Understanding effects of atmospheric variables on spectral vegetation indices derived from satellite based time series of multispectral images

In agricultural practices, it is very essential to monitor crops phenological pattern over the time to manage agronomic activities such as irrigation, weed control, pest control, fertilization, drainage system etc. From the past decade, due to free availability of data and large coverage area, satellite based remote sensing has been most popular and widely used among other techniques such as physical ground surveys, ground based sensors and aerial based remote sensing. Sentinel-2 is European based satellite equipped with the state of the art multispectral imager which offers high spectral resolution (13-spectral bands), high spatial resolution (up to 10m pixel(-1)) and good temporal resolution (6 to 10days). Considering these features, time series of multispectral images of sentinel-2 has been used to establish temporal pattern of spectral vegetation indices (i.e. NDVI, SAVI, EVI, RVI) of crops to monitor the phenological behavior over time. In addition, the influence of various atmospheric variables (such as temperature in the air and precipitation) on the derived spectral vegetation indices has also been investigated in this work. Land use and coverage area frame survey (LUCAS-2015) has been used as ground reference data for this study. This study shows that by using sentinel-2, understanding relation between atmospheric conditions and crops phenological behavior can be useful to manage agricultural activities.