Alejandro Egido

GLORI: A GNSS-R Dual Polarization Airborne Instrument for Land Surface Monitoring

Global Navigation Satellite System-Reflectometry (GNSS-R) has emerged as a remote sensing tool, which is complementary to traditional monostatic radars, for the retrieval of geophysical parameters related to surface properties. In the present paper, we describe a new polarimetric GNSS-R system, referred to as the GLObal navigation satellite system Reflectometry Instrument (GLORI), dedicated to the study of land surfaces (soil moisture, vegetation water content, forest biomass) and inland water bodies. This system was installed as a permanent payload on a French ATR42 research aircraft, from which simultaneous measurements can be carried out using other instruments, when required. Following initial laboratory qualifications, two airborne campaigns involving nine flights were performed in 2014 and 2015 in the Southwest of France, over various types of land cover, including agricultural fields and forests. Some of these flights were made concurrently with in situ ground truth campaigns. Various preliminary applications for the characterisation of agricultural and forest areas are presented. Initial analysis of the data shows that the performance of the GLORI instrument is well within specifications, with a cross-polarization isolation better than −15 dB at all elevations above 45°, a relative polarimetric calibration accuracy better than 0.5 dB, and an apparent reflectivity sensitivity better than −30 dB, thus demonstrating its strong potential for the retrieval of land surface characteristics.

Airborne GNSS-R Polarimetric Measurements for Soil Moisture and Above-Ground Biomass Estimation

Soil moisture content (SMC) and above-ground biomass (AGB) are key parameters for the understanding of both the hydrological and carbon cycles. From an economical perspective, both SMC and AGB play a significant role in the agricultural sector, one of the most relevant markets worldwide. This paper assesses the sensitivity of Global Navigation Satellite System (GNSS) reflected signals to soil moisture and vegetation biomass from an experimental point of view. For that, three scientific flights were performed in order to acquire GNSS reflectometry (GNSS-R) polarimetric observations over a wide range of terrain conditions. The GNSS-R data were used to obtain the right-left and right-right reflectivity components, which were then georeferenced according to the transmitting GNSS satellite and receiver positions. It was determined that for low-altitude GNSS-R airborne platforms, the reflectivity polarization ratio provides a highly reliable observable for SMC due to its high stability with respect to surface roughness. A correlation coefficient of 0.93 and a sensitivity of 0.2 dB/SMC (%) were obtained for moderately vegetated fields with a surface roughness standard deviation below 3 cm. Similarly, the copolarized reflection coefficient shows a stable sensitivity to forest AGB with equal to 0.9 with a stable sensitivity of 1.5 dB/(100 t/ha) up to AGB values not detectable by other remote sensing systems.

Global Navigation Satellite Systems Reflectometry as a Remote Sensing Tool for Agriculture

The 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.

SAVERS: A Simulator of GNSS Reflections From Bare and Vegetated Soils

The mean power of the reflected Global Navigation Satellite System (GNSS) signals acquired by a GNSS-Reflectometry (GNSS-R) receiver can be modeled through the integral bistatic radar equation by weighting the contributions of all scatterers on the surface by the system impulse response. The geophysical properties of the scattering surface affect the magnitude of the reflected navigation signals through the bistatic scattering coefficient which, in case the observed surface is land, is a function of the soil dielectric properties, surface roughness, and vegetation cover. In this paper, the GNSS-R signal simulator developed in the framework of the Land MOnitoring with Navigation signal (LEiMON) Project, supported by European Space Agency, is presented. The simulator is able to predict the power reflected by land, taking as input the system and observation parameters, as well as the land surface parameters. The latter are used to simulate both the coherent and the incoherent scattering, taking advantage of widely used theoretical models of bistatic scattering from bare soils and vegetated surfaces. First, the geometrical formulation is discussed, and then, the problem of polarization mismatch due to real antennas at circular polarization is faced following the polarization synthesis approach. Finally, a comparison with some experimental data collected during the LEiMON campaign is presented. The simulations display the same trend of the experimental data, thus showing that the simulator can be used as an efficient tool for the interpretation of GNSS-R measurements.

