Title :
Multifrequency microwave vegetation indexes for estimating vegetation biomass
Author :
E. Santi;S. Paloscia;P. Pampaloni
Author_Institution :
IFAC-CNR, Florence (Italy)
fDate :
7/1/2015 12:00:00 AM
Abstract :
The polarization capabilities in estimating vegetation biomass on both global and local scales by using passive and active microwave satellite data (AMSR-E/2, ENVISAT and COSMO-SkyMed) were investigated. Two algorithms that are based on Artificial Neural Networks (ANN) and are able to ingest data from different frequency channels have been implemented. The algorithm validation, carried out on the available experimental data, confirmed that the two polarizations and related indices can be legitimately used to produce vegetation maps on a global and local scale by separating at least 3-4 levels of biomass, without any need of further information from other sensors.
Keywords :
"Vegetation mapping","Biomass","Indexes","Artificial neural networks","Microwave radiometry","Satellites","Remote sensing"
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International
Electronic_ISBN :
2153-7003
DOI :
10.1109/IGARSS.2015.7327002