Jean-Pierre Wigneron

Soil moisture retrieval from space: the Soil Moisture and Ocean Salinity (SMOS) mission

Microwave radiometry at low frequencies (L-band: 1.4 GHz, 21 cm) is an established technique for estimating surface soil moisture and sea surface salinity with a suitable sensitivity. However, from space, large antennas (several meters) are required to achieve an adequate spatial resolution at L-band. So as to reduce the problem of putting into orbit a large filled antenna, the possibility of using antenna synthesis methods has been investigated. Such a system, relying on a deployable structure, has now proved to be feasible and has led to the Soil Moisture and Ocean Salinity (SMOS) mission, which is described. The main objective of the SMOS mission is to deliver key variables of the land surfaces (soil moisture fields), and of ocean surfaces (sea surface salinity fields). The SMOS mission is based on a dual polarized L-band radiometer using aperture synthesis (two-dimensional [2D] interferometer) so as to achieve a ground resolution of 50 km at the swath edges coupled with multiangular acquisitions. The radiometer will enable frequent and global coverage of the globe and deliver surface soil moisture fields over land and sea surface salinity over the oceans. The SMOS mission was proposed to the European Space Agency (ESA) in the framework of the Earth Explorer Opportunity Missions. It was selected for a tentative launch in 2005. The goal of this paper is to present the main aspects of the baseline mission and describe how soil moisture will be retrieved from SMOS data.

A simple parameterization of the L-band microwave emission from rough agricultural soils

A simple model for simulating the L-band microwave emission from bare soils is developed. The model is calibrated on a large set of measurements obtained during a three-month period over seven plots covering a wide range of surface roughness (representing the total range which can be expected on agricultural fields), soil moisture, and temperature conditions. The approach is based on the parameterization of an effective roughness parameter as a function of surface characteristics: surface roughness (standard deviation of height and correlation length) and the surface soil moisture. The parameterizations that are developed are independent of incidence angle and polarization and are valid over a large range in surface roughness conditions, representative of most of typical agricultural bare fields, from very smooth (rolled field after sowing) to very rough surfaces (deeply plowed soil). This approach will enable the use of microwave radiometric observations for soil moisture retrieval over agricultural areas.

Retrieving near-surface soil moisture from microwave radiometric observations: current status and future plans

Abstract Surface soil moisture is a key variable used to describe water and energy exchanges at the land surface/atmosphere interface. Passive microwave remotely sensed data have great potential for providing estimates of soil moisture with good temporal repetition on a daily basis and on a regional scale (∼10 km). However, the effects of vegetation cover, soil temperature, snow cover, topography, and soil surface roughness also play a significant role in the microwave emission from the surface. Different soil moisture retrieval approaches have been developed to account for the various parameters contributing to the surface microwave emission. Four main types of algorithms can be roughly distinguished depending on the way vegetation and temperature effects are accounted for. These algorithms are based on (i) land cover classification maps, (ii) ancillary remote sensing indexes, and (iii) two-parameter or (iv) three-parameter retrievals (in this case, soil moisture, vegetation optical depth, and effective surface temperature are retrieved simultaneously from the microwave observations). Methods (iii) and (iv) are based on multiconfiguration observations, in terms of frequency, polarization, or view angle. They appear to be very promising as very few ancillary information are required in the retrieval process. This paper reviews these various methods for retrieving surface soil moisture from microwave radiometric systems. The discussion highlights key issues that will have to be addressed in the near future to secure operational use of the proposed retrieval approaches.

A simple algorithm to retrieve soil moisture and vegetation biomass using passive microwave measurements over crop fields

Abstract A simple algorithm to retrieve sail moisture and vegetation water content from passive microwave measurements is analyzed in this study. The approach is based on a zeroth-order solution of the radiative transfer equations in a vegetation layer. In this study, the single scattering albedo accounts for scattering effects and two parameters account for the dependence of the optical thickness on polarization, incidence angle, and frequency. The algorithm requires only ancillary information about crop type and surface temperature. Retrievals of the surface parameters from two radiometric data sets acquired over a soybean and a wheat crop have been attempted. The model parameters have been fitted in order to achieve best match between measured and retrieved surface data. The results of the inversion are analyzed for different configurations of the radiometric observations: one or several look angles, L-band, C-band or (L-band and C-band). Sensitivity of the retrievals to the best fit values of the model parameters has also been investigated. The best configurations, requiring simultaneous measurements at L- and C-band, produce retrievals of soil moisture and biomass with a 15% estimated precision (about 0.06 m 3 /m 3 for soil moisture and 0.3 kg/m 2 for biomass) and exhibit a limited sensitivity to the best fit parameters.

