BUILDING DAMAGE ASSESSMENT AFTER EARTHQUAKE USING POST-EVENT LiDAR DATA

14 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.
2. Earthquake building damage classification based on full suite of Sentinel-1 features X. Lv et al.
3. 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.
4. DALi-CGAN: domain adaptive LiDAR-based conditional generative adversarial network for earthquake damage assessment P. Talreja & S. Durbha
5. Earthquake-induced building damage detection using the fusion of optical and radar data in intelligent systems M. Ghahrloo & M. Mokhtarzade
6. Semisupervised classification of hurricane damage from postevent aerial imagery using deep learning Y. Li et al.
7. Identifying Collapsed Buildings Using Post-Earthquake Satellite Imagery and Convolutional Neural Networks: A Case Study of the 2010 Haiti Earthquake M. Ji et al.
8. Use of active learning for earthquake damage mapping from UAV photogrammetric point clouds Z. Xu et al.
9. Remote Sensing-Based Proxies for Urban Disaster Risk Management and Resilience: A Review S. Ghaffarian et al.
10. Aligning Discriminative and Representative Features: An Unsupervised Domain Adaptation Method for Building Damage Assessment Y. Li et al.
11. Unsupervised domain adaptation with self-attention for post-disaster building damage detection Y. Li et al.
12. 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.
13. Rapid large-scale building damage level classification after earthquakes using deep learning with Lidar and satellite optical data C. Liu et al.
14. Decision-level fusion of satellite imagery and LiDAR data for post-earthquake damage map generation in Haiti F. Eslamizade et al.