A review on early wildfire detection from unmanned aerial vehicles using deep learning-based computer vision algorithms

Wildfire is one of the most critical natural disasters that threaten wildlands and forest resources. Tra-ditional firefighting systems, which are based on ground crew inspection, have several limits and can expose firefighters' lives to danger. Thus, remote sensing technologies have become one of the most de-manded strategies to fight against wildfires, especially UAV-based remote sensing technologies. They have been adopted to detect forest fires at their early stages, before becoming uncontrollable. Autonomous wildfire early detection from UAV-based visual data using different deep learning algorithms has attracted significant interest in the last few years. To this end, in this paper, we focused on wildfires detection at their early stages in forest and wildland areas, using deep learning-based computer vision algorithms to prevent and then reduce disastrous losses in terms of human lives and forest resources (c) 2021 Elsevier B.V. All rights reserved.

Automated summary

The study focused on early detection of wildfires in forest and wildland areas using deep learning-based computer vision algorithms to prevent and reduce disastrous losses in terms of human lives and forest resources.