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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 above-canopy observations, this resulted in emissivity values of bare soil, soil--litter, soil--litter--grass, and soil--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 soil 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. Index Terms--Forest, L-band, litter, microwave radiometry, understory.

The 2015/16 El Niño brought severe drought and record-breaking temperatures in the tropics. Here, using satellite-based L-band microwave vegetation optical depth, we mapped changes of above-ground biomass (AGB) during the drought and in subsequent years up to 2019. Over more than 60% of drought-affected intact forests, AGB reduced during the drought, except in the wettest part of the central Amazon, where it declined 1 y later. By the end of 2019, only 40% of AGB reduced intact forests had fully recovered to the predrought level. Using random-forest models, we found that the magnitude of AGB losses during the drought was mainly associated with regionally distinct patterns of soil water deficits and soil clay content. For the AGB recovery, we found strong influences of AGB losses during the drought and of γ. γ is a parameter related to canopy structure and is defined as the ratio of two relative height (RH) metrics of Geoscience Laser Altimeter System (GLAS) waveform data--RH25 (25% energy return height) and RH100 (100% energy return height; i.e., top canopy height). A high γ may reflect forests with a tall understory, thick and closed canopy, and/or without degradation. Such forests with a high γ (γ ≤ 0.3) appear to have a stronger capacity to recover than low-γ ones. Our results highlight the importance of forest structure when predicting the consequences of future drought stress in the tropics. [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 ([T.sub.B]) and vegetation coverage information which can be derived from optical sensors. The global [T.sub.B] 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 ([f.sub.cover]). 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 [T.sub.B], 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 [m.sup.3] * [m.sup.-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 [T.sub.B] 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. Index Terms--Microwave radiometry, microwave remote sensing, moisture, normalized difference vegetation index (NDVI), satellite applications, Soil Moisture and Ocean Salinity (SMOS), surface soil moisture, synergy, vegetation.

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. Index Terms--Microwave radiometry, moisture, simulation.

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 ([tau]), single scattering albedo ([omega]), and structural parameters tt (H) and tt (V), besides the soil roughness parameters [H.sub.R] and [N.sub.R]. 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. Index Terms--Forest, L-band, microwave radiometry, soil moisture, Soil Moisture and Ocean Salinity (SMOS).

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 To, 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 [T.sub.G], have never been investigated. In this paper, several simple formulations of [T.sub.G] 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 [T.sub.G] can be significantly improved by using additional information on the soil temperature at depth (the average error in the estimation of [T.sub.G] 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 [T.sub.G]. 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 [T.sub.G] is closer to the soil temperature at depth for these soil conditions. Index Terms--Microwave measurements, microwave radiometry, remote sensing, soil measurements, temperature.

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. Index Terms--L-band, passive microwave, Soil Moisture and Ocean Salinity (SMOS), topography impacts.

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 aH 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. Index Terms--Bare soil, emissivity, L-band radiometry, soil moisture, surface roughness.

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 [Q.sub.p] model, which was developed using advanced integral equation model simulations of microwave emission. Through evaluation of the relationship between roughness parameters [Q.sub.p] 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 available experimental data at the incidence angles of 50[degrees] and 60[degrees]. 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[degrees] and 55[degrees]. Index Terms--Inversion technique, passive microwave, roughness, soil moisture.

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. Index Terms--Global scale, L-, C-, X-band radiometry, simple emission model, Scanning Multichannel Microwave Radiometer (SMMR), Soil Moisture and Ocean Salinity (SMOS), soil moisture.

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 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. Index Terms--Microwave, modeling, surface emissivity, roughness.

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 Ait) 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. Index Terms--Forest architecture, forests, L-band, microwave radiometry.

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 background. 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. Index Terms--Angular dependence, frequency dependence, optical depth, passive microwaves, polarization dependence, vegetation properties.

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 [m.sup.3]/[m.sup.3] 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 [m.sup.3]/[m.sup.3]. Using specific retrieval configurations for each dataset, the rms error was generally lower than 0.04 [m.sup.3]/[m.sup.3] Index Terms--L-band radiometry, model inversion, retrieval, soil moisture, Soil Moisture and Ocean Salinity (SMOS), soil roughness, surface temperature, vegetation.

