基于无人机遥感的冬小麦氮素营养诊断

Nitrogen nutrition diagnosis of winter wheat based on the UAV remote sensing

无人机遥感具有实时、灵活、低成本等特点,在农作物长势监测及精准农业管理中应用广泛。为了实现冬小麦高产高效及氮肥的合理使用,利用无人机搭载Tetracam Mini-MCA 6多光谱相机,于2016年对山东省乐陵市的冬小麦试验田进行了遥感监测及氮素营养诊断分析,结果表明:(1)对无人机获取的遥感影像数据进行处理,经验证拼接后,影像的平均精度为99.3%;(2)植被指数对冬小麦地上部生物量(R2=0.94)和植株吸氮量(R2=0.91)均可以准确地估测,对植株氮质量分数的估测能力稍弱(R2=0.73);(3)通过氮充足指数NSI对植被指数进行归一化处理后,对氮营养指数NNI的估测能力都优于原始的植被指数(R2=0.85),使用NSI-MNDI进行氮营养诊断,氮素缺乏时NSI-MNDI小于1.006,氮素过量时,NSI-MNDI大于1.020,1.006~1.020时NSI-MNDI为适宜;(4)通过植被指数估测地上部生物量、植株氮质量分数再间接估测氮营养指数的方法精度最高,一致性检验结果为85%。

Unmanned aerial vehicles remote sensing（ UAVRS） has features of real time,flexibility and low coast. It is widely used in crop growth monitoring and precision agriculture management. In order to achieve high yield and high efficiency of winter wheat,the winter wheat in Laoling of Shandong province is monitored and its nitrogen nutrition is diagnosed by using UAV carrying Tetracam Mini-MCA 6 multi-spectral camera. The results are as follows：（ 1） the remote sensing image data acquired by unmanned aerial vehicle（ UAV） is processed and the average accuracy of the mosaic image is 99. 3%;（ 2） the vegetation indices（ VIs） can accurately estimate above-ground biomass and plant nitrogen uptake of winter wheat（ R^2= 0. 94; R^2= 0. 91）. For the plant N concentration,the estimation effect is weak with R^2= 0. 73;（ 3） by using the nitrogen sufficiency index（ NSI） to normalized the vegetation indices（ VIs）,the estimation ability of NSI-VIs for the nitrogen nutritional index（ NNI） is better than original VIs with R^2= 0. 85. by using the range of NSI-MNDI to estimate NNI is as follows ∶ NSI-MNDI 1. 006 indicates lack of nitrogen,NSI-MNDI 1. 020 indicates overdose of nitrogen,1. 006 ～ 1. 020 indicates suitable of nitrogen.（ 4） the indirectly method to estimate the N nutrition index by using the estimated ABG and PNC has the highest precision and the consistency between the estimated value and the observed value is 85%.