Global Navigation Satellite Systems Reflectometry as a Remote Sensing Tool for Agriculture
AbstractThe use of Global Navigation Satellite Systems (GNSS) signals for remote sensing applications, generally referred to as GNSS-Reflectometry (GNSS-R), is gaining increasing interest among the scientific community as a remote sensing tool for land applications. This paper describes a long term experimental campaign in which an extensive dataset of GNSS-R polarimetric measurements was acquired over a crop field from a ground-based stationary platform. Ground truth ancillary data were also continuously recorded during the whole experimental campaign. The duration of the campaign allowed to cover a full crop growing season, and as a consequence of seasonal rains on the experimental area, data could be recorded over a wide variety of soil conditions. This enabled a study on the effects of different land bio-geophysical parameters on GNSS scattered signals. It is shown that significant power variations in the measured GNSS reflected signals can be detected for different soil moisture and vegetation development conditions. In this work we also propose a technique based on the combination of the reflected signal’s polarizations in order to improve the integrity of the observables with respect to nuisance parameters such as soil roughness.
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Egido, A.; Caparrini, M.; Ruffini, G.; Paloscia, S.; Santi, E.; Guerriero, L.; Pierdicca, N.; Floury, N. Global Navigation Satellite Systems Reflectometry as a Remote Sensing Tool for Agriculture. Remote Sens. 2012, 4, 2356-2372.
Egido A, Caparrini M, Ruffini G, Paloscia S, Santi E, Guerriero L, Pierdicca N, Floury N. Global Navigation Satellite Systems Reflectometry as a Remote Sensing Tool for Agriculture. Remote Sensing. 2012; 4(8):2356-2372.Chicago/Turabian Style
Egido, Alejandro; Caparrini, Marco; Ruffini, Giulio; Paloscia, Simonetta; Santi, Emanuele; Guerriero, Leila; Pierdicca, Nazzareno; Floury, Nicolas. 2012. "Global Navigation Satellite Systems Reflectometry as a Remote Sensing Tool for Agriculture." Remote Sens. 4, no. 8: 2356-2372.