The noise-reduction potential of Radar Vegetation Index for crop management in the Czech Republic.

Wheat and rapeseed are significant crops in Czech agriculture and remote sensing has huge potential for their management, given Sentinel-1 can overcome issues of cloudiness and monitor vegetation development via radar backscatter. This study compares radar and optical data characterizing the development of wheat and rapeseed in an agricultural cooperative in the Czech Republic. Radar Vegetation Index (RVI) and Normalized Difference Vegetation Index (NDVI) time-series of the main vegetation seasons between 2015 and 2018 are processed, analysed, and compared with each other. In 2018, the comparison of data with ground measurement by camera was also used. The temporal development of RVI is affected by noise, which is caused by the composition of imagery from different Relative orbits. The separation of imagery according to the Relative orbit used seemed to provide results more comparable to the phenological curve. Simple linear regression between NDVI and RVI illustrated that considering Relative orbit can slightly increase the Coefficient of determination. By selecting a suitable Relative orbit, the coefficient of determination between NDVI and RVI increased from 0.281 to 0.387 in the case of wheat and from 0.233 to 0.316 in the case of rape monitoring. The RVI for rapeseed and the height of canopy correlation was 0.392. The results for RVI presented in this article demonstrated that monitoring wheat and rapeseed development by Sentinel-1 has potential, however more research needs to be conducted in the areas of spatial and temporal noise removal. [ABSTRACT FROM AUTHOR]