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The Soil Moisture and Ocean Salinity (SMOS) mission provides global surface soil moisture over the continental land surfaces. The retrieval algorithm is based on the comparison between the observations of the L-band (1.4 GHz) brightness temperatures (TB) and the simulated TB data using the L-band Microwave Emission of the Biosphere (L-MEB) model. The L-MEB model includes a dielectric model for the computation of the soil dielectric constant. Since the beginning of the mission, the Dobson model has been used in the operational SMOS algorithm. Recently, a new model of the soil dielectric constant has been developed by Mironov et al. and is now considered. This paper is the first evaluation of these two models based on the actual SMOS observations. First, both Dobson and Mironov models were modified to ensure that the SMOS retrieval algorithm converges to realistic soil moisture retrievals (symmetrization for negative soil moisture values was applied). Second, soil moisture was retrieved over several sites using both Dobson and Mironov models to compute the soil dielectric constant and were compared with in situ measurements. At a global scale, the use of the Mironov model leads to higher retrieved soil moisture than when using the Dobson model (0.033 m3/m3 on average). However, the comparisons of the two model output with in situ measurements over various test sites do not demonstrate a superior performance of one model over the other. [ABSTRACT FROM AUTHOR]

In this paper, a numerical modeling approach was used to evaluate the semiempirical H–Q model used in the Soil Moisture and Ocean Salinity (SMOS) retrieval algorithm to account for roughness effects over bare soil. The H–Q model uses four parameters, HR, QR, NRH, and NRV, which are usually calibrated at the ground scale for different surface types. The aim of this paper is to investigate whether these empirical parameters could be linked to the physical roughness parameters of standard deviation of surface heights \sigma and autocorrelation length Lc. First, a numerical modeling approach was used to calculate rough soil emissivities for different roughness and soil moisture conditions. Second, H –Q model parameters were retrieved by minimizing a cost function between these emissivities and those calculated by the H–Q model. It was found that the retrieved HR could be related directly to Zs = \sigma^2/Lc and that QR, NRV, and NRH were dependent on HR. HR was found to have a negligible dependence on soil moisture. Based on these results, a new model was proposed where the four H–Q model parameters were calibrated to Zs. This model was tested on the PORTOS 1993 data set and found to yield a root-mean-square difference between the retrieved and measured soil moisture values of \sim\! 0.03\ \m^3/\m^3, which was within the desired 0.04-\m^3/\m^3 error margin for the SMOS mission. [ABSTRACT FROM AUTHOR]

Land surface temperature data are rarely available at high temporal and spatial resolutions at the same locations. To fill this gap, the low spatial resolution data can be disaggregated at high temporal frequency using empirical relationships between remotely sensed temperature and fractional green (photosynthetically active) and senescent vegetation covers. In this paper, a new disaggregation methodology is developed by physically linking remotely sensed surface temperature to fractional green and senescent vegetation covers using a radiative transfer equation. Moreover, the methodology is implemented with two additional factors related to the energy budget of irrigated areas, being the fraction of open water and soil evaporative efficiency (ratio of actual to potential soil evaporation). The approach is tested over a 5 km by 32 km irrigated agricultural area in Australia using airborne Polarimetric L-band Multibeam Radiometer brightness temperature and spaceborne Advanced Scanning Thermal Emission and Reflection radiometer (ASTER) multispectral data. Fractional green vegetation cover, fractional senescent vegetation cover, fractional open water, and soil evaporative efficiency are derived from red, near-infrared, shortwave-infrared, and microwave-L band data. Low-resolution land surface temperature is simulated by aggregating ASTER land surface temperature to 1-km resolution, and the disaggregated temperature is verified against the high-resolution ASTER temperature data initially used in the aggregation process. The error in disaggregated temperature is successively reduced from 1.65°C to 1.16°C by including each of the four parameters. The correlation coefficient and slope between the disaggregated and ASTER temperatures are improved from 0.79 to 0.89 and from 0.63 to 0.88, respectively. Moreover, the radiative transfer equation allows quantification of the impact on disaggregation of the temperature at high resolution for each parameter: fractional green vegetation cover is responsible for 42% of the variability in disaggregated temperature, fractional senescent vegetation cover for 11%, fractional open water for 20%, and soil evaporative efficiency for 27%. [ABSTRACT FROM AUTHOR]

