27 citations as recorded by crossref.

1. Evaluation of effectiveness of three fuzzy systems and three texture extraction methods for building damage detection from post-event LiDAR data M. Janalipour & A. Mohammadzadeh https://doi.org/10.1080/17538947.2017.1387818
2. Automated extraction of lane markings from mobile LiDAR point clouds based on fuzzy inference H. Rastiveis et al. https://doi.org/10.1016/j.isprsjprs.2019.12.009
3. Optimizing Geospatial Data for ML/CV Applications: A Python-Based Approach to Streamlining Map Processing by Removing Irrelevant Areas D. Kasperek & M. Podpora https://doi.org/10.3390/app142411978
4. Identifying Collapsed Buildings Using Post-Earthquake Satellite Imagery and Convolutional Neural Networks: A Case Study of the 2010 Haiti Earthquake M. Ji et al. https://doi.org/10.3390/rs10111689
5. Decision-level fusion of satellite imagery and LiDAR data for post-earthquake damage map generation in Haiti F. Eslamizade et al. https://doi.org/10.1007/s12517-021-07293-y
6. Using high-resolution satellite imagery to provide a relief priority map after earthquake H. Ranjbar et al. https://doi.org/10.1007/s11069-017-3085-y
7. 3D building reconstruction from single street view images using deep learning H. Pang & F. Biljecki https://doi.org/10.1016/j.jag.2022.102859
8. Seismic Behavior of Steel Off-Diagonal Bracing System (ODBS) Utilized in Reinforced Concrete Frame K. Ramin https://doi.org/10.1155/2014/403916
9. Segmentation parameter selection for object-based land-cover mapping from ultra high resolution spectral and elevation data A. Hadavand et al. https://doi.org/10.1080/01431161.2017.1302107
10. Seismic urban damage map generation based on satellite images and Gabor convolutional neural networks H. Rastiveis et al. https://doi.org/10.1016/j.jag.2023.103450
11. Earthquake-induced building damage detection using the fusion of optical and radar data in intelligent systems M. Ghahrloo & M. Mokhtarzade https://doi.org/10.1007/s12145-024-01557-3
12. Building damage assessment after the earthquake in Haiti using two post-event satellite stereo imagery and DSMs J. Tian et al. https://doi.org/10.1080/19479832.2014.1001879
13. Using Support Vector Machine to Generate Building Damage Map from Post-Event LiDAR Data F. Eslamizadeh & H. Rastiveis https://doi.org/10.29252/jgit.4.3.77
14. A New Risk Assessment Model for Construction Projects by Adopting a Best–Worst Method–Fuzzy Rule-Based System Coupled with a 3D Risk Matrix H. Abed & H. Rashid https://doi.org/10.1007/s40996-023-01105-x
15. Finite Element Modeling and Nonlinear Analysis for Seismic Assessment of Off-Diagonal Steel Braced RC Frame K. Ramin & M. Fereidoonfar https://doi.org/10.1007/s40069-014-0089-9
16. Building Damage Characterization for the 2016 Amatrice Earthquake Using Ascending–Descending COSMO-SkyMed Data and Topographic Position Index S. Karimzadeh & M. Matsuoka https://doi.org/10.1109/JSTARS.2018.2825399
17. Multiresolution Change Analysis Framework for Postdisaster Assessment of Natural Gas Pipeline Risk Z. Zhou et al. https://doi.org/10.3141/2595-04
18. Segment-by-segment comparison technique for earthquake-induced building damage map generation using satellite imagery N. Khodaverdizahraee et al. https://doi.org/10.1016/j.ijdrr.2020.101505
19. Building change detection using the parallel spatial-channel attention block and edge-guided deep network A. Eftekhari et al. https://doi.org/10.1016/j.jag.2023.103180
20. UAV-based urban structural damage assessment using object-based image analysis and semantic reasoning J. Fernandez Galarreta et al. https://doi.org/10.5194/nhess-15-1087-2015
21. BDD-Net: An End-to-End Multiscale Residual CNN for Earthquake-Induced Building Damage Detection S. Seydi et al. https://doi.org/10.3390/rs14092214
22. Building Damage Detection Using Object-Based Image Analysis and ANFIS From High-Resolution Image (Case Study: BAM Earthquake, Iran) M. Janalipour & A. Mohammadzadeh https://doi.org/10.1109/JSTARS.2015.2458582
23. Earthquake damage mapping: An overall assessment of ground surveys and VHR image change detection after L'Aquila 2009 earthquake R. Anniballe et al. https://doi.org/10.1016/j.rse.2018.03.004
24. An Enhanced Rule-Based Fuzzy Segmentation Approach for Automated Urban Feature Extraction Using High-Resolution Satellite Imagery K. Yadav et al. https://doi.org/10.1109/JSTARS.2025.3601527
25. Remote Sensing-Based Proxies for Urban Disaster Risk Management and Resilience: A Review S. Ghaffarian et al. https://doi.org/10.3390/rs10111760
26. A GIS-based approach for earthquake loss estimation based on the immediate extraction of damaged buildings H. Ranjbar et al. https://doi.org/10.1080/19475705.2016.1265013
27. A proposed spatial index to prioritize damaged buildings for allocating USAR operations H. Ranjbar et al. https://doi.org/10.1080/10106049.2017.1303088