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Robust assessment of an operational algorithm for the retrieval of soil moisture from AMSR-E data in central Italy

Conference Paper
Publication Date:
2015
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.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
AMSR-E; Artificial Neural Networks; Soil Moisture Content; soil water balance model
List of contributors:
Ciabatta, Luca; Brocca, Luca
Authors of the University:
BROCCA LUCA
CIABATTA LUCA
Handle:
https://iris.cnr.it/handle/20.500.14243/316701
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http://www.scopus.com/record/display.url?eid=2-s2.0-84962508317&origin=inward
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