Defining Sheep Grazing Environments Using Remotely Sensed Data at a Range of Scales

Abstract

The grazing environment (i.e. the quantity and quality of pasture available) drives sheep production in Australia. The long-term viability of the sheep industry is dependent on the sustainable use of pasture, which requires monitoring. Remotely sensed data have the potential to monitor changes in pasture resources within and between seasons. Remotely sensed data have the potential to; map pasture resources within a paddock, differentiate paddocks within a farm, differentiate farms within a region and differentiate grazing environments across the country. This thesis examines the application of remotely sensed data in the sheep industry at three scales (within a paddock, at the paddock/farm scale and at a continental scale). Data from a hand-held active sensor (Crop Circle™) were used to estimate green dry matter (GDM) within a paddock and produce a map that highlighted the variability within the paddock. The normalised difference vegetation index (NDVI) and soil adjusted vegetation index (SAVI) were used to estimate GDM in mixed annual and perennial swards over three years at two sites. Comparisons between NDVI, SAVI, pasture height and GDM indicated that producers should continue to use pasture height to estimate GDM but the Crop Circle™ could be used to map GDM variability within a paddock.