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

Xin Wang,Linlin Ge,Xiaojing Li

doi:10.3390/rs5073611

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 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.

Highlights

Pastures represent one type of managed landscape units in the terrestrial system
When we focused on growing season, ASAR HH backscattering with an incidence angle of 33° maintained the moderate sensitivity for temporal variation of biomass (R2 = 0.48, p = 0.05), while with incidence angles of 17° and 21° it did not show any capability for biomass or soil moisture
As pasture is one dominant land type used in Australia, how to better manage it is of great importance for profitability and sustainability

Summary

Introduction

Pastures represent one type of managed landscape units in the terrestrial system. Pastures are essential contributors to the productivity and biodiversity of the biosphere, supporting domesticated livestock as a key component of ecosystem. Improved utilization of pastures can be achieved by implementation of intensive rotational grazing mechanisms. Rotational grazing involves controlled movement of herds, from paddock to paddock, according to the amount of available biomass or feed in both the current and the destination paddock. A paddock is a small field of grassland, normally fenced and separated by farmers for keeping sheep or cattle. In these intensive grazing systems, pasture biomass must be regularly estimated at the paddock scale for better grazing rotation. Paddocks with higher biomass may be used to lengthen the grazing interval while paddocks with lower biomass should be allowed more time to grow to the desired mass. The process is time consuming, requires field work skill, and is limited to single transect [1]

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