DocumentCode :
484313
Title :
Solar Radiance Estimation by Means of MeteoSat 2nd Generation and Neural Processing: A Vineyard Precision Farming Case
Author :
Burini, A. ; Solimini, C. ; Cossu, R. ; Fusco, L. ; Solimini, D. ; Argentini, S.
Author_Institution :
Geo-K S.r.l., Rome
Volume :
3
fYear :
2008
fDate :
7-11 July 2008
Abstract :
We propose the use of MSG images for local ground radiance estimation. To this end, first the presence of clouds must be detected, then the satellite measurements must be correlated with measurements at ground. A Cloud Detection Net (CDN) algorithm has been implemented for the first task, while time series of radiance measured at ground by the National Research Council´s Institute of Atmospheric Sciences and Climate have been compared with the MSG radiance measures. The joint use of ground and satellite radiance values led to the development of a Radiance Estimation Net (REN) algorithm yielding space-based estimates of the radiance on the field.
Keywords :
agriculture; atmospheric radiation; geophysical signal processing; remote sensing; vegetation; Cloud Detection Net algorithm; Institute of Atmospheric Sciences and Climate; MeteoSat 2nd generation; National Research Council; Radiance Estimation Net algorithm; local ground radiance estimation; neural processing; solar radiance estimation; vineyard precision farming; Atmospheric measurements; Clouds; Neural networks; Pollution measurement; Reflectivity; Satellites; Solar power generation; Solar radiation; Time measurement; Yield estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4244-2807-6
Electronic_ISBN :
978-1-4244-2808-3
Type :
conf
DOI :
10.1109/IGARSS.2008.4779410
Filename :
4779410
Link To Document :
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