Radiative properties at 1.4 GHz of vine vegetation are investigated by measuring brightness temperatures with the ETH L-band Radiometer II (ELBARA II) operated on a tower at the Mediterranean Ecosystem L-band Characterisation Experiment III (MELBEX III) field site in Spain. To this aim, experiments with and without a reflecting foil placed under the vines were performed for the vegetation winter and summer states, respectively, to provide prevailingly information on vegetation transmissivities. The resulting parameters, which can be considered as “ground truth” for the MELBEX III vineyard, were retrieved from brightness temperature at horizontal and vertical polarization measured at observation angles between 30° and 60°. These MELBEX III “ground-truth” values are representative for the Mediterranean Soil Moisture and Ocean Salinity (SMOS) Valencia Anchor Station (VAS) and therefore valuable for the corresponding calibration and validation activities over the VAS site. Likewise, quantifying the uncertainties of the measured brightness temperatures was also important, particularly as several equivalent ELBARA II instruments are currently operative in ongoing SMOS-related field campaigns. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Ground-based multifrequency (L-band to W-band, 1.41–90 GHz) and multiangular (20 ^\circ–50^\circ) 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 \m^3 \cdot \m^-3 and 0.52 \kg \cdot \m^-2, respectively) obtained at H polarization, 20^\circ and 50^\circ 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 ^\circ). 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. [ABSTRACT FROM AUTHOR]

The emission of bare soils at microwave L-band (1-2 GHz) frequencies is known to be correlated with surface soil moisture. Roughness plays an important role in determining soil emissivity although it is not clear which roughness length scales are most relevant. Small-scale (i.e., smaller than the resolution limit) inhomogeneities across the soil surface and with soil depth caused by both spatially varying soil properties and topographic features may affect soil emissivity. In this paper, roughness effects were investigated by comparing measured brightness temperatures of well-characterized bare soil surfaces with the results from two reflectivity models. The selected models are the air-to-soil transition model and Shi's parameterization of the integral equation model (IEM). The experimental data taken from the Surface Monitoring of the Soil Reservoir Experiment (SMOSREX) consist of surface profiles, soil permittivities and temperatures, and brightness temperatures at 1.4 GHz with horizontal and vertical polarizations. The types of correlation functions of the rough surfaces were investigated as required to evaluate Shi's parameterization of the IEM. The correlation functions were found to be clearly more exponential than Gaussian. Over the experimental period, the diurnal mean root mean square (rms) height decreased, while the correlation length and the type of correlation function did not change. Comparing the reflectivity models with respect to their sensitivities to the surface rms height and correlation length revealed distinct differences. Modeled reflectivities were tested against reflectivities derived from measured brightness, which showed that the two models perform differently depending on the polarization and the observation angle. [ABSTRACT FROM AUTHOR]

Recent studies of passive L-band observations over forests have shown that the average canopy transmissivity in temperate coniferous and deciduous forests is on the order of 0.4-0.5. Although the canopy would therefore be expected to transmit a reasonable amount of ground emission, the total emission observed above the canopy shows very little variation with varying soil moisture content. Moist litter present on the forest floor is known to obscure the soil emission. Therefore, more knowledge on the L-band radiative properties of litter and understory layers is needed to better understand the emission of the whole forest system. In order to contribute toward this issue, a field experiment was conducted in a pine forest in southwest France. Radiometric observations were done on the canopy and on different configurations of the forest floor, following sequential stripping of each forest floor layer. In combination with a long-term data set of abovecanopy observations, this resulted in emissivity values of bare soil, soil-litter, soil-litter-grass, and soU-litter-grass-canopy configurations for a range of soil and litter moisture values. Calculations involved the use of the Wilheit and L-MEB models. The sensitivity to soil moisture was found to be substantially suppressed by the presence of a grass understory and litter. This corroborates the low correlation between sdil moisture and L-band brightness temperature measured above the canopy. Several results of recent modeling and laboratory studies are also confirmed by this paper, which is, to our knowledge, the first to use in situ experimental data in this context. [ABSTRACT FROM AUTHOR]

