无人机影像识别白喉乌头的相对高程阈值法适用性分析  

Applicability analysis of relative elevation threshold method in recognizing diphtheria aconitum in UAV images

作　　者：范媛 范宏 吴建国 林峻 陈吉军 巴日斯 郑江华[1,3] FAN Yuan;FAN Hong;WU Jianguo;LIN Jun;CHEN Jijun;Baris;ZHENG Jianghua(College of Resources and Environmental Sciences,Xinjiang University,Urumqi 830046,China;Xinjiang Disease Control and Rodent Control Headquarters Office,Urumqi 830001,China;Key Laboratory of Oasis Ecology,Xinjiang University,Urumqi 830046,China)

机构地区：[1]新疆大学资源与环境科学学院,新疆乌鲁木齐830046 [2]新疆治蝗灭鼠指挥部办公室,新疆乌鲁木齐830001 [3]新疆大学绿洲生态教育部重点实验室,新疆乌鲁木齐830046

出　　处：《测绘通报》2022年第2期131-135,共5页Bulletin of Surveying and Mapping

基　　金：基于低空遥感数据的典型草原毒害草高精度识别方法研究(XJEDU2019I010);新疆草原生物灾害遥感监测(070216328)。

摘　　要：本文以新疆伊犁州新源县那拉提草原的典型毒害草白喉乌头为研究对象,通过PhotoScan软件对无人机航拍影像进行数据处理并获取研究区DSM数据,在此基础上,运用相对高程阈值法识别提取白喉乌头的最佳阈值范围,并验证其有效性。试验结果表明:(1)在无人机影像中,相对高程阈值法能够清晰准确地体现地物分布特征,适用于提取与普通牧草高度误差明显的地物;(2)当10 cm≤T<20 cm时,白喉乌头能够被准确识别,且与实际白喉乌头分布点基本一致,分类精度达91%;(3)相对高程阈值法能够较好地分离出白喉乌头,既提升了分类依据的可靠性,又实现了白喉乌头高精度识别。该方法可应用于实际的草原监测工作。Taking the typical poisonous grass diphtheria aconitum in the Nalati grassland of Xinyuan county, Ili Kazak Autonomous Prefecture, Xinjiang as the research object, the PhotoScan software is used to process the drone aerial images and obtain the DSM data of the study area. On this basis, the relative elevation threshold is used. The method extracts the optimal threshold range for identifying diphtheria aconitum and verifies its effectiveness. The results show that:(1) In UAV images, the relative elevation threshold method can clearly and accurately reflect the distribution characteristics of ground features, and is suitable for extracting ground features with obvious height errors from ordinary grass;(2) When 10 cm≤T<20 cm, diphtheria aconitum can be accurately identified, and is basically consistent with the actual distribution of diphtheria aconitum, with a classification accuracy of 92%;(3) The relative elevation threshold method can better separate diphtheria aconitum, which improves the reliability of the classification basis. It also realizes the high-precision identification of diphtheria aconitum. This method can be applied to actual grassland monitoring.

关 键 词：相对高程阈值法 无人机 毒害草 图像识别 

分 类 号：P237[天文地球—摄影测量与遥感]