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

机译:卫星在架空传输线附近野火的分区动态阈值监测技术

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摘要

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.
机译:野火是一种主要的自然灾害,可能会威胁到架空传输线的安全和稳定运行。与大面积森林火灾相比,传输线野火通常覆盖一个小面积并迅速蔓延,使监控精度和实时要求高优先级。基于卫星遥感的野火监测在监测范围宽度和实时监测的能力方面具有优势;然而,由于影响监测准确性的气候,地理,天气和其他因素的影响,检测阈值动态变化。专注于靠近顶端传输线的小面积野火,我们开发了一种基于时间序列预测的分区动态阈值计算方法。基于大量历史值获得基本阈值,然后根据数字高程模型数据和随后的校正来划分这些值之一。与传统的恒定阈值监测方法相比,我们提出的方法显着降低了错过和假检测率。另外,为了改善射灯定位到顶置传输线塔,我们开发了一种基于块搜索的塔式定位算法。与传统的遍历算法相比,我们的算法使操作速度增加了15,000倍。这些改进将显着提高传输线野火的监测,这在报警速度时高度依赖。

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