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Wildfires are increasing globally due to climate change. Wildfires can spread rapidly in a short period of time, early detection is important. A CCTV and thermal imaging camera are used for early detection and prevention of wildfires and improved using camera analysis method and AI technology. However, the wildfire detection distance is still shortened depending on weather conditions and air quality, and image processing performance deteriorates due to low light at night. A satellite remote sensing technology is difficult to monitor wild fires in real time and affected by cloud mask, low spatial and temporal resolution. A Drone is also limited in flight time by communication, weather conditions, battery capacity, and payload. In the case of lidar-based long-distanced wildfire monitoring, advanced remote sensing monitoring that can monitor wildfires is possible by classifying the type of aerosol particles and the amount of light backscattered by smoke particles. Our recently developed wildfire scanning lidar technology uses light sources of two wavelengths (532 nm and 1064 nm) and developed a system capable of 360 observation within 30 minutes with an angular resolution of less than 1 in the horizontal direction. In addition, it is the wildfire scanning lidar capable of detectiong a wildfire in the atmosphere using the backscattering coefficient and aerosol optical properties calculated at two wavelengths. A depolarization of smoke aerosol in the air can be used to improve the accuracy of wildfire smoke detection using characterization of particles. Presently wildfire monitoring lidar technology under development is producing commercial products that protect eyesight and monitor forest fire smoke within a radius of 10 km through long-wavelength laser and object analysis. Acknowledgement: This research was supported by a grant (2023-MOIS-20024324) of Ministry-Cooperation RD Program of Disaster-Safety funded by Ministry of Interior and Safety (MOIS, Korea).
Kim et al. (Sat,) studied this question.