TOWARDS POST-DISASTER DEBRIS IDENTIFICATION FOR PRECISE DAMAGE AND RECOVERY ASSESSMENTS FROM UAV AND SATELLITE IMAGES

24 citations as recorded by crossref.

1. Application and comparison of remote sensing techniques for data-driven disaster debris quantification J. Bekkaye & N. Jafari https://doi.org/10.1080/01431161.2024.2339197
2. Post-Hurricane Debris and Community Flood Damage Assessment Using Aerial Imagery D. Aggarwal et al. https://doi.org/10.3390/rs17183171
3. Post-Disaster Recovery Monitoring with Google Earth Engine S. Ghaffarian et al. https://doi.org/10.3390/app10134574
4. Flood detection in UAV images using PSPNet and uncertainty quantification with Monte-Carlo Dropout technique S. Ahmadi & A. Mohammadzadeh https://doi.org/10.61186/jgst.13.4.41
5. The board packing problem G. Abraham et al. https://doi.org/10.1016/j.ejor.2023.01.030
6. Fast Inspection in War-affected Areas Using Airborne Remote Sensing Point Cloud J. Zoaa et al. https://doi.org/10.1051/e3sconf/202567602005
7. Satellite earth observation for recovery from hydrometeorological hazards H. Friedrich et al. https://doi.org/10.1016/j.wasec.2026.100205
8. A conceptual framework for integrated management of disasters recovery projects H. Bahmani & W. Zhang https://doi.org/10.1007/s11069-022-05328-5
9. UAV-g 2019: Unmanned Aerial Vehicles in Geomatics F. Nex https://doi.org/10.3390/drones3030074
10. A post-hurricane building debris estimation workflow enabled by uncertainty-aware AI and crowdsourcing C. Cheng et al. https://doi.org/10.1016/j.ijdrr.2024.104785
11. Challenges and limitations of earthquake-induced building damage mapping techniques using remote sensing images-A systematic review S. Matin & B. Pradhan https://doi.org/10.1080/10106049.2021.1933213
12. An innovative structural health assessment tool for existing precast concrete buildings using deep learning methods and thermal infrared satellite imagery M. Kargin et al. https://doi.org/10.1007/s13349-022-00655-4
13. Monitoring Urban Deprived Areas with Remote Sensing and Machine Learning in Case of Disaster Recovery S. Ghaffarian & S. Emtehani https://doi.org/10.3390/cli9040058
14. Evaluating Resilience-Centered Development Interventions with Remote Sensing N. Kerle et al. https://doi.org/10.3390/rs11212511
15. Detection of Tornado damage in forested regions via convolutional neural networks and uncrewed aerial system photogrammetry S. Carani & T. Pingel https://doi.org/10.1007/s11069-023-06125-4
16. Detection and Semantic Segmentation of Disaster Damage in UAV Footage Y. Pi et al. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000947
17. Multi-Hazard and Spatial Transferability of a CNN for Automated Building Damage Assessment T. Valentijn et al. https://doi.org/10.3390/rs12172839
18. Building Change Detection Based on a Gray-Level Co-Occurrence Matrix and Artificial Neural Networks M. Christaki et al. https://doi.org/10.3390/drones6120414
19. Post-Flood Analysis for Damage and Restoration Assessment Using Drone Imagery D. Whitehurst et al. https://doi.org/10.3390/rs14194952
20. Deep learning for automatic post-disaster debris identification for precise damage assessments using UAV footage G. Prakash et al. https://doi.org/10.1007/s12518-025-00616-8
21. Review article: Towards resilient vital infrastructure systems – challenges, opportunities, and future research agenda S. Mehvar et al. https://doi.org/10.5194/nhess-21-1383-2021
22. Automated Detection of Roadway Obstructions to Assess Vehicle Accessibility Using Aerial and Reference Images C. Opanasopit & J. Louis https://doi.org/10.1061/JCCEE5.CPENG-6857
23. BD-SKUNet: Selective-Kernel UNets for Building Damage Assessment in High-Resolution Satellite Images S. Ahmadi et al. https://doi.org/10.3390/rs16010182
24. Lessons learned from the Ezgeleh–Sarpol Zahab earthquake of November 2017: status of damage and disposal of disaster waste A. Saffarzadeh et al. https://doi.org/10.1007/s42768-019-00025-9