本文關(guān)鍵詞： 無人機 熱紅外 遙感 煤火探測 地表溫度反演　出處：《煤礦安全》2017年12期 　論文類型：期刊論文

【摘要】：為了提高礦區(qū)煤火識別的精度,利用無人機搭載數(shù)碼相機和熱紅外相機分別在白天和夜晚采集RGB圖像和熱紅外圖像,基于面向?qū)ο蟮姆诸惙椒▽⒌V區(qū)彩色正射影像分類并賦予對應(yīng)類別的發(fā)射率值;熱紅外影像經(jīng)過輻射定標(biāo)后鑲嵌為正射影像,根據(jù)輻射傳導(dǎo)方程和Plank反函數(shù)反演礦區(qū)地表溫度,采用移動窗口熱異常提取算法識別煤火區(qū)。試驗表明,實測煤火點與無人機熱紅外技術(shù)探測的煤火區(qū)的重疊率為96.72%,說明無人機熱紅外遙感煤火探測方法的精度可靠,技術(shù)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.
【作者單位】： 防災(zāi)科技學(xué)院防災(zāi)工程系;中國礦業(yè)大學(xué)(北京)地球科學(xué)與測繪工程學(xué)院;北京工業(yè)職業(yè)技術(shù)學(xué)院建筑與測繪工程學(xué)院;
【基金】：中央高�；究蒲袠I(yè)務(wù)費創(chuàng)新團隊計劃資助項目(ZY20160102) 國家自然科學(xué)基金資助項目(51474217) 北京市教委面上課題資助項目(KM201610853005)
【分類號】：TD75
【正文快照】： 煤火經(jīng)常發(fā)生在地下煤層,由暴露到空氣中的地下煤層與空氣發(fā)生放熱氧化反應(yīng)而引發(fā)。煤火自燃與煤的特性、煤層屬性和外部開采方式有關(guān),其中不恰當(dāng)?shù)牟擅悍绞絼?chuàng)造了煤與空氣間的通風(fēng)路徑,是引發(fā)煤火的最主要因素[1]。煤層一旦發(fā)火,將很難控制,煤火災(zāi)害嚴重威脅著煤炭資源、大氣，

本文編號：1468355