作 者：
黄焕华;马晓航;黄华毅;周宇飞;张伟;黄咏槐
关键词：
固定翼无人机;监测;松材线虫病;枯死松树
摘 要：
无人机航摄监测森林病虫害是一个新的研究热点。为探究无人机航摄在松材线虫病监测中的应用,本研究于2017年11月利用小型固定翼无人机采集了广东省河源市新丰江库区松材线虫病疫点的航摄影像,总面积1425.9 hm~2。固定翼无人机搭载了1台可见光数码相机和1台多光谱数码相机,能同时采集枯死松树的可见光和近红外的航摄影像。利用LAMapper软件对航摄图像进行空中三角测量和像素匹配,获得可见光正射影像和多光谱正射影像。使用ERDAS软件生成影像的归一化植被指数(NDVI)。然后将带有地理信息的完整影像自动导入GIS系统进行异常点识别和几何矫正,导出最终的影像数据。最后,对影像进行分析,并根据植被指数(NDVI)对图像进行分类。分析结果显示,航摄的疫点中共自动识别1486株枯死松树,并获得了其分布地图及坐标点位置。验证结果表明监测的准确率达到80%以上,坐标点精度达到2-3 m。本研究结果具有低成本、自动化、可靠、客观、高效和及时等优点,可为大面积监测松材线虫病的发生现状和流行动态、评估防控效果和灾害损失提供技术支撑。
译 名：
A preliminary study on monitoring of dead pine trees caused by pine wilt disease with fixed-wing unmanned aerial vehicle
作 者：
HUANG Huan-Hua;MA Xiao-Hang;HUANG Hua-Yi;ZHOU Yu-Fei;ZHANG Wei;HUANG Yong-Huai;Guangdong Provincial Key Laboratory of Silviculture, Protection and Utilization/Guangdong Academy of Forestry;Shouxin(Beijing) Technology Co.Ltd.;
关键词：
Fixed-wing unmanned aerial vehicle(UAV);;monitor;;pine wilt disease(PWD);;dead pine tree
摘 要：
Using unmanned aerial vehicle(UAV) monitor forest pests and diseases is a new research hotspot. To explore the application of UAV monitor pine wilt disease(PWD),we used a small fixedwing UAV acquisition platform to obtain aerial images of disease areas of PWD in November 2017 in this study. The disease areas are located in Xinfeng river reservoir,Heyuan,Guangdong Province. The total aerial area was 1425. 9 hm~2. The fixed-wing UAV equipped with a visible digital camera and a multispectral digital camera which have been calibrated and modified to record not only the visual but also the near infrared reflection(NIR) of possibly infected pine trees. The aerial images processed by the LAMapper software, including aerial triangulation and pixel matching, to obtain visible light orthophotograph image and multispectral orthophotograph image. Normalized difference vegetation index(NDVI) of images were generated by use ERDAS software. Then,the orthophotograph images withgeographic information automatically imported into GIS system for anomaly spot identification and geometric correction,and the processed image data was exported. Finally,the images were analysed and classified vigour maps were produced based on NDVI. Analysis results showed that 1486 dead pine trees were automatically identified,and the distribution maps and location coordinates of dead pine trees were obtained. The verification results showed that the accuracy of monitoring could be reached more than 80%,and the coordinate points accuracy for 2-3 m. The results of our study provided low-cost,automatic,reliable,objective,efficient and timely technical support for the research and control of PWD,including the large-scale monitoring of the occurrence status and epidemic dynamics,evaluation control effects and disaster losses.
