DocumentCode :
3690188
Title :
Robust assessment of an operational algorithm for the retrieval of soil moisture from AMSR-E data in central Italy
Author :
E. Santi;S. Paloscia;S. Pettinato;L. Brocca;L. Ciabatta
Author_Institution :
Institute of Applied Physics - National Research Council, Florence, Italy
fYear :
2015
fDate :
7/1/2015 12:00:00 AM
Firstpage :
1288
Lastpage :
1291
Abstract :
In this work, the surface soil moisture (SMC) derived from the AMSR-E acquisitions by using Artificial Neural Networks (ANN) is compared with simulated data obtained from the application of a soil water balance model in central Italy. All the overpasses available for the 9-years lifetime of AMSR-E have been considered for the comparison, which was carried out point by point over a grid of 91 nodes spaced at 0.1×0.1°, roughly corresponding to the Umbria region. The main purpose of this study is to exploit the potential of AMSR-E sensors for hydrological studies, and in particular, for SMC monitoring at regional scale in heterogeneous environments.
Keywords :
"Artificial neural networks","Soil moisture","Orbits","Data models","Radiometers","Training"
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International
ISSN :
2153-6996
Electronic_ISBN :
2153-7003
Type :
conf
DOI :
10.1109/IGARSS.2015.7326010
Filename :
7326010
Link To Document :
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