基于无人机平台的稻纵卷叶螟为害程度遥感监测

Monitoring of rice damage by rice leaf roller using UAV-based remote sensing

虫害是造成粮食减产的重要原因之一,传统人工巡查法调查虫害的方法效率较低,难以实现大范围农田虫害监测,因此,快速、客观的虫害监测手段是规模化种植农业的必要需求。以稻纵卷叶螟虫害为研究对象,使用基于无人机平台的遥感技术获取不同虫害程度水稻的多光谱影像,结合地面卷叶率调查,分析不同虫害程度水稻的冠层光谱特征,建立稻纵卷叶螟危害下水稻卷叶率的遥感估算模型,用于虫害严重程度的快速诊断。结果表明:遭受稻纵卷叶螟为害的水稻卷叶率与冠层在绿(560 nm)、红边(717 nm)和近红外(840 nm)波段的光谱反射率显著负相关,与红(668 nm)波段光谱反射率显著正相关,与归一化植被指数(NDVI)和差值植被指数(DVI)显著负相关。以光谱反射率和植被指数为自变量、使用偏最小二乘回归(PLSR)算法建立的卷叶率估算模型精度最高,验证R2为0.675,RMSE为0.753。通过使用PLSR模型得到的卷叶率分布图与实际调查结果基本一致。研究结果可以为稻纵卷叶螟虫害快速调查提供理论依据和技术支持,也可以为虫害精准防控提供决策依据。

The infestation by insects is one of the major reasons for the reduction of grain yields.Traditional investigation of insect infestation by manpower is inefficiency and can not cover large fields.Therefore,a fast and objective method to monitor insect infestation is necessary for large scale farming.This study took the rice leaf roller as the research object.The multispectral images of rice field were acquired by a UAV-based remote sensing system and the rate of roll leaf was investigated.Then the spectral features of rice in different infestation levels were analyzed.Based on the sensitive bands and vegetation indices(VI),the estimation models of the rate of roll leaf were established to evaluate the infestation levels.The results showed that the rate of roll leaf had significant negative correlation with the spectral reflectance at green(560 nm),red-edge(717 nm)and NIR(840 nm)bands and positive correlation with the spectral reflectance at red(668 nm)band.The rate of roll leaf was also negatively correlated with Normalized Difference Vegetation Index(NDVI)and Difference Vegetation Index(DVI).The estimation models of the rate of roll leaf established by partial least squares regression(PLSR)achieved the best accuracy.The validation R2 was 0.675 and the RMSE was 0.753.The distribution map of the rate of roll leaf based on the PLSR model was consistent with the field survey.The results could provide theoretical basis and technical support for the rapid investigation and precise control of insect infestation.