To retrieve soil moisture from L-band microwave radiometry, it is necessary to account for the effects of temperature within both vegetation and soil media. To compute the effective soil temperature TG, several simple formulations accounting for soil temperatures at the surface and at depth and surface soil moisture have been developed. However, the effects of the soil physical properties in terms of texture, density, or structure, which all may be important variables in the modeling of TG, have never been investigated. In this paper, several simple formulations of TG at L-band, accounting for or ignoring the effects of soil texture and density, were developed and compared based on a very large simulated data set. The best configurations and parameterizations of these simple formulations were computed and could be directly used for operational applications in future soil moisture retrieval studies. For instance, we showed that the use of the surface temperature in the estimation of TG can be significantly improved by using additional information on the soil temperature at depth (the average error in the estimation of TG decreased from ∼4 to ∼1.8 K). On the contrary, almost no improvement was obtained if air temperature was used instead of surface temperature. Also, it is shown that the use of additional information on the soil properties, mainly the soil clay content and density, led to improved results by about 0.2 K in the estimation of TG. The improvement was found to be larger for sandy and dry soils: simplified formulations accounting for soil properties are able to represent the fact that TG is closer to the soil temperature at depth for these soil conditions. [ABSTRACT FROM AUTHOR]

The European Centre for Medium-range Weather Forecasts (ECMWF) brightness will use temperatures from the Soil Moisture and Ocean Salinity mission to analyze root zone soil moisture through a variational data assimilation system. The first guess is obtained from numerical weather prediction (NWP) model fields, an auxiliary database, and a land surface microwave emission model. In this paper, we present the Community Microwave Emission Model and research the first-guess errors in L-band brightness temperatures. An error propagation study is performed on errors introduced through: 1) uncertainties in the parameterizations of the radiative transfer model; 2) auxiliary geophysical quantities for the radiative transfer computations; and 3) an imperfect NWP model. It is found that the vegetation and dielectric models introduce uncertainties with a difference of up to 25 K between models. However, the biggest error in brightness temperature is likely related to the use of an auxiliary vegetation database, which results in differences of -20 to +20 K in our simulations. These potential errors are in many regions higher than the variance in brightness temperatures related to an imperfect NWP model. [ABSTRACT FROM AUTHOR]

Methods to retrieve surface soil moisture were assessed at the global scale for one entire year by using simulated Soil Moisture and Ocean Salinity brightness temperatures (TB) and vegetation coverage information which can be derived from optical sensors. The global TB database consists of half-degree continental pixels and accounts for within-pixel heterogeneity, based on 1-km resolution land cover maps. The retrievals were performed by using a three-parameter inversion method applied to the L-band Microwave Emission of the Biosphere model. By using a Bayesian approach, vegetation data were injected as a priori information. Two options were investigated to profit from normalized difference vegetation index products: providing an a priori knowledge either on vegetation optical depth or on the vegetation cover fraction (fcover). The latter option allows for a better description of the surface heterogeneity by considering a bare soil fraction. When an error of 1 K is applied to the TB, both synergistic schemes significantly improved the soil moisture accuracy compared with methods using microwave data only. Using the vegetation a priori information, about 80% of the pixels present soil moisture retrieval accuracy less than 0.04 m³ m-3 in terms of root-mean-square error, whereas methods based only on the microwave data provide 63% of pixels of the studied area with this accuracy. If the error in TB is larger (2 or 3 K), the soil moisture retrieval accuracy decreases significantly for both methods. The use of optical data to give a priori value of vegetation optical option is then the best for these cases. [ABSTRACT FROM AUTHOR]

In this paper, the L-band Microwave Emission of the Biosphere (L-MEB) model used in the Soil Moisture and Ocean Salinity (SMOS) Level 2 Soil Moisture algorithm is calibrated using L-band (1.4 GHz) microwave measurements over a coniferous (Pine) and a deciduous (mixed/Beech) forest. This resulted in working values of the main canopy parameters optical depth (τ), single scattering albedo (ω), and structural parameters tt(H) and tt(V), besides the soil roughness parameters HR and NR. Using these calibrated values in the forward model resulted in a root mean-square error in brightness temperatures from 2.8 to 3.8 K, depending on data set and polarization. Furthermore, the relationship between canopy optical depth and leaf area index is investigated for the deciduous site. Finally, a sensitivity study is conducted for the focus parameters, temperature, soil moisture, and precipitation. The results found in this paper will be integrated in the operational SMOS Level 2 Soil Moisture algorithm and used in future inversions of the L-MEB model, for soil moisture retrievals over heterogeneous, partly forested areas. [ABSTRACT FROM AUTHOR]

