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林业研究(英文版) >

2024 , Vol. 35 >Issue 1: 86

DOI: https://doi.org/10.1007/s11676-024-01737-3

  • Li Meng 1, a ,
  • Jim O’Hehir 1 ,
  • Jing Gao 1 ,
  • Stefan Peters 1 ,
  • Anthony Hay 2
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收稿日期: 2023-10-09

  录用日期: 2024-01-18

  网络出版日期: 2024-10-16

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A theoretical framework for improved fire suppression by linking management models with smart early fire detection and suppression technologies

  • Li Meng 1, a ,
  • Jim O’Hehir 1 ,
  • Jing Gao 1 ,
  • Stefan Peters 1 ,
  • Anthony Hay 2
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  • 1 University of South Australia, Adelaide, SA, Australia
  • 2 Esk Spatial, Invermay, TAS, Australia
a

Received date: 2023-10-09

  Accepted date: 2024-01-18

  Online published: 2024-10-16

Supported by

University of South Australia

Copyright

© The Author(s) 2024
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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本文引用格式

Li Meng , Jim O’Hehir , Jing Gao , Stefan Peters , Anthony Hay . [J]. 林业研究(英文版), 2024 , 35(1) : 86 . DOI: 10.1007/s11676-024-01737-3

Abstract

Bushfires are devastating to forest managers, owners, residents, and the natural environment. Recent technological advances indicate a potential for faster response times in terms of detecting and suppressing fires. However, to date, all these technologies have been applied in isolation. This paper introduces the latest fire detection and suppression technologies from ground to space. An operations research method was used to assemble these technologies into a theoretical framework for fire detection and suppression. The framework harnesses the advantages of satellite-based, drone, sensor, and human reporting technologies as well as image processing and artificial intelligence machine learning. The study concludes that, if a system is designed to maximise the use of available technologies and carefully adopts them through complementary arrangements, a fire detection and resource suppression system can achieve the ultimate aim: to reduce the risk of fire hazards and the damage they may cause.

Key words： Forest fire; Resource suppression; Smart fire detection and suppression system; Forest fire management; Holistic system

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