Pre- and Post-Disaster Remote Sensing with Drones for Supporting Disaster Management
Date
2023-04-27
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Abstract
Small (< 25 kg) aerial drones have expanded the remote sensing toolkit for disaster management activities, resulting in hundreds of published case studies in the past two decades. The overall goal of this doctoral research, which comprises three related studies, is to evaluate drone-based pre- and post-disaster remote sensing as a tool to support disaster management. The first study provides a critical review of drone-based remote sensing in natural hazard-related disasters to highlight research trends, biases, and expose new opportunities. Recommendations for future research include a greater focus on demonstrating and evaluating drone-based support of pre-disaster data acquisition (a preparedness activity) and rapid damage assessment (a response activity). As such, the second study presents the first pre-disaster drone-based mapping mission over an urban area (downtown Victoria, British Columbia) approved by Transport Canada. The objective was to assess the quality of 3D data obtained with the only legally approved drone. Finally, the third study demonstrates rapid mapping of hurricane roof damage using artificial intelligence (deep learning) and drone imagery, including an accuracy assessment. Overall, this doctoral research identified critical knowledge gaps in the field of pre- and post-disaster remote sensing with small aerial drones, and then demonstrated and evaluated drone-based support of two building-damage-related activities that were recommended for future research.
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disaster, hazard, emergency, damage, drone, UAV, RPAS, literature review, remote sensing, mapping, photogrammetry, structure from motion, artificial intelligence, deep learning, convolutional neural network
Citation
Kucharczyk, M. (2023). Pre- and post-disaster remote sensing with drones for supporting disaster management (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.