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| Titel |
Microwave radiometric measurements of soil moisture in Italy |
| VerfasserIn |
G. Macelloni, S. Paloscia, P. Pampaloni, E. Santi, M. Tedesco |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 7, no. 6 ; Nr. 7, no. 6, S.937-948 |
| Datensatznummer |
250004865
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| Publikation (Nr.) |
 copernicus.org/hess-7-937-2003.pdf |
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| Zusammenfassung |
| Within the framework of the MAP and RAPHAEL projects, airborne experimental
campaigns were carried out by the IFAC group in 1999 and 2000, using a multifrequency
microwave radiometer at L, C and X bands (1.4, 6.8 and 10 GHz). The aim of the experiments
was to collect soil moisture and vegetation biomass information on agricultural areas to
give reliable inputs to the hydrological models. It is well known that microwave emission
from soil, mainly at L-band (1.4 GHz), is very well correlated to its moisture content.
Two experimental areas in Italy were selected for this project: one was the Toce Valley,
Domodossola, in 1999, and the other, the agricultural area of Cerbaia, close to Florence,
where flights were performed in 2000. Measurements were carried out on bare soils, corn
and wheat fields in different growth stages and on meadows. Ground data of soil moisture
(SMC) were collected by other research teams involved in the experiments. From the
analysis of the data sets, it has been confirmed that L-band is well related to the SMC
of a rather deep soil layer, whereas C-band is sensitive to the surface SMC and is more
affected by the presence of surface roughness and vegetation, especially at high incidence
angles. An algorithm for the retrieval of soil moisture, based on the sensitivity to
moisture of the brightness temperature at C-band, has been tested using the collected data
set. The results of the algorithm, which is able to correct for the effect of vegetation
by means of the polarisation index at X-band, have been compared with soil moisture data
measured on the ground. Finally, the sensitivity of emission at different frequencies to
the soil moisture profile was investigated. Experimental data sets were interpreted by
using the Integral Equation Model (IEM) and the outputs of the model were used to train
an artificial neural network to reproduce the soil moisture content at different
depths.
Keywords: microwave radiometry, soil moisture mapping, river basins, vegetative biomass,
neural networks |
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