Detection of Soil Moisture Variations Using GPS and GLONASS SNR Data for Elevation Angles Ranging From 2° to 70°

We propose a Global Navigation Satellite System-Reflectometry (GNSS-R) interference pattern technique method to estimate the temporal variations of the soil moisture content of the ground surrounding a single geodetic antenna. Three parameters can be inverted from GNSS signal-to-noise ratio (SNR) acquisitions: amplitude/phase of the multipath contribution to SNR and effective antenna height. Our method is applied to determine the surface moisture of a bare soil at Lamasquère, France, from February 5 to March 15, 2014. First, only data from low satellite elevation angles (<; 30°) are taken into consideration and are compared with independent 2-cm depth soil moisture records. The combination of the measurements from all GPS satellites, tested for the first time, improves the quality of the results with a correlation coefficient reaching 0.95, with a 10-min sampling rate. Our study shows that it is also possible to take high satellite elevation angles into account, even if the sign of the correlation appears to be reversed w.r.t. data from low satellite elevation angles. The cutoff angle where the sign of the correlation reverses seems to be around 30°. With regard to the effective antenna height, only a very low correlation is observed for high satellite elevation angles. We propose a new inversion method taking the pseudo-dynamic of the surface into account, which increases the correlation from 0.39 to 0.82. By normalizing and inverting the time series obtained from either low or high satellite elevation angles, it is possible to combine them, which enhances the results (correlation = 0.95).

[1]  Arnaud Mialon,et al.  MCM'10: An experiment for satellite multi-sensors crop monitoring from high to low resolution observations , 2012, 2012 IEEE International Geoscience and Remote Sensing Symposium.

[2]  Valery U. Zavorotny,et al.  A Physical Model for GPS Multipath Caused by Land Reflections: Toward Bare Soil Moisture Retrievals , 2010, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[3]  E. Small,et al.  Use of GPS receivers as a soil moisture network for water cycle studies , 2008 .

[4]  P. Axelrad,et al.  Initial results of land-reflected GPS bistatic radar measurements in SMEX02 , 2004 .

[5]  S. Seneviratne,et al.  Investigating soil moisture-climate interactions in a changing climate: A review , 2010 .

[6]  Budiman Minasny,et al.  Microwave dielectric behavior of wet soils , 2006 .

[7]  Raul Onrubia Ibáñez,et al.  Improving the Accuracy of Soil Moisture Retrievals Using the Phase Difference of the Dual-Polarization GNSS-R Interference Patterns , 2014, IEEE Geoscience and Remote Sensing Letters.

[8]  P. Y. Georgiadou,et al.  On carrier signal multipath effects in relative GPS positioning , 1988 .

[9]  Felix Perosanz,et al.  Simulations of direct and reflected waves trajectories for in situ GNSS-R experiments , 2014 .

[10]  Bruce M. Hannah.  Modelling and simulation of GPS multipath propagation , 2001 .

[11]  Delphis F. Levia,et al.  Soil moisture: A central and unifying theme in physical geography , 2011 .

[12]  R. Biancale,et al.  Simulations of direct and reflected wave trajectories for ground-based GNSS-R experiments , 2014 .

[13]  Thomas Ruf,et al.  The Lomb-Scargle Periodogram in Biological Rhythm Research: Analysis of Incomplete and Unequally Spaced Time-Series , 1999 .

[14]  Pierre Borderies,et al.  Radar altimetry backscattering signatures at Ka, Ku, C, and S bands over West Africa , 2015 .

[15]  Frédéric Frappart,et al.  Estimating surface soil moisture over sahel using envisat radar altimetry , 2012, 2012 IEEE International Geoscience and Remote Sensing Symposium.

[16]  M. Martín-Neira.  A pasive reflectometry and interferometry system (PARIS) application to ocean altimetry , 1993 .

[17]  Frédéric Frappart,et al.  Sea level monitoring and sea state estimate using a single geodetic receiver , 2015 .

[18]  P. Axelrad,et al.  Using GPS multipath to measure soil moisture fluctuations: initial results , 2008 .

[19]  A. Bilich.  Improving the precision and accuracy of geodetic GPS: Applications to multipath and seismology , 2006 .

[20]  J. Scargle.  Studies in astronomical time series analysis. II - Statistical aspects of spectral analysis of unevenly spaced data , 1982 .

[21]  Richard K. Moore,et al.  Radar remote sensing and surface scattering and emission theory , 1986 .

[22]  N. Lomb.  Least-squares frequency analysis of unequally spaced data , 1976 .

[23]  Erik Andreas Lydersen.  Scattering of Electromagnetic Waves from Randomly Rough Surfaces with Skewed Height Distributions , 2014 .

[24]  J. Klobuchar,et al.  Multipath effects on the determination of absolute ionospheric time delay from GPS signals , 1985 .

[25]  Aslak Grinsted,et al.  Nonlinear Processes in Geophysics Application of the Cross Wavelet Transform and Wavelet Coherence to Geophysical Time Series , 2022 .

[26]  Valery U. Zavorotny,et al.  Effects of Near-Surface Soil Moisture on GPS SNR Data: Development of a Retrieval Algorithm for Soil Moisture , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[27]  Y. Kerr,et al.  The SMOS Mission: New Tool for Monitoring Key Elements of the Global Water Cycle This satellite mission will use new algorithms to try to forecast weather and estimate climate change from satellite measurements of the Earth's surface. , 2010 .

[28]  Valery U. Zavorotny,et al.  GPS Multipath and Its Relation to Near-Surface Soil Moisture Content , 2010, IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens..

[29]  F. Ulaby,et al.  Microwave Dielectric Behavior of Wet Soil-Part 1: Empirical Models and Experimental Observations , 1985, IEEE Transactions on Geoscience and Remote Sensing.

[30]  David Brewster,et al.  On the laws of the polarization of light by refraction , 2022 .

[31]  Johan Löfgren,et al.  Local Sea Level Observations Using Reflected GNSS Signals , 2014 .

[32]  Frédéric Baup,et al.  Mapping surface soil moisture over the Gourma mesoscale site (Mali) by using ENVISAT ASAR data , 2010 .

[33]  W. Wagner,et al.  A Method for Estimating Soil Moisture from ERS Scatterometer and Soil Data , 1999 .