Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Hydrol. Earth Syst. Sci., 21, 4767-4784, 2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
26 Sep 2017
Use of reflected GNSS SNR data to retrieve either soil moisture or vegetation height from a wheat crop
Sibo Zhang1,2, Nicolas Roussel3, Karen Boniface2,3,4,a, Minh Cuong Ha3, Frédéric Frappart3,5, José Darrozes3, Frédéric Baup4, and Jean-Christophe Calvet1 1CNRM – UMR3589 (Météo-France, CNRS), Toulouse, France
2Fondation STAE, Toulouse, France
3GET – UMR5563, CNRS/Université Paul Sabatier, UR254 IRD, Toulouse, France
4CESBIO, Université de Toulouse, CNES/CNRS/IRD/UPS, Toulouse, France
5LEGOS – UMR566 (CNES, CNRS, IRD, UPS), Toulouse, France
anow at: Joint Research Centre/European Commission, Ispra, Italy
Abstract. This work aims to estimate soil moisture and vegetation height from Global Navigation Satellite System (GNSS) Signal to Noise Ratio (SNR) data using direct and reflected signals by the land surface surrounding a ground-based antenna. Observations are collected from a rainfed wheat field in southwestern France. Surface soil moisture is retrieved based on SNR phases estimated by the Least Square Estimation method, assuming the relative antenna height is constant. It is found that vegetation growth breaks up the constant relative antenna height assumption. A vegetation-height retrieval algorithm is proposed using the SNR-dominant period (the peak period in the average power spectrum derived from a wavelet analysis of SNR). Soil moisture and vegetation height are retrieved at different time periods (before and after vegetation's significant growth in March). The retrievals are compared with two independent reference data sets: in situ observations of soil moisture and vegetation height, and numerical simulations of soil moisture, vegetation height and above-ground dry biomass from the ISBA (interactions between soil, biosphere and atmosphere) land surface model. Results show that changes in soil moisture mainly affect the multipath phase of the SNR data (assuming the relative antenna height is constant) with little change in the dominant period of the SNR data, whereas changes in vegetation height are more likely to modulate the SNR-dominant period. Surface volumetric soil moisture can be estimated (R2  =  0.74, RMSE  =  0.009 m3 m−3) when the wheat is smaller than one wavelength (∼ 19 cm). The quality of the estimates markedly decreases when the vegetation height increases. This is because the reflected GNSS signal is less affected by the soil. When vegetation replaces soil as the dominant reflecting surface, a wavelet analysis provides an accurate estimation of the wheat crop height (R2  =  0.98, RMSE  =  6.2 cm). The latter correlates with modeled above-ground dry biomass of the wheat from stem elongation to ripening. It is found that the vegetation height retrievals are sensitive to changes in plant height of at least one wavelength. A simple smoothing of the retrieved plant height allows an excellent matching to in situ observations, and to modeled above-ground dry biomass.

Citation: Zhang, S., Roussel, N., Boniface, K., Ha, M. C., Frappart, F., Darrozes, J., Baup, F., and Calvet, J.-C.: Use of reflected GNSS SNR data to retrieve either soil moisture or vegetation height from a wheat crop, Hydrol. Earth Syst. Sci., 21, 4767-4784,, 2017.
Publications Copernicus
Short summary
GNSS SNR data were obtained from an intensively cultivated wheat field in southwestern France. The data were used to retrieve soil moisture and vegetation characteristics during the growing period of wheat. Vegetation growth broke up the constant height assumption used in soil moisture retrieval algorithms. Soil moisture could not be retrieved after wheat tillering. A new algorithm based on a wavelet analysis was implemented and used to retrieve vegetation height.
GNSS SNR data were obtained from an intensively cultivated wheat field in southwestern France....