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Identification of forest fire-prone region in Lamington National Park using GIS-based multicriteria technique validation using field and Sentinel-2-b3.71 MB
Published VersionCC BY-NC V4.0, Open Access
Journal article
Identification of forest fire-prone region in Lamington National Park using GIS-based multicriteria technique: validation using field and Sentinel-2-based observations
Geocarto International, Vol.40(1), pp.1-29
2025
Appears in UniSC Supported Open Access Outputs
Abstract
Lamington National Park in Queensland, Australia, is increasingly threatened by wildfires, intensified by climate change. This study integrates remote sensing, GIS, and the Analytical Hierarchy Process (AHP) to identify fire-prone areas within the park. Eight parameters were analyzed, with major fuel type being the most significant. Multispectral satellite data provided essential insights into landscape changes and vegetation stress, enhancing the understanding of wildfire risks. Historical records, field observations, and remote sensing data were utilized to develop and validate a Forest Fire Risk Index map, highlighting heightened fire susceptibility in the northern and eastern regions due to subtropical humid conditions. The findings emphasise the importance of advanced spatial analysis for proactive wildfire management. Combining remote sensing with GIS and multicriteria decision-making equips conservationists and policymakers with critical tools to strengthen wildfire response strategies, safeguard vital ecosystems, and protect surrounding communities. This approach is valuable for managing similar landscapes globally.
Details
- Title
- Identification of forest fire-prone region in Lamington National Park using GIS-based multicriteria technique: validation using field and Sentinel-2-based observations
- Authors
- Harikesh Singh (Corresponding Author) - University of the Sunshine Coast, Queensland, School of Science, Technology and EngineeringSanjeev Kumar Srivastava - University of the Sunshine Coast, Queensland, School of Science, Technology and Engineering
- Publication details
- Geocarto International, Vol.40(1), pp.1-29
- Publisher
- Taylor & Francis
- Date published
- 2025
- DOI
- 10.1080/10106049.2025.2462484
- ISSN
- 1752-0762; 1010-6049
- Copyright note
- © 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
- Data Availability
- All data of this study are provided in the results and raw data can be made available on request.
- Grant note
- We would like to thank the University of the Sunshine Coast, Queensland, Australia and SmartSat CRC for their generous support for this PhD research.
- Organisation Unit
- School of Science, Technology and Engineering; Sustainability Research Cluster
- Language
- English
- Record Identifier
- 991103735702621
- Output Type
- Journal article
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- Collaboration types
- Domestic collaboration
- Web Of Science research areas
- Environmental Sciences
- Geosciences, Multidisciplinary
- Imaging Science & Photographic Technology
- Remote Sensing
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Source: InCites