For anticipated synergistic approaches of the L-band radiometer on the Soil Moisture and Ocean Salinity (SMOS) mission with higher frequency microwave radiometers such as the Advanced Microwave Scanning Radiometer (AMSR) (C-band), a reanalysis has been performed on the frequency dependence of the linear relationship between vegetation optical depth ([[tau].sub.o]) and vegetation water content (W), given by [[tau].sub.o] = bxW. Insight into the frequency dependence of the b-factor is important for the retrieval of surface moisture from dual- or multifrequency microwave brightness temperature observations from space over vegetation-covered regions using model inversion techniques. The b-values presented in the literature are based on different methods and approaches. Therefore, a direct comparison is not straightforward and requires a critical analysis. This paper confirms that when a large frequency domain is considered, the b-factor is inversely proportional to the power of the wavelength b = c/[([lambda]).sup.x], which is in line with theoretical considerations. It was found that different canopy types could be separated into different groups, each with a different combination of values for log(c) and x, which characterize the linearized relationship log(b) = log(c) - x x log([lambda]). A comparison of ratios [b.sub.C]/[b.sub.L] (with C and L denoting C- and L-band, respectively) also resulted in basically the same groups. Index Terms--b-factor, canopy extinction, C-band, L-band, vegetation optical depth.

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 ([tau]) and the single-scattering aibedo ([omega]). When the retrievals are based on multiconfiguration measurements, it is necessary to take into account the dependence of [tau] and [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 he useful for developing more accurate forward modeling and retrieval methods over mixed pixels including a variety of vegetation types. Index Terms--Crops, incidence angle, microwave radiometry, modeling, polarization, Soil Moisture and Ocean Salinity mission (SMOS), vegetation.

This letter presents a synthetic L-band (1.4 GHz) multiangular brightness temperature dataset over land surfaces that was simulated at a half-degree resolution and at the global scale. The microwave emission of various land-covers (herbaceous and woody vegetation, frozen and unfrozen bare soil, snow, etc.) was computed using a simple model [L-band Microwave Emission of the Biosphere (L-MEB)] based on radiative transfer equations. The soil and vegetation characteristics needed to initialize the L-MEB model were derived from existing land-cover maps. Continuous simulations from a land-surface scheme for 1987 and 1988 provided time series of the main variables driving the L-MEB model: soil temperature at the surface and at depth, surface soil moisture, proportion of frozen surface soil moisture, and snow cover characteristics. The obtained global maps constitute a useful dataset for a first evaluation of the sensitivity of future satellite-based L-band radiometry data to soil moisture. Index Terms--Global scale, L-band radiometry, modeling, soil moisture.

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. Index Terms--Global scale, L-band radiometry, soil moisture.

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. Index Terms--Multiangle observations, parameter retrieval, passive microwaves, Soil Moisture and Ocean Salinity (SMOS), surface heterogeneity.

Our limited understanding of the impacts of drought on tropical forests significantly impedes our ability in accurately predicting the impacts of climate change on this biome. Here, we investigated the impact of drought on the dynamics of forest canopies with different heights using time‐series records of remotely sensed Ku‐band vegetation optical depth (Ku‐VOD), a proxy of top‐canopy foliar mass and water content, and separated the signal of Ku‐VOD changes into drought‐induced reductions and subsequent non‐drought gains. Both drought‐induced reductions and non‐drought increases in Ku‐VOD varied significantly with canopy height. Taller tropical forests experienced greater relative Ku‐VOD reductions during drought and larger non‐drought increases than shorter forests, but the net effect of drought was more negative in the taller forests. Meta‐analysis of in situ hydraulic traits supports the hypothesis that taller tropical forests are more vulnerable to drought stress due to smaller xylem‐transport safety margins. Additionally, Ku‐VOD of taller forests showed larger reductions due to increased atmospheric dryness, as assessed by vapor pressure deficit, and showed larger gains in response to enhanced water supply than shorter forests. Including the height‐dependent variation of hydraulic transport in ecosystem models will improve the simulated response of tropical forests to drought. [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. Index Terms--Emission model, forests, microwave radiometry, soil moisture.

Physically based land surface process/radiobrightness (LSP/R) models may characterize well the relationship between radiometric signatures and surface parameters. They can be used to develop and improve the means of sensing surface parameters by microwave radiometry. However, due to a