Monitoring Alpine grassland dynamics with optical sensors on multiple spatial scales

Grasslands areas are the second largest land cover type in the Alps ranging from intensively managed meadows to semi-natural pastures for livestock covering all altitudes and exposures. Although grasslands are well studied from an ecological point of view, changing climatic conditions as well as the high biodiversity and intensive management of grasslands require a continuous monitoring of their conditions and health. Recently, advances in the availability and detection frequency of observations from optical sensors have been accomplished through new sensors (e.g. Copernicus Sentinels), alternative platforms (e.g. UAV) or further adapted technology (e.g. repeated digital imagery or station networks ) which can be used to link optical responses to real biophysical processes. We are examining the growth dynamics of four different grasslands in South Tyrol, Italy during the period of 2017. On these managed Meadow sites we produced the NDVI index from four different sensors: Sentinel-2 MSI, Netcams (Phenocams), Spectral Reflectance Sensors (SRS) and a spectroradiometer. We analysed how measurements on different S2-pixels are correlated by sensor on the respective scale and what the strengths and weaknesses of each sensor are. First results show clear differences between the NDVIs acquired from the diverse scales. Although applying intense filtering, the linear correlation among the sensors spans relatively wide (R2 0.46-0.92). The NDVI saturation level of the diverse sensors is reached at different periods as well as at different maxima. These factors have potential impacts on the calibration of each sensors and the combined use of the same optical index from different sensors on analysing vegetation dynamics (e.g. stress, drought), anthropogenic interaction (e.g. irrigation, harvesting) and for the prediction of biophysical parameters (e.g. LAI)