André Chanzy

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.

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.

A parameterized multifrequency-polarization surface emission model

This study develops a parameterized bare surface emission model for the applications in analyses of the passive microwave satellite measurements from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E). We first evaluated the capability of the advanced integral equation model (AIEM) in simulating wide-band and high-incidence surface emission signals in comparison with INRAs field experimental data obtained in 1993. The evaluation results showed a very good agreement. With the confirmed confidence, we generated a bare surface emission database for a wide range of surface dielectric and roughness properties under AMSR-E sensor configurations using the AIEM model. Through the evaluations of the commonly used semiempirical models with both the AIEM simulated and the field experimental data, we developed a parameterized multifrequency-polarization surface emission model-the Qp model. This model relates the effects of the surface roughness on the emission signals through the roughness variable Qp at the polarization p. The Qp can be simply described as a single-surface roughness property-the ratio of the surface rms height and the correlation length. The comparison of the emissivity simulations by the Qp and AIEM models indicated that the absolute error is extremely small at the magnitude of 10/sup -3/. The newly developed surface emission model should be very useful in modeling, improving our understanding, analyses, and predictions of the AMSR-E measurements.

Characterizing the dependence of vegetation model parameters on crop structure, incidence angle, and polarization at L-band

To retrieve soil moisture over vegetation-covered areas from microwave radiometry, it is necessary to account for vegetation effects. At L-band, many retrieval approaches are based on a simple model that relies on two vegetation parameters: the optical depth (/spl tau/) and the single-scattering albedo (/spl omega/). When the retrievals are based on multiconfiguration measurements, it is necessary to take into account the dependence of /spl tau/ and /spl omega/ on the system configuration, in terms of incidence angle and polarization. In this paper, this dependence was investigated for several crop types (corn, soybean, wheat, grass, and alfalfa) based on L-band experimental datasets. The results should be useful for developing more accurate forward modeling and retrieval methods over mixed pixels including a variety of vegetation types.

Evaluating an Improved Parameterization of the Soil Emission in L-MEB

In the forward model [L-band microwave emission of the biosphere (L-MEB)] used in the Soil Moisture and Ocean Salinity level-2 retrieval algorithm, modeling of the roughness effects is based on a simple semiempirical approach using three main “roughness” model parameters: HR, QR, and NR. In many studies, the two parameters QR and NR are set to zero. However, recent results in the literature showed that this is too approximate to accurately simulate the microwave emission of the rough soil surfaces at L-band. To investigate this, a reanalysis of the PORTOS-93 data set was carried out in this paper, considering a large range of roughness conditions. First, the results confirmed that QR could be set to zero. Second, a refinement of the L-MEB soil model, considering values of NR for both polarizations (namely, NRV and NRH), improved the model accuracy. Furthermore, simple calibrations relating the retrieved values of the roughness model parameters HR and (NRH - NRV) to the standard deviation of the surface height were developed. This new calibration of L-MEB provided a good accuracy (better than 5 K) over a large range of soil roughness and moisture conditions of the PORTOS-93 data set. Conversely, the calibrations of the roughness effects based on the Choudhury approach, which is still widely used, provided unrealistic values of surface emissivities for medium or large roughness conditions.

An empirical calibration of the integral equation model based on SAR data, soil moisture and surface roughness measurement over bare soils

The retrieval of surface parameters demands the use of well calibrated models and unfortunately, none of the existing models provide consistently good agreement with the measured data. The overall objective of this article is to propose a semi-empirical calibration of the Integral Equation Model (IEM) so as to better reproduce the backscattering coefficient measured from SAR images over bare soils. As correlation length is not only the least accurate parameter but also the most difficult to measure, we propose its empirical estimation from an experimental data set of SAR images and soil parameter measurements. Based on a first data set, correlation length behaviour was studied in terms of f rms (where f is the wave number and rms the standard deviation of surface height) and radar configuration (polarization and incidence angle). Exponential relationships between optimal correlation length and rms height were found for each radar configuration. The IEM was then tested on another set of measured data in order to validate the calibration procedure. The new calibrated version of the IEM, corresponding to the original IEM with a coupling of the empirical function of correlation length, shows a very good agreement with the backscattering measurements provided by space-borne SAR systems. This adapted version of the IEM can be used in inversion techniques for retrieving rms height and/or soil moisture from radar observations.

