DocumentCode
3070750
Title
Modeling of the GNSS-R signal as a function of soil moisture and vegetation biomass
Author
Guerriero, Leila ; Pierdicca, N. ; Egido, Alejandro ; Caparrini, Marco ; Paloscia, S. ; Santi, Enrico ; Floury, Nicola
Author_Institution
Tor Vergata Univ., Rome, Italy
fYear
2013
fDate
21-26 July 2013
Firstpage
4050
Lastpage
4053
Abstract
Very recently, it has been observed that GNSS-R can provide a significant contribution to agricultural and forestry applications, since the use of GNSS signals as sources of opportunity enables bistatic radar measurements at L-band, which showed to be sensitive to soil moisture and vegetation parameters. This perspective has been investigated in two experimental activities funded by the European Space Agency: the LEiMON and GRASS campaigns. This work has been carried out with the aim of interpreting the data collected during the two campaigns over land. This requires to model the coherent component associated to the mean surface, but at the same time the diffuse incoherent component due to roughness at wavelength scale. In presence of vegetation, both components must be taken into account. The paper presents the approach followed to develop a simulator of GNSS-R data over land, aiming to support potential applications of GNSS-R for soil moisture and biomass retrieval.
Keywords
geophysical signal processing; remote sensing by radar; satellite navigation; soil; vegetation; European Space Agency; GNSS-R signal; GRASS campaign; LEiMON campaign; agricultural applications; bistatic radar measurement; forestry applications; soil moisture; vegetation biomass; Biological system modeling; Biomass; Receivers; Scattering; Sensitivity; Soil; Vegetation mapping; GNSS-R; biomass; bistatic scattering model; soil moisture;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International
Conference_Location
Melbourne, VIC
ISSN
2153-6996
Print_ISBN
978-1-4799-1114-1
Type
conf
DOI
10.1109/IGARSS.2013.6723722
Filename
6723722
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