Pasture Monitoring Using SAR with COSMO-SkyMed, ENVISAT ASAR, and ALOS PALSAR in Otway, Australia

Because of all-weather working ability, sensitivity to biomass and moisture, and high spatial resolution, Synthetic aperture radar (SAR) satellite images can perfectly complement optical images for pasture monitoring. This paper aims to examine the potential of the integration of COnstellation of small Satellites for the Mediterranean basin Observasion (COSMO-SkyMed), Environmental Satellite Advanced Synthetic Aperture Radar (ENVISAT ASAR), and Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR) radar signals at horizontally emitted and received polarization (HH) for pasture monitoring at the paddock scale in order to guide farmers for better management. The pasture site is selected, in Otway, Victoria, Australia. The biomass, water content of grass, and soil moisture over this site were analyzed with these three bands of SAR images, through linear relationship between SAR backscattering coefficient, and vegetation indices Normalized Differential Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Enhanced Vegetation Index (EVI)), together with soil moisture index (MI). NDVI, NDWI, and MI are considered as proxy of pasture biomass, plant water content, and soil moisture, respectively, and computed from optical images and climate data. SAR backscattering coefficient and vegetation indices are computed within a grass zone, defined by classification with MODIS data. The grass condition and grazing activities for specific paddocks are detectable, based on SAR backscatter, with all three wavelengths datasets. Both temporal and spatial analysis results show that the X-band SAR has the highest correlation to the vegetation indices. However, its accuracy can be affected by wet weather due to its sensitivity to the water on leaves. The C-band HH backscattering coefficient showed moderate reliability to evaluate biomass and water content of grass, with limited influence from rainfall in the dry season. The L-band SAR is the less accurate one for grass biomass measurement due to stronger penetration.

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