep learning Y. Li et al. 10.1117/1.JRS.12.045008
5. Identifying Collapsed Buildings Using Post-Earthquake Satellite Imagery and Convolutional Neural Networks: A Case Study of the 2010 Haiti Earthquake M. Ji et al. 10.3390/rs10111689
6. Use of active learning for earthquake damage mapping from UAV photogrammetric point clouds Z. Xu et al. 10.1080/01431161.2018.1466083
7. Remote Sensing-Based Proxies for Urban Disaster Risk Management and Resilience: A Review S. Ghaffarian et al. 10.3390/rs10111760
8. Aligning Discriminative and Representative Features: An Unsupervised Domain Adaptation Method for Building Damage Assessment Y. Li et al. 10.1109/TIP.2020.2988175
9. Unsupervised domain adaptation with self-attention for post-disaster building damage detection Y. Li et al. 10.1016/j.neucom.2020.07.005
10. SAR and LIDAR Datasets for Building Damage Evaluation Based on Support Vector Machine and Random Forest Algorithms—A Case Study of Kumamoto Earthquake, Japan M. Hajeb et al. 10.3390/app10248932
11. Rapid large-scale building damage level classification after earthquakes using deep learning with Lidar and satellite optical data C. Liu et al. 10.1080/17538947.2024.2441934
12. Decision-level fusion of satellite imagery and LiDAR data for post-earthquake damage map generation in Haiti F. Eslamizade et al. 10.1007/s12517-021-07293-y