Global Scale Monitoring of Soil and Vegetation by using AMSR-E Multi-temporal Data

In this paper, the brightness temperatures, and other microwave parameters, measured by using AMSR-E data over two yearly cycles on some test sites selected in different climatic regions of the world, have been related to surface features obtained from ground information and cartography. The areas are characterized by various meteorological conditions and vegetation covers and spread from deserts to dense forests. The analysis was carried out on the data collected with AMSR-E in 2002, 2003 and 2004. The capabilities of the satellite multi- frequency microwave radiometers in the retrieval of land surface parameters were evaluated, focusing the attention to the parameters related to the hydrological cycle, and forest areas. In general, the analysis carried out by using AMSR-E data confirmed the capability of the multi-temporal and multi- frequency analysis in a global scale monitoring of soil moisture as well as snow and vegetation covers, in the limits of the spatial resolution offered by this sensor. An algorithm based on a neural network has been implemented, tested with experimental data collected during SMEX02, and used to generate global maps of soil moisture.