A Framework for Burnt Area Mapping and Evacuation Problem Using Aerial Imagery Analysis

Article


Munawar, Hafiz Suliman, Gharineiat, Zahra, Akram, Junaid and Khan, Sara Imran. 2022. "A Framework for Burnt Area Mapping and Evacuation Problem Using Aerial Imagery Analysis." Fire. 5 (4), pp. 1-15. https://doi.org/10.3390/fire5040122
Article Title

A Framework for Burnt Area Mapping and Evacuation Problem Using Aerial Imagery Analysis

ERA Journal ID212512
Article CategoryArticle
AuthorsMunawar, Hafiz Suliman (Author), Gharineiat, Zahra (Author), Akram, Junaid (Author) and Khan, Sara Imran (Author)
Journal TitleFire
Journal Citation5 (4), pp. 1-15
Article Number122
Number of Pages15
Year2022
PublisherMDPI AG
Place of PublicationSwitzerland
ISSN2571-6255
Digital Object Identifier (DOI)https://doi.org/10.3390/fire5040122
Web Address (URL)https://www.mdpi.com/2571-6255/5/4/122
Abstract

The study aims to develop a holistic framework for maximum area coverage of a disaster region during a bushfire event. The monitoring and detection of bushfires are essential to assess the extent of damage, its direction of spread, and action to be taken for its containment. Bushfires limit human’s access to gather data to understand the ground situation. Therefore, the application of Unmanned Aerial Vehicles (UAVs) could be a suitable and technically advanced approach to grasp the dynamics of fires and take measures to mitigate them. The study proposes an optimization model for a maximal area coverage of the fire-affected region. The advanced Artificial Bee Colony (ABC) algorithm will be applied to the swarm of drones to capture images and gather data vital for enhancing disaster response. The captured images will facilitate the development of burnt area maps, locating access points to the region, estimating damages, and preventing the further spread of fire. The proposed algorithm showed optimum responses for exploration, exploitation, and estimation of the maximum height of the drones for the coverage of wildfires and it outperformed the benchmarking algorithm. The results showed that area coverage of the affected region was directly proportional to drone height. At a maximum drone height of 121 m, the area coverage was improved by 30%. These results further led to a proposed framework for bushfire relief and rescue missions. The framework is grounded on the ABC algorithm and requires the coordination of the State Emergency Services (SES) for quick and efficient disaster response.

Keywordsbushfires; burnt area; damage detection; UAVs; ABC algorithm; evacuation
ANZSRC Field of Research 2020350703. Disaster and emergency management
401304. Photogrammetry and remote sensing
461199. Machine learning not elsewhere classified
Byline AffiliationsSchool of Surveying and Built Environment
University of Sydney
University of New South Wales
Institution of OriginUniversity of Southern Queensland
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