Multi-temporal Monitoring of Wheat Growth through Correlation Analysis of Satellite Images, Unmanned Aerial Vehicle Images with Ground Variable

Satellite remote sensing has been proved to be an effective way of monitoring crop growth status and yield prediction. Recently near-ground remote sensing using unmanned aerial vehicle (UAV) witnessed wide applications in obtaining field information. In this research, four satellite and eight UAV images were used from early June to the end of July, 2015, which covers two experimental wheat fields, in order to monitor wheat canopy growth status and analyze the correlation among satellite images based normalized difference vegetation index (NDVI) with UAV images based visible-band difference vegetation index (VDVI) and ground variable of grain protein contents. The results of relational analysis of NDVI with sampled wheat grain protein content showed that the NDVI related most to the grain protein content at the later stage of wheat growing season, one week prior to harvesting. And the correlation analysis of NDVI with VDVI showed good consistency at the early stage of wheat growing season, with the coefficient of determination R2=0.77, in regardless of the wheat varieties.