无人机热红外遥感煤火探测方法

发布时间：2018-01-27 11:24

  本文关键词： 无人机 热红外 遥感 煤火探测 地表温度反演　出处：《煤矿安全》2017年12期 　论文类型：期刊论文

【摘要】：为了提高矿区煤火识别的精度,利用无人机搭载数码相机和热红外相机分别在白天和夜晚采集RGB图像和热红外图像,基于面向对象的分类方法将矿区彩色正射影像分类并赋予对应类别的发射率值;热红外影像经过辐射定标后镶嵌为正射影像,根据辐射传导方程和Plank反函数反演矿区地表温度,采用移动窗口热异常提取算法识别煤火区。试验表明,实测煤火点与无人机热红外技术探测的煤火区的重叠率为96.72%,说明无人机热红外遥感煤火探测方法的精度可靠,技术可行。
[Abstract]:In order to improve the accuracy of coal fire recognition in mining area, RGB images and thermal infrared images were collected by unmanned aerial vehicle (UAV) carrying digital camera and thermal infrared camera during the day and night respectively. Based on the object-oriented classification method, the color orthophoto image of mining area is classified and the emissivity value of the corresponding category is assigned. The thermal infrared image is embedded into orthophoto image after radiation calibration. According to the radiation conduction equation and Plank inverse function, the mining area surface temperature is retrieved, and the moving window thermal anomaly extraction algorithm is used to identify the coal fire area. The overlap rate between the measured coal fire point and the coal fire area detected by the thermal infrared technology of UAV is 96.72, which indicates that the precision of the thermal infrared remote sensing coal fire detection method of UAV is reliable and the technology is feasible.
【作者单位】： 防灾科技学院防灾工程系;中国矿业大学(北京)地球科学与测绘工程学院;北京工业职业技术学院建筑与测绘工程学院;
【基金】：中央高校基本科研业务费创新团队计划资助项目(ZY20160102) 国家自然科学基金资助项目(51474217) 北京市教委面上课题资助项目(KM201610853005)
【分类号】：TD75
【正文快照】： 煤火经常发生在地下煤层,由暴露到空气中的地下煤层与空气发生放热氧化反应而引发。煤火自燃与煤的特性、煤层属性和外部开采方式有关,其中不恰当的采煤方式创造了煤与空气间的通风路径,是引发煤火的最主要因素[1]。煤层一旦发火,将很难控制,煤火灾害严重威胁着煤炭资源、大气，

本文编号：1468355