Soil moisture retrieval models from the Soil Moisture and Ocean Salinity (SMOS) mission, which is an L-band microwave interferometer, are based on multiangular measurements and make use of the emissivity angular signature. Mountainous areas modify local incidence angles, implying significant impacts on brightness temperatures and, consequently, on soil moisture retrievals. The purpose of this paper is to establish a criterion in quantifying the relevance of topographic impacts at the SMOS scale (∼40 km). The goal is thus to define a method of flagging the pixels according to the relative impact of topography on the brightness temperature. The proposed method uses the variogram of digital elevation model images. As a result, a map of the pixels to be flagged is produced to ensure that no soil moisture retrievals are carried out on pixels that are affected by strong topographic effects. As validation, a model was also used to simulate differences between brightness temperature variations between mountainous areas and flat surfaces. [ABSTRACT FROM AUTHOR]

A simple reflectivity model of a bare soil at L-band is developed to account for the effects of soil roughness at different angles and polarizations. This model was developed using a long-term dataset acquired over the bare soil in the framework of the Surface Monitoring Of the Soil Reservoir EXperiment (SMOSREX). It is shown that the roughness effects are different depending on the measurement configuration, in terms of incidence angle and polarization. However, in this paper, a simple parameterization that is based on a single roughness parameter was calibrated in order to account for this angular and polarization dependencies. This parameter was found to be dependent on soil moisture: drier conditions were associated to higher "roughness" conditions. The root-mean-square error between the measured and modeled reflectivities on days when no precipitation events were detected at vertical polarization (V-pol) is 0.0275, and at horizontal polarization (H-pol), the rmse is 0.0237; all incidence angles were considered. When all data are considered, the rmsd for V-pol is 0.0350, and for H-pol, the rmse is 0.0373. This new simple model is suitable for soil moisture retrieval from Soil Moisture and Ocean Salinity data. By means of this simple parameterization, almost two years of soil moisture data were retrieved with a good accuracy. The SMOSREX dataset allowed to ensure a long-term suitability of the proposed parameterization. [ABSTRACT FROM AUTHOR]

A physically based bare-surface soil moisture inversion technique for application with passive microwave satellite measurements, including the Advanced Microwave- Scanning Radiometer—Earth Observing System, Special Sensor Microwave/Imager, Scanning Multichannel Microwave Radiometer, and Tropical Rainfall Measuring Mission Microwave Imager, was developed in this paper. The inversion technique is based on the concept of a simple parameterized surface emission model, the Qp, model, which was developed using advanced integral equation model simulations of microwave emission. Through evaluation of the relationship between roughness parameters Qp, at different polarizations, it was found that they could be described by a linear function. Using this relationship and the surface emissivities measured from two polarizations, the effect of the surface roughness is cancelled out. In other words, this approach consisted in adding different weights on the v and h polarization measurements so as to minimize the surface roughness effects. This method leads to a dual-polarization inversion technique for the estimation of the surface dielectric properties directly from the emissivity measurements. For validation, we compared the soil moisture estimates, derived from ground radiometer measurements at C- to Ka-band obtained from the Institute National de Recherches Agronomiques' field experimental data in 1993 and the Beltsville Agricultural Research Center's field experimental data at C- and X-band obtained in 1979-1982, with the field in situ soil moisture measurements. The accuracies [root-mean-square error (rmse)] are higher than 4% for the avail- able experimental data at the incidence angles of 500 and 60°. The newly developed inversion technique should be very useful in monitoring global soil moisture properties using the currently available satellite instruments that commonly have incidence angles between 50° and 550W [ABSTRACT FROM AUTHOR]

