One study was made for estimation of sugar beet residue nitrogenby alternate satellite models
(Beeri et al., 2005). 1 nm bandwidth spectroradiometer was used to take spectral reflectance to
measure in situ leaf C and leafN. These hyperspectral data were convolved to suit Landsat 5,
SPOT 5, Quick-Bird 2, and Ikonos 2 multi-spectral satellite bands and models were created
using stepwise linear regression. Mapping of average ground biomass was 80-90% accurate by
this process. Synthetic Aperture Radar (SAR) images from satellite like ESR2 can penetrate
cloud cover. So combination of SAR images with multi-spectral images can improve spatial
crop management decision (Mondal and Tewari, 2007; Stafford, 2000). Ground penetrating
radar (GPR) with 100 MHz surface GPR antennas was used to estimate soil moisture content
(Lunt et al., 2005). Results of that study suggested that the two-way travel time to a GPR
reflection along with a geological surface could be used to predict average water content over a
large area, under natural conditions if borehole control is available and the reflection strength is
sufficient.