Abstract
An analysis on the capabilities of microwave radiometers in estimating soil moisture, snow cover and vegetation biomass was carried out on a global scale by using AMSR-E (Advanced Microwave Scanning Radiometer for EOS) data. The temporal trends of brightness temperature together with some microwave indexes, namely combinations of polarizations and frequencies, were taken into account over some test areas. In case of the estimate of soil moisture, the use of these indexes makes it possible eliminating deserts, dense vegetation and snow areas, as well as correcting for the effect of light vegetation. Afterwards, the inversion to retrieve soil moisture is performed by means of an Artificial Neural Network (ANN). Lastly, a technique based on a multi-sensor image fusion technique for enhancing the C-band spatial resolution is described here.