In the framework of the Soil Moisture and Ocean Salinity mission, a two-year (1987–1988) global simulation of brightness temperatures (TB) at L-band was performed using a simple model [L-band microwave emission of the biosphere, (L-MEB)] based on radiative transfer equations. However, the lack of alternative L-band spaceborne measurements corresponding to real-world data prevented from assessing the realism of the simulated global-scale TB fields. In this study, using a similar modeling approach, TB simulations were performed at C-band and X-band. These simulations required the development of C-MEB and X-MEB models, corresponding to the equivalent of L-MEB at C-band and X-band, respectively. These simulations were compared with Scanning Multichannel Microwave Radiometer (SMMR) measurements during the period January to August 1987 (corresponding to the end of life of the SMMR mission). A sensitivity study was also carried out to assess, at a global scale, the relative contributions of the main MEB parameters (particularly the roughness and vegetation model parameters). Regional differences between simulated and measured TBs were analyzed, discriminating possible issues either linked to the radiative transfer model (C-MEB and X-MEB) or due to land surface simulations. A global agreement between observations and simulations was discussed and allowed to evaluate regions where soil moisture retrievals would give best results. This comparison step made at C-band and X-band allowed to better assess how realistic and/or accurate the L-band simulations could be. [ABSTRACT FROM AUTHOR]

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 INRA's 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 ALEM 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 10-3. The newly developed surface emission model should be very useful in modeling, improving our understanding, analyses, and predictions of the AMSR-E measurements. [ABSTRACT FROM AUTHOR]

In the microwave region, discrete physical models are often used to simulate surface emission and backscattering of forests These models require detailed information on the geometry of the forest constituents, typically represented by canonical shapes. This paper presents a forest geometric description (FGD) of a Maritime pine tree forest (Pinus pinaster Aït) suitable for discrete models at low microwave frequencies. The FGD contains a number of allometric equations developed from the analysis of a very large set of ground-based measurements of the forest structure. These allometric equations reproduce the density, shape, and dimension of branches, trunks, and needles, represented by cylinders in the FGD. An original approach to describe the tree architecture is presented: primary branches (branches inserted in the trunk) are split into segments or growth units (GUs) so that the full branch curvature can be accounted for, and probability distribution functions are given for the orientation and diameter of the GUs. The FGD uses only two variables, tree density (number of trees per ha) and tree age, as input information to simulate the forest geometric characteristics at three layers: the upper crown, the lower crown, and a crown-free layer. Input parameters to compute the dielectric constant of the forest constituents are also given. [ABSTRACT FROM AUTHOR]

In support of algorithm development for the multiangle interferometric synthetic L-band radiometer on the Soil Moisture and Ocean Salinity sensor (SMOS) and for possible synergistic approaches with higher frequency microwave radiometers such as the Advanced Microwave Scanning Radiometer (C-band), an inventory has been made of polarization, angular, and frequency dependencies of vegetation optical depth and single-scattering albedo. Both parameters form the basis of a zero-order radiative transfer model, which is often used for inverse modeling of microwave observations from space. The inventory is based on experimental data published in the literature. Underlying models have been reviewed because data comparison is impossible without due consideration of the theoretical back- ground. In general, it can be concluded that both single-scattering albedo and optical depth are angular, polarization, and frequency dependent. This dependence, however, depends on the canopy type and structure. Angular dependence implies that the cosine correction for the slant path through the canopy is no longer valid. Knowledge of these dependencies, therefore, is important for processing multiangle observations such as those anticipated for the planned SMOS and for possible synergistic approaches with C-band observations. Because of the existing variety of methods and procedures found in the literature, some guidelines for a protocol for field experiments are proposed in order to facilitate intercomparison of experimental results and proper incorporation of the parameters in zero-order transfer models. [ABSTRACT FROM AUTHOR]

A number of studies have shown the feasibility of estimating surface soil moisture from L-band passive microwave measurements. Such measurements should be acquired in the near future by the Soil Moisture and Ocean Salinity (SMOS) mission. The SMOS measurements will be done at many incidence angles and two polarizations. This multiconfiguration capability could be very useful in soil moisture retrieval studies for decoupling between the effects of soil moisture and of the various surface parameters that also influence the surface emission (surface temperature, vegetation attenuation, soil roughness, etc.). The possibility to implement N-parameter (N-P) retrieval methods (where N = 2,3,4, . . . , corresponds to the number of parameters that are retrieved) was investigated in this study based on experimental datasets acquired over a variety of crop fields. A large number of configurations of the N-P retrievals were studied, using several initializations of the model input parameters that were considered to be fixed or free. The best general configuration using no ancillary information (same configuration for all datasets) provided an rms error of about 0.059 m3/m3 in the soil moisture retrievals. If a priori information was available on soil roughness and at least one vegetation model parameter, the rms error decreased to 0.049 m3/m3. Using specific retrieval configurations for each dataset, the rms error was generally lower than 0.04 m3/m3 [ABSTRACT FROM AUTHOR]