Sensitivity of Passive Microwave Observations to Soil Moisture and Vegetation Water Content: L-Band to W-Band

Ground-based multifrequency (L-band to W-band, 1.41-90 GHz) and multiangular (20°-50°) bipolarized (V and H) microwave radiometer observations, acquired over a dense wheat field, are analyzed in order to assess the sensitivity of brightness temperatures (Tb) to land surface properties: surface soil moisture (mv) and vegetation water content (VWC). For each frequency, a combination of microwave Tb observed at either two contrasting incidence angles or two polarizations is used to retrieve mv and VWC, through regressed empirical logarithmic equations. The retrieval performance of the regression is used as an indicator of the sensitivity of the microwave signal to either mv or VWC. In general, L-band measurements are shown to be sensitive to both mv and VWC, with lowest root mean square errors (0.04 m3 ·m-3 and 0.52 kg ·m-2 , respectively) obtained at H polarization, 20° and 50° incidence angles. In spite of the dense vegetation, it is shown that mv influences the microwave observations from L-band to K-band (23.8 GHz). The highest sensitivity to soil moisture is observed at L-band in all configurations, while observations at higher frequencies, from C-band (5.05 GHz) to K-band, are only moderately influenced by mv at low incidence angles (e.g., 20°). These frequencies are also shown to be very sensitive to VWC in all the configurations tested. The highest frequencies (Q- and W-bands) are shown to be moderately sensitive to VWC only. These results are used to analyze the response of W-band emissivities derived from the Advanced Microwave Sounding Unit instruments over northern France.

Soil moisture and temperature profile effects on microwave emission at low frequencies

Abstract Soil moisture and temperature vertical profiles vary quickly during the day and may have a significant influence on the soil microwave emission. The objective of this work is to quantify such an influence and the consequences in soil moisture estimation from microwave radiometric information. The analysis is based on experimental data collected by the ground-based PORTOS radiometer at 1.4, 5.05, and 10.65 GHz and data simulated by a coherent model of microwave emission from layered media [Wilheit model (1978)]. In order to simulate diurnal variations of the brightness temperature (TB), the Wilheit model is coupled to a mechanistic model of heat and water flows in the soil. The Wilheit model is validated on experimental data and its performances for estimating TB are compared to those of a simpler approach based on a description of the soil media as a single layer (Fresnel model). When the depth of this single layer (hereafter referred to as the sampling depth) is determined to fit the experimental data, similar accuracy in TB estimation is found with both the Wilheit and Fresnel models. The soil microwave emission is found to be strongly affected by the diurnal variations of soil moisture and temperature profiles. Consequently, the TB sensitivity to soil moisture and temperature profiles has an influence on the estimation, from microwave observations, of the surface soil moisture in a surface layer with a fixed depth (05): the accuracy of θs retrievals and the optimal sampling depth depends both on the variation in soil moisture and temperature profile shape.

Microwave emission of vegetation: sensitivity to leaf characteristics

The effects of leaf characteristics on the microwave emission of land surfaces are analyzed. In order to simulate these effects, a radiative transfer model is presented. The medium consists of a vegetated layer containing randomly oriented leaves, modeled as elliptic-shaped scatterers, over the ground surface. Radiative transfer equations are solved with a discrete-ordinate-eigenanalysis method. The calculation of the phase matrix of the elliptic scatterers is based on the generalized Rayleigh-Gans approximation, which increases the frequency range of the modeling. The sensitivity of brightness temperature and polarization ratio to leaf characteristics, volume fraction, gravimetric moisture, size, shape, and inclination distribution is investigated at C-, and X-band. The behavior of the simulated emission of a soybean canopy versus frequency and incidence angle is studied for different soil moisture levels. Up to 10 GHz the microwave emission appears to contain significant information on underlying soil moisture. >

A simple approach to monitor crop biomass from C-band radar data

Abstract A simple two-term model of the radar backscattering coefficient of crops, designed for the retrieval of the amount of water in the canopy, is described and analyzed. The principle of the method is to calibrate the simple model from the simulations of a discrete first-order radiative transfer model during crop development. The canopy structure is taken into account in the discrete model to compute the relationships between a) the vegetation direct contribution to backscattering σ ° v and the optical depth τ and b) the optical depth τ and the amount of water in the canopy. The two-term model is tested against C-band radar data acquired over a soybean crop during the whole vegetation cycle. The simulations correlate well with the measurements and the retrieval of the amount of water in the canopy Wc (kg/m 2 ) can be carried out. Accurate temporal information on the crop growth could be derived from the radar data. Ancillary information about soil moisture are required, but it is found that rough estimates on a 4–5 day basis are sufficient.