Agriculture
From the EM scattering point of view, agricultural scatterers can be divided into two categories: bare and vegated surfaces.
Bare surfaces
Bare surfaces are characterised by a direct surface interaction. In this case only the geometric and dielectric properties of the surface affect the scattered wave. Inversion of soil-moisture (and roughness) from fully polarimetric SAR data has been demonstrated, while alternative roughness inversion methods from Pol-InSAR data has been proposed.
Vegetated surfaces
For vegetated surfaces the EM waves propagate through the vegetation layer and interact with the underlying surface. Vegetation and surface scattering are superimposed.
Quantitative agricultural Pol-InSAR applications for vegetated surfaces are rather in an early development stage. The significant differences in vegetation height and form as well as the attenuation of the EM waves through the vegetation layer make the adoption of forest concepts for agriculture applications questionable and ineffective. Agriculture vegetation monitoring is rather a high frequency Pol-InSAR application – a fact that makes airborne repeat-pass demonstration a challenge. However, first dedicated airborne campaigns and indoor measurements provided first initial data for the development of agriculture applications.
Vegetation layer height estimation: The height of agricultural vegetation is an important input parameter for the estimation of crop biomass. Furthermore, monitoring of agricultural plant height at different development stages allows direct conclusions about crop health and yield. Early results demonstrated the potential of estimating height in the case of large differential extinction values.
Extinction of the vegetation layer:
Density and water content of the vegetation layer affect the extinction of the forward propagating EM wave. The scatterers within the vegetation layer are characterized by a certain orientation introducing anisotropic propagation effects and differential extinction. The extinction coefficient and its variation with polarisation are therefore related to attributes such as the leaf area index (LAI) and the orientation effects of vegetation structure. Furthermore, the knowledge of the differential extinction is strongly related to the vegetation moisture content and this, in turn, is an essential parameter for agricultural cultivation management. First experimental results provide optimism towards a successful development.
Moisture Content of the Underlying Surface:
Its estimation is casting for farming optimization and predictive hydrological modeling. The importance combined with the absence of any alternative remote sensing methodology for even a rough estimation makes the inversion of the dielectric properties of the underlying surface a challenge. The potential of Pol-InSAR techniques is currently addressed in the frame of an ongoing ESA funded R&D study.