Oceanpal®: Monitoring sea state with a GNSS-R coastal instrument

Oceanpalreg is a coastal instrument developed at Starlab for operational remote sensing of the ocean surface, with potential direct applications to snow/ice mapping and soil moisture monitoring. The instrument is based on the exploitation of global navigation satellite systems (GNSS) and their augmentation systems (WAAS, EGNOS). The emitted signals provide an exceptional source of opportunity for passive remote sensing of the Earth. The use of GNSS reflections (GNSS-R) for sea-surface monitoring is a bistatic radar technique only requiring a receiving system. The concept has already been implemented for coastal platforms (few meters above the water), aircraft (1km to 10 km) and is being studied for space platforms (LEO, orbiting at 500-1000 km). The potential applications include sea-state, sea-surface altimetry and surface roughness, both for scientific and operational oceanography. We report on a recent long-term experimental and demonstration campaign, carried out at the Oceanpalreg Coeli station in the Barcelona Port during the period 2004-2007, with a real time web-based service. This campaign has been made possible through collaboration with the Barcelona Port Authority Environmental Monitoring Department (APB). The instrument was installed on a breakwater near the main entrance of the port, at 23 m over the sea-surface. We describe in this paper the successful long-term comparison between the data obtained by Oceanpal instrument and the observables recorded by two nearby buoys. Data used for this analysis cover a period of over one year, allowing a definitive evaluation of the performances of this GNSS-R based coastal instrument for SWH retrieval. We also review results from a weeklong phase altimetry campaign at the port of Vilagarcia.

On the coherent and non coherent components of bare and vegetated terrain bistatic scattering: Modelling the GNSS-R signal over land

The work presented in this paper has been carried out with the aim of interpreting the data of a GNSS Reflectometer (GNSS-R) over land. The problem involves the analysis of bistatic scattering of the incoming signal collected around the specular direction. 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 will be affected, the former mainly because of the canopy attenuation and the latter for the combined effect of attenuation and volume scattering. The paper reviews the problem and 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.

Applications of GNSS-R in Continental Hydrology

Abstract: GNSS (Global Navigation Satellite System) Reflectometry (GNSS-R) is a bistatic radar remote sensing technology (transmitters and receivers are not in the same place) that uses microwave signals of opportunity from radio navigation such as the Global Positioning System (GPS). It extends and complements existing techniques for observation of the Earth by multiplying the number of transmitters (satellites in different positioning constellations) and receivers through the use of ground measurement networks, such as the permanent GNSS network in France (Reseau permanent GNSS, RGP) or the Plate Boundary Observatory (PBO) in the western United States, and allowing new measuring geometries.

Bistatic Radar Measurements of Significant Wave Height Using Signals of Opportunity in L-, S-, and Ku-Bands

This paper compares the retrieval of significant wave height (SWH) from reflected signals of opportunity in the L-band, S-band, and Ku-band. The fundamental observation is the time series of the interferometric complex field (ICF) of the reflected signal. A known relationship between the coherence time of the ICF time series (width of the ICF autocorrelation function) and SWH of the ocean is used for this retrieval. This relationship is applied to data recorded at three frequencies in the S-band, L-band, and Ku-band. The accuracy obtained for S-band and L-band were on the order of 0.4 m, but this model saturated around the SWH value of 3 m. A secondary algorithm used spectral bandwidth to estimate SWH. This model showed linear dependence, with the error also around 0.4 m. The ICF coherence time for Ku-band signals showed little sensitivity to SWH. Furthermore, the effect of fully developed sea, wind, and wave directions on SWH retrieval is analyzed.

Modeling of the GNSS-R signal as a function of soil moisture and vegetation biomass

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.

A simulator prototype of Delay-Doppler Maps for GNSS reflections from bare and vegetated soils

When considering a bistatic system made up of GNSS satellites and a receiver, the power at the receiver is modeled taking into account the matched filtering of the incoming signal with the PRN code modulation and Doppler filtering. In this paper, the simulator developed in the framework of the LEIMON Project [1] supported by ESA, will be presented. The simulator is able to predict the power reflected by land taking as input the system and observation parameters, as well as the land surface parameters. The earth surface (represented by bare and vegetated soils) leaves its signature through the bistatic scattering coefficient which has been modeled by means of well established electromagnetic theories applicable at L-band. Experimental data collected during the LEIMON campaign will be compared with simulated data.