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Open AccessArticle

Potential Applications of GNSS-R Observations over Agricultural Areas: Results from the GLORI Airborne Campaign

1
CESBIO (CNRS/UPS/IRD/CNES), 18 av. Edouard Belin, bpi 2801, 31401 Toulouse CEDEX 9, France
2
TETIS, IRSTEA, University of Montpellier, 34093 Montpellier, France
3
ISPA, INRA, 33140 Villenave d’Ornon, France
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(8), 1245; https://doi.org/10.3390/rs10081245
Received: 6 July 2018 / Revised: 1 August 2018 / Accepted: 3 August 2018 / Published: 8 August 2018
(This article belongs to the Special Issue Environmental Research with Global Navigation Satellite System (GNSS))
The aim of this study is to analyze the sensitivity of airborne Global Navigation Satellite System Reflectometry (GNSS-R) on soil surface and vegetation cover characteristics in agricultural areas. Airborne polarimetric GNSS-R data were acquired in the context of the GLORI’2015 campaign over two study sites in Southwest France in June and July of 2015. Ground measurements of soil surface parameters (moisture content) and vegetation characteristics (leaf area index (LAI), and vegetation height) were recorded for different types of crops (corn, sunflower, wheat, soybean, vegetable) simultaneously with the airborne GNSS-R measurements. Three GNSS-R observables (apparent reflectivity, the reflected signal-to-noise-ratio (SNR), and the polarimetric ratio (PR)) were found to be well correlated with soil moisture and a major vegetation characteristic (LAI). A tau-omega model was used to explain the dependence of the GNSS-R reflectivity on both the soil moisture and vegetation parameters. View Full-Text
Keywords: GNSS-R; GLORI; airborne; agriculture; soil moisture; crops; LAI GNSS-R; GLORI; airborne; agriculture; soil moisture; crops; LAI
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MDPI and ACS Style

Zribi, M.; Motte, E.; Baghdadi, N.; Baup, F.; Dayau, S.; Fanise, P.; Guyon, D.; Huc, M.; Wigneron, J.P. Potential Applications of GNSS-R Observations over Agricultural Areas: Results from the GLORI Airborne Campaign. Remote Sens. 2018, 10, 1245.

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