Articles | Volume 15, issue 6
https://doi.org/10.5194/nhess-15-1087-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/nhess-15-1087-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
UAV-based urban structural damage assessment using object-based image analysis and semantic reasoning
J. Fernandez Galarreta
CORRESPONDING AUTHOR
Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, the Netherlands
N. Kerle
Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, the Netherlands
M. Gerke
Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, the Netherlands
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- Automated regional seismic damage assessment of buildings using an unmanned aerial vehicle and a convolutional neural network C. Xiong et al. 10.1016/j.autcon.2019.102994
- An Evaluation of UAV Path Following and Collision Avoidance Using NFMGOA Control Algorithm R. Thusoo et al. 10.1007/s11277-021-08947-6
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- Large-Scale Synthetic Urban Dataset for Aerial Scene Understanding Q. Gao et al. 10.1109/ACCESS.2020.2976686
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- Automatic Detection of Earthquake-Damaged Buildings by Integrating UAV Oblique Photography and Infrared Thermal Imaging R. Zhang et al. 10.3390/rs12162621
- Remote sensing‐based mapping of structural building damage in the Ahr valley G. Samprogna Mohor et al. 10.1111/jfr3.12983
- Review of Automatic Feature Extraction from High-Resolution Optical Sensor Data for UAV-Based Cadastral Mapping S. Crommelinck et al. 10.3390/rs8080689
- Automatic extraction of urban land information from unmanned aerial vehicle (UAV) data A. Shukla & K. Jain 10.1007/s12145-020-00498-x
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- A BIM-Based Method for Structural Stability Assessment and Emergency Repairs of Large-Panel Buildings Damaged by Military Actions and Explosions: Evidence from Ukraine P. Hryhorovskyi et al. 10.3390/buildings12111817
- A Drone-Based Structure from Motion Survey, Topographic Data, and Terrestrial Laser Scanning Acquisitions for the Floodgate Gaps Deformation Monitoring of the Modulo Sperimentale Elettromeccanico System (Venice, Italy) M. Fabris & M. Monego 10.3390/drones8100598
- Remote Sensing of Wildland Fire-Induced Risk Assessment at the Community Level M. Ahmed et al. 10.3390/s18051570
- Big Data in Natural Disaster Management: A Review M. Yu et al. 10.3390/geosciences8050165
- A Review on UAV-Based Remote Sensing Technologies for Construction and Civil Applications S. Guan et al. 10.3390/drones6050117
- Rapid urban flood damage assessment using high resolution remote sensing data and an object-based approach S. Jiménez-Jiménez et al. 10.1080/19475705.2020.1760360
- Photogrammetry in Documentation and Ambient Vibration Test of Historical Masonry Minarets K. Hacıefendioğlu & E. Maraş 10.1007/s40799-016-0137-2
- Vector Field UAV Guidance for Path Following and Obstacle Avoidance with Minimal Deviation J. Wilhelm & G. Clem 10.2514/1.G004053
- How can Big Data and machine learning benefit environment and water management: a survey of methods, applications, and future directions A. Sun & B. Scanlon 10.1088/1748-9326/ab1b7d
- Unmanned Aerial Vehicles for Search and Rescue: A Survey M. Lyu et al. 10.3390/rs15133266
- SAM-VQA: Supervised Attention-Based Visual Question Answering Model for Post-Disaster Damage Assessment on Remote Sensing Imagery A. Sarkar et al. 10.1109/TGRS.2023.3276293
- Identification of Structurally Damaged Areas in Airborne Oblique Images Using a Visual-Bag-of-Words Approach A. Vetrivel et al. 10.3390/rs8030231
- Territoires « cyclonés ». Les aléas cycloniques et leurs impacts F. Vinet & F. Leone 10.4000/echogeo.18621
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