Sentinel-2 imagery utilization for small-plot agricultural studies

Abstract

In terms of mitigation the negative aspects of agriculture on the environment, various advancements were achieved during the past few decades. Precision agriculture and related remote sensing enable canopy properties to be monitored and evaluated timely and non-destructively. Although remote sensing is nowadays widely utilized in agricultural studies with significant results, there are still certain constraints. The spatial resolution of source imagery is one of them. This study deals with this issue by evaluating Sentinel-2 imagery and it’s utilization on a small-plot experiment. Four spectral indices were derived using open-source software SNAP and compared with leaf chlorophyll content data obtained during terrestrial measurements. Correlation analysis gave ambiguous results ranging from r = 0.64 (Green Chlorophyll Index) to r = -0.47 (Triangular Chlorophyll Index). Based on this observation it was concluded that this issue requires to be investigated more thoroughly to define the relation of pixel size and size of the surface unit.