基于无人机多光谱遥感数据的植被指数玉米估产模型研究

Study on Corn Yield Estimation Model of Vegetation Index Based on UAV Multispectral Remote Sensing Data

玉米作为主要的粮食作物,其产量估产意义较为重大。传统的产量估算方法均以数据抽样调查为主,产量估算精度较低。随着新技术新方法的不断涌现,该文以无人机结合多光谱遥感技术,通过采集玉米的拔节期、吐丝期、乳熟期、蜡熟期4个关键生育期植被指数的变化,通过产量构建分析模型,并验证筛选合理的模型用于产量估算。经验证,在乳熟期,依据RVI、DVI、SAVI构建的产量模型精度较高。在蜡熟期,依据NDVI、RVI、DVI、SAVI构建的产量模型较高。通过以上研究,对于在玉米生长过程中,能够积极结合数据变化,便于高效开展农作物种植,估测作物产量具有重要的指导意义。

Corn,as the main grain crop,has significant significance in estimating its yield.The traditional yield estimation methods are mainly based on data sampling survey,and the accuracy of yield estimation is low.With the continuous emergence of new technologies and new methods,this paper uses UAV based on multi-spectral remote sensing technology to collect the changes of vegetation index in four key growth stages of corn,such as jointing stage,silking stage,milking stage and doughing stage,and construct an analysis model through yield,and verify and screen a reasonable model for yield estimation.It is proved that in the milk stage,the yield model based on RVI,DVI and SAVI has higher accuracy.In the wax ripening stage,the yield model based on NDVI,RVI,DVI and SAVI was higher.Through the above research,it has important guiding significance to actively combine the changes of data in the process of corn growth,facilitate efficient crop planting and estimate crop yield.