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

Abstract

Abstract: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 OPEN ACCESSRemote Sens. 2013, 5 3612 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.

Temporal Polarimetric Behavior of Oilseed Rape (Brassica napus L.) at C-Band for Early Season Sowing Date Monitoring

“…The increase of the backscattering signal can be due to the increase of soil moisture (from 41.7% to 56.3%, Table 3) and water standing on the plant canopy after rainfall. The rain effect on backscattering of plant canopies had also been observed in previous studies [18,39,40].…”

Detection of major climatic and environmental predictors of liver fluke exposure risk in Ireland using spatial cluster analysis

“…NVDI and EVI are monitoring indexes of vegetation, with the latter having improved sensitivity and monitoring capability than NDVI due to background adjustment and reduction in atmospheric influences (Matsushita et al, 2007). Both EVI and NDVI are regarded as proxy for the grass biomass of pastures and, therefore, could be used as an indicator of grass condition and grazing activities for specific paddocks of farms (Wang et al, 2013).…”

Improving the Estimation of Above Ground Biomass Using Dual Polarimetric PALSAR and ETM+ Data in the Hyrcanian Mountain Forest (Iran)

“…L-band SAR can penetrate more through vegetation; thus, the soil backscattering is involved in the total backscattering [21,97]. However, in low biomass densities, soil moisture has more effect on SAR backscattering, since radar signal can penetrate through the trees and hit the surface [15,21].…”