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基于无人机遥感的松材线虫病识别定位与视频会商系统开发研究
引用本文:尤程,潘洁,刘运书.基于无人机遥感的松材线虫病识别定位与视频会商系统开发研究[J].浙江林业科技,2021(1).
作者姓名:尤程  潘洁  刘运书
作者单位:南京林业大学林学院
基金项目:国家自然科学基金资助项目(31470579)。
摘    要:为实现松材线虫病Bursaphelenchusxylophilus的有效识别和定位,开发了基于Java、C++和HTML编程语言,结合OpenCV开源库、CloudRoomSDK、GeoTools工具和MySql数据库的具有松材线虫病识别定位和视频会商两个模块的系统。该系统利用OpenCV算法对感病松树Pinus sp.进行识别和标绘,利用HTTP从数据库/服务器查询到的DEM数据,结合影像空间位置和姿态信息,实现无人机平台的单木水平松材线虫病的识别定位,感病松树定位水平偏移最小值为0.09 m,最大值1.77 m,平均误差为0.64 m,均方根误差为0.492 8 m;并基于视频编解码原理和Cloudroom SDK,开发了视频会商系统,实现了无人机实时视频流的网络传输和视频会商指挥通信功能。本系统对实现松材线虫病的精准识别与实施监测提供了方法借鉴。

关 键 词:无人机遥感  松材线虫病  识别  定位  视频会商系统

System for Bursaphelenchus xylophilus Infeccted Pines Identification and Positioning and Video Meeting based on Remote Sensing
YOU Cheng,PAN Jie,LIU Yun-shu.System for Bursaphelenchus xylophilus Infeccted Pines Identification and Positioning and Video Meeting based on Remote Sensing[J].Journal of Zhejiang Forestry Science and Technology,2021(1).
Authors:YOU Cheng  PAN Jie  LIU Yun-shu
Institution:(Forestry College,Nanjing Forestry University,Nanjing 210037,China)
Abstract:Presentations were made on a system with two modules of Bursaphelencus xylophilus infected pines identification and positioning and video meeting based on Java,C++and HTML programming languages,combined with OpenCV open source library,CloudRoom SDK,GeoTools and MySql database.Test of the system was carried out in July and September in Nanjing,Jiangsu province.The result demonstrated that the system had the minimum value and maximum value of 0.09 m and 1.77 m of horizontal shift of positioning,with the average error of 0.64 m,root-mean-square error of 0.4928 m.Based on the video codec principle and Cloudroom SDK,a video meeting system was developed to realize the network transmission of real-time video stream of UAV and the function of video meeting.
Keywords:UAV remote sensing  Bursaphelencus xylophilus  identification  positioning  video meeting system
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