基于地球同步轨道卫星的输电线路山火监测方法研究与应用分析

为了满足输电线路山火易发地区的低漏检、高精度、大范围、高时效性火点近实时监测需求，本文以地球同步轨道卫星影像为基础，提出了一种基于MC-CNN的山火检测算法。通过结合大津算法(OTSU)和上下文算法来增加潜在火点，从而在一定程度上降低火点检测的漏检率；引入PCA算法对输入特征进行优化，构建多通道网络结构，并利用联合概率和PSO参数寻优算法获取不同通道火点识别权重，在加权平均的基础上最终判定火点；同时，采用固定高温热源和太阳耀斑对虚假火点进行去除，以降低误报率。为了验证所提算法的有效性，本文随机选取了2019年至2022年期间输电线路附近历史卫星监测山火案例，并利用已知火点样本对火点反演结果进行验证。计算结果显示，该算法的火点检测精度达到了89.4%。

Research Methodology and Application Analysis of Wildfires Monitor for Transmission Line Based on Geostationary Orbit Satellites

To meet the needs of low residual, high precision, large range, high timeliness wildfire point near the real-time monitoring for transmission line fire prone areas, this paper put forward a fire detection algorithm based on MC - CNN.with the earth synchronous orbit satellite images.The main characteristic of this algorithm are as follows:By taking OTSU algorithm with the context of two kinds of algorithm union set to further increase the possibility of potential point, which to a certain extent, reduce the residual rate of fire detection;Get weights of different channel fire point recognition by optimizing the input features with the PCA algorithm, building a multichannel network structure and optimization algorithm based on joint probability and PSO parameters ,and determine the fire on the basis of the weighted average finally.This paper randomly selected the satellite monitoring history fire case near transmission line from 2019 to 2022,and inverse analysis the effectiveness of the proposed algorithm by using samples of known fire points,results show that the calculation for the fire detection accuracy is 89.4%.