An interactive vegetation SVAT model tested against data from six contrasting sites

Abstract The interactions between soil, biosphere, and atmosphere scheme (ISBA) is modified in order to account for the atmospheric carbon dioxide concentration on the stomatal aperture. The physiological stomatal resistance scheme proposed by Jacobs (1994) is employed to describe photosynthesis and its coupling with stomatal resistance at leaf level. In addition, the plant response to soil water stress is driven by a normalized soil moisture factor applied to the mesophyll conductance. The computed vegetation net assimilation can be used to feed a simple growth submodel, and to predict the density of vegetation cover. Only two parameters are needed to calibrate the growth model: the leaf life expectancy and the effective biomass per unit leaf area. The new soil–vegetation–atmosphere transfer (SVAT) scheme, called ISBA–A–gs, is tested against data from six micrometeorological databases for vegetation ranging from temperate grassland to tropical forest. It is shown that ISBA–A–gs is able to simulate the water budget and the CO2 flux correctly. Also, the leaf area index predicted by the calibrated model agrees well with observations over canopy types ranging from shortcycled crops to evergreen grasslands or forests. Once calibrated, the model is able to adapt the vegetation density in response to changes in the precipitation distribution.

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.

Estimation of watershed soil moisture index from ERS/SAR data.

Abstract The aim of this article is to show that a watershed hydrological index could be derived from ERS/SAR measurements. Indeed, it is well known that, over bare soil, the SAR signal is a function of the geometric and dielectric surface properties. The problem to estimate soil moisture is to free from the effects of the space and time fluctuations of soil roughness and from the vegetation cover attenuation and scattering. The methodology presented here is based on the selection of land cover types or “targets,” for which the SAR signal is mainly sensitive to soil water content variations, and for which the vegetation and the roughness effects (in SAR signal) can be estimated and removed if needed. This method has been validated over an agricultural watershed in France. We show that the accuracy of the retrieved soil moisture is ±0.04–0.05 cm 3 /cm 3 , except during May and June, when vegetation cover is too dense to get reliable soil information.

Simulating L-band emission of forests in view of future satellite applications

The microwave model developed at the Tor Vergata University is used to simulate the emissivity of forests, in order to study the performance of an L-band spaceborne radiometer, similar to that carried by the Soil Moisture Ocean Salinity mission. The model is first validated, and the importance of a correct vegetation growth parametrization in the modeling procedure is pointed out. This model is also used to calibrate a simple zero-order radiative transfer model, since simple models have been recognized to be useful in retrieval applications at a global scale. We show that although a zero-order approximation cannot be directly used for forests, a simple formulation may be applied, provided the albedo and the optical depth are defined as equivalent parameters.

Two-dimensional microwave interferometer retrieval capabilities over land surfaces (SMOS Mission).

Abstract This paper discusses the potential of an L-band 2-D microwave interferometric radiometer for monitoring surface variables over land surfaces. The instrument is the payload of the Soil Moisture and Ocean Salinity (SMOS) Mission recently selected for phase A studies by the European Space Agency (ESA) as the second Earth Explorer Opportunity Mission. The L-band radiometer is based on an innovative two-dimensional aperture synthesis concept. This sensor has new and significant capabilities, especially in terms of multiangular viewing configurations. The main aspects of the retrieval capabilities of SMOS for monitoring soil moisture, vegetation biomass, and surface temperature are presented in this paper. The analysis is based on model inversion. The standard errors of estimate of the surface variables are computed for various configurations as a function of both the uncertainties associated with the space measurements and those associated with the ancillary information used in the retrievals. The potential of SMOS and the possibility to retrieve one, two, or three surface variables are investigated, depending on the view angle configuration. These questions are key issues to optimize the SMOS mission scenario, to meet both the scientific requirements and the technical constraints of the mission.

Estimation of Evapotranspiration and Photosynthesis by Assimilation of Remote Sensing Data into SVAT Models

Abstract Estimation of evapotranspiration and photosynthesis from remote sensing data frequently use soil–vegetation–atmosphere transfer models (SVAT models). These models compute energy and mass transfers using descriptions of turbulent, radiative, and water exchanges, as well as a description of stomatal control in relation with water vapor transfers and photosynthesis. Remote sensing data may provide information that is useful for driving SVAT models (e.g., surface temperature, surface soil moisture, canopy structure, solar radiation absorption, or albedo). Forcing or recalibration methods may be employed to combine remote sensing data and SVAT models. In this article a review of SVAT models and remote sensing estimation of energy and mass fluxes is presented. Examples are given based on our work on two different SVAT models. Eventually, some of the difficulties in the combined use of multispectral remote sensing data and SVAT models are discussed.