Using a global simulation of L-band (1.4 GHz) brightness temperature (T[sub B]) for two years (1987 and 1988), the relationship between L-band brightness temperatures and surface soil moisture was analyzed using simple regression models. The global T[sub B] dataset describes continental pixels at a half-degree spatial resolution and accounts for within-pixel heterogeneity, based on 1-km resolution land cover maps. Two different statistical methods were investigated. First, a single regression model was obtained using a linear combination of T[sub B] indexes. This method consisted in retrieving surface soil moisture using the same global regression model for all the pixels. Second, a regression model was calibrated over each pixel using similar linear combinations of the T[sub B] indexes. In both cases, the influence of the radiometric noise on T[sub B] was investigated. Applying these two methods, the capability of L-band T[sub B] observations to monitor surface soil moisture was evaluated at the global scale and during a two-year time period. Global maps of the estimated accuracy of the soil moisture retrievals were produced. These results contribute to better define the potential of the observations from future spaceborne missions such as the Soil Moisture and Ocean Salinity (SMOS) mission. [ABSTRACT FROM AUTHOR]

The L-band (1.4 GHz) two-dimensional microwave interferometric radiometer, the payload of the Soil Moisture and Ocean Salinity (SMOS) mission, will observe elements of the earth's surface simultaneously at multiple angles. Compared to single-angle observations, this multiangle observation technology is expected to significantly improve the capability of passive microwave remote sensing to retrieve soil moisture and vegetation properties from space. Although multiangle retrieval algorithms have been developed and successfully evaluated for homogeneous surfaces on the basis of simulation studies, the inherently large footprint of microwave observations from space has serious consequences for parameter retrieval from "real-world" inhomogeneous surfaces. At the spatial scale of SMOS (∼30 km for nadir observations), the earth's surface is inhomogeneous almost by default. This aspect has not been fully accounted for yet. This study gives some insight into the consequences of vegetation spatial heterogeneity for the retrieval of "effective" surface parameters (soil moisture, canopy microwave transmissivity, and effective surface temperature) from inhomogeneous surfaces without prior knowledge of the within-pixel canopy heterogeneity. [ABSTRACT FROM AUTHOR]

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. In this paper, 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. [ABSTRACT FROM AUTHOR]

Present a study that investigated the retrieval of wheat plant water content and soil moisture content profiles from the measured H-polarized and V-polarized brightness temperatures by an error learning back propagation neural network. Description of the retrieval process; Correlation between brightness temperatures and surface parameters; Details of the retrieval of soil moisture and vegetation water content.

Presents information on the first images obtained by a demonstrator of the Soil Moisture and Ocean Salinity (SMOS) over land surfaces at the Avignon test site in 1999. Details of the SMOS mission; Function of L-band microwave radiometry; Positions of the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) during the SMOS experiment; Information on the MIRAS demonstrator; Description of the images obtained over land surfaces.

Presents information on a study which described a model for simulating the L-band microwave emission from bare soils. Experimental details; Derivation of surface emissivity from the measurements; Discussion and conclusions.

Presents information on a study which described the antenna synthesis methods for Soil Moisture and Ocean Salinity mission. Mission description; Data acquisition and processing; Calibration and validation; Conclusion.

Focuses on a study that tested a theoretical model against experimental data obtained during the overall crop cycle of a wheat field and is used to investigate the potential of multifrequency radiometers to retrieve biomass and soil moisture. Methodology; Results; Proposed solution to the problem of retrieving the moisture content of vegetation-covered soils.

Presents a study which analyzed the frequency and angular variations of land surface microwave emissivities. Details on special sensor microwave/temperature (SSM/T) and advanced microwave sounding units (AMSU); Scanning and polarization mechanisms of the instruments; Feasibility of estimating the SSM/T and AMSU emissivities over the globe from special sensor microwave/imager.

Presents information on a study which investigated the potential use of microwave observations to monitor soil moisture and vegetation biomass over a soybean cover. Differences between the active and passive models of microwave observations used in the study; Parametric analysis; Discussion and conclusion.

In the above paper (ibid., vol. 49, no. 4, pp. 1177-1189, Apr. 2011), there is an error in equation (7). The explanation and corrected equation are presented here. [ABSTRACT FROM PUBLISHER]