A review on flood management technologies related to image processing and machine learning

Article


Munawar, Hafiz Suliman, Hammad, Ahmed W. A. and Waller, S. Travis. 2021. "A review on flood management technologies related to image processing and machine learning." Automation in Construction. 132, pp. 1-18. https://doi.org/10.1016/j.autcon.2021.103916
Article Title

A review on flood management technologies related to image processing and machine learning

ERA Journal ID4159
Article CategoryArticle
AuthorsMunawar, Hafiz Suliman, Hammad, Ahmed W. A. and Waller, S. Travis
Journal TitleAutomation in Construction
Journal Citation132, pp. 1-18
Article Number103916
Number of Pages18
Year2021
PublisherElsevier
Place of PublicationNetherlands
ISSN0926-5805
1872-7891
Digital Object Identifier (DOI)https://doi.org/10.1016/j.autcon.2021.103916
Web Address (URL)https://www.sciencedirect.com/science/article/pii/S0926580521003678
Abstract

Flood management, which involves flood prediction, detection, mapping, evacuation, and relief activities, can be improved via the adoption of state-of-the-art tools and technology. Focusing on ways to mitigate floods and provide a quick response after floods is critical to ensuring fatalities are minimized, along with reducing environmental and economic damages. In the literature, techniques from different domains including remote sensing, machine learning, image processing and data analysis have been explored to manage different tasks related to flood management. This study proposes a new framework that categorizes the recent research that has been conducted on flood management systems. The framework addresses the following significant research questions: (1) What are the major techniques deployed in flood management? (2) What are the phases of flood management which existing studies tend to focus on? (3) What are the systems that are proposed to tackle problems related to flood management? (4) What are the research gaps identified in the literature when it comes to deploying technology for flood management? A classification framework for flood management has been proposed to group the various technologies reviewed. Lack of hybrid models, which combine image processing and machine learning, for flood management was observed. In addition, the application of machine learning-based methods in the post-disaster scenario was found to be limited. Thus, future efforts need to focus on combining disaster management knowledge, image processing techniques and machine learning tools to ensure effective and holistic disaster management across all phases.

KeywordsDisaster management; Flood management; Image processing; Machine learning
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Byline AffiliationsUniversity of New South Wales
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