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Sensors· 2020Q1· Review

A Review on Early Forest Fire Detection Systems Using Optical Remote Sensing

Panagiotis Barmpoutis, Periklis Papaioannou, Kosmas Dimitropoulos, Nikos Grammalidis

Short summary

This review surveys optical remote sensing technologies and algorithms for early forest fire detection, categorizing systems into terrestrial, airborne, and spaceborne types.

AI-generated from the title and abstract; the full text is not read.

Key points

  • Forest fires are increasing in frequency and magnitude, necessitating effective early warning systems.
  • Optical remote sensing technologies are key for early fire detection.
  • Systems are classified into terrestrial, airborne, and spaceborne categories.
  • Various flame and smoke detection algorithms are surveyed for accuracy in challenging environments.

AI-generated from the title and abstract; the full text is not read.

Abstract

The environmental challenges the world faces nowadays have never been greater or more complex. Global areas covered by forests and urban woodlands are threatened by natural disasters that have increased dramatically during the last decades, in terms of both frequency and magnitude. Large-scale forest fires are one of the most harmful natural hazards affecting climate change and life around the world. Thus, to minimize their impacts on people and nature, the adoption of well-planned and closely coordinated effective prevention, early warning, and response approaches are necessary. This paper presents an overview of the optical remote sensing technologies used in early fire warning systems and provides an extensive survey on both flame and smoke detection algorithms employed by each technology. Three types of systems are identified, namely terrestrial, airborne, and spaceborne-based systems, while various models aiming to detect fire occurrences with high accuracy in challenging environments are studied. Finally, the strengths and weaknesses of fire detection systems based on optical remote sensing are discussed aiming to contribute to future research projects for the development of early warning fire systems.

The authors' abstract, as published at the source. Sensors, 2020 · DOI ↗

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Field: Safety, Risk, Reliability and Quality

Safety, Risk, Reliability and QualityEngineering