基于无人机多光谱影像的病害棉田产量损失估算  

Estimation of yield loss in diseased cotton fields using UAV multi-spectral images

作　　者：宋勇 陈兵[1] 王琼[1] 王静[3] 赵静[1] 孙乐鑫 陈子杰 韩焕勇[1] 王方永[1] 傅积海 Song Yong;Chen Bing;Wang Qiong;Wang Jing;Zhao Jing;Sun Lexin;Chen Zijie;Han Huanyong;Wang Fangyong;Fu Jihai(Xinjiang Academy of Agricultural and Reclamation Science,Shihezi,832000,China;Agricultural College,Shihezi University,Shihezi,832003,China;Water Conservancy Construction Engineering,Xinjiang Shihezi Vocational Technical College,Shihezi,832003,China)

机构地区：[1]新疆农垦科学院棉花研究所,石河子832000 [2]石河子大学农学院,石河子832003 [3]新疆石河子职业技术学院水利建筑工程分院,石河子832003

出　　处：《农业工程学报》2022年第6期175-183,共9页Transactions of the Chinese Society of Agricultural Engineering

基　　金：国家自然科学基金项目(41961054,41971321);兵团领军人才计划(2019CB018);新疆兵团英才项目联合资助;。

摘　　要：该研究利用无人机多光谱遥感影像对棉花黄萎病造成的产量损失进行估算,为棉花黄萎病预防和防治提供依据。对病害棉田进行调查,获取无人机多光谱影像及地面产量损失数据,利用相关系数法及灰度值标准差法分别筛选识别病害棉株的最佳植被指数、最佳波段组合;基于筛选的结果建立棉田综合影像(最佳波段组合与差值植被指数综合影像),利用支持向量机径向基核函数分类法对病害棉田原始影像和综合影像进行产量空间分布分析及产量损失估算。结果表明,无人机多光谱影像识别病害棉田的最佳植被指数、最佳波段组合分别是差值植被指数(相关系数为-0.86)、波段B_(3)(550~10 nm)、B_(5)(656~10 nm)、B_(8)(800~10 nm)的波段组合(B_(3)-B_(5)-B_(8))(最佳指数因子为153.44);综合影像较原始影像更能准确识别病害棉田产量空间分布情况(总体精度为96.64%,Kappa系数为95.61%),不同病害严重度(健康b_(0)、轻度b_(1)、中度b_(2)、重度b_(3)、极严重b_(4))对应棉田面积比例分别为7.81%、23.78%、29.20%、13.92%、17.43%;综合影像对病害棉田产量损失量估算效果最好,不同病害严重度(b_(0)、b_(1)、b_(2)、b_(3)、b_(4))对应棉田产量损失率分别为0、22.80%、31.32%、49.02%、76.33%,预估籽棉损失量达4260.01 kg,损失率为49.16%,皮棉损失量达2267.18 kg,损失率为54.51%。与病害胁迫棉田产量损失估算值相比,实际棉田籽棉损失率高6.28%,皮棉损失率高4.48%。病害胁迫棉田产量估算值与实际棉田收获值差异不显著,能够准确实现病害棉田产量损失估算。研究结果可为无人机遥感监测作物病害造成的产量损失提供理论依据和参考。Verticillium wilt has been one of the most common high-risk diseases of cotton in recent years.A huge threat can be posed to the stable production of cotton fields in Xinjiang,one of the most important commodity cotton production bases in China.However,the annual area of verticillium wilt disease in cotton fields is ever increasing and resulting in serious yield losses,due to the long-term influence of planting modes,geographical,and climate characteristics.Most traditional measurements for the yield loss present time-consuming,labor-intensive,large errors,one-sidedness.It is a high demand to accurately estimate the yield loss caused by the diseases.Fortunately,the Unmanned Aerial Vehicle(UAV)multi-spectral data can be combined with the ground survey data for the comprehensive characteristics of high accuracy.In this study,a systematic investigation was conducted to estimate the yield loss in the diseased cotton fields using the UVA multi-spectral images.An experiment was carried out in the cotton verticillium wilt disease nursery(44°31′N,85°98′E)of Xinjiang Academy of Agricultural Sciences,Shihezi Reclamation District,Xinjiang in China in 2020.The gray desert soil was collected in the study area,with an organic matter content of 21.30 g/kg,a soil layer pH of 7.82,and electrical conductivity(EC)of 0.48 mS/cm.Taking the test variety as Xinluzao 8,the specific procedure was set:the on-demand sowing was adopted on the film,the drip irrigation under the film,(66+10)cm wide and narrow row design,while the cotton plants were manually capped on July 5,and sprayed by drones on September 6 and September 13 Defoliant,and finally harvested by the cotton picker on October 13th.The ground monitoring points were arranged in a grid format(66 in total)from the beginning of the disease,in order to collect the disease severity data.The output was then measured in the later period.The monitoring point was taken as the center during the production measurement(cotton harvest period),and the area of the monitoring point was expa

关 键 词：棉花 无人机 病害 多光谱影像 产量损失 估算 

分 类 号：S562[农业科学—作物学] TP79[自动化与计算机技术—检测技术与自动化装置]