Partition dynamic threshold monitoring technology of wildfires near overhead transmission lines by satellite

Jiazheng Lu, Yu Liu (), Guoyong Zhang, Bo Li, Lifu He and Jing Luo
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Jiazheng Lu: State Key Laboratory of Disaster Prevention and Reduction for Power Grid Transmission and Distribution Equipment
Yu Liu: State Key Laboratory of Disaster Prevention and Reduction for Power Grid Transmission and Distribution Equipment
Guoyong Zhang: State Key Laboratory of Disaster Prevention and Reduction for Power Grid Transmission and Distribution Equipment
Bo Li: State Key Laboratory of Disaster Prevention and Reduction for Power Grid Transmission and Distribution Equipment
Lifu He: State Key Laboratory of Disaster Prevention and Reduction for Power Grid Transmission and Distribution Equipment
Jing Luo: State Key Laboratory of Disaster Prevention and Reduction for Power Grid Transmission and Distribution Equipment

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2018, vol. 94, issue 3, No 19, 1327-1340

Abstract: Abstract Wildfires are a major natural disaster that can threaten the safe and stable operation of overhead transmission lines. Compared with large-area forest fires, transmission-line wildfires usually cover a small area and spread rapidly, making monitoring accuracy and real-time requirements of high priority. Wildfire monitoring based on satellite remote sensing has advantages in terms of monitoring-range width and the capacity for real-time monitoring; however, the detection threshold changes dynamically due to the influences of climate, geography, weather, and other factors that affect monitoring accuracy. To focus on small-area wildfires near overhead transmission lines, we developed a partition dynamic threshold calculation method based on time-series prediction. Basic thresholds are obtained based on a large number of historical values, followed by partitioning one of these values according to digital elevation model data and subsequent correction. Compared with conventional constant-threshold monitoring methods, our proposed method significantly reduced missed and false detection rates. Additionally, to improve fire-spot localization to the overhead transmission-line towers, we developed a tower-location algorithm based on block searching. Compared with the traditional traversal algorithm, our algorithm enabled a 15,000-fold increase in operation speed. These improvements will significantly enhance the monitoring of transmission-line wildfires, which are highly reliant upon alarm speed.

Keywords: Wildfire; Satellite monitoring; Partition dynamic threshold; Time-series prediction; Tower location; Block searching (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s11069-018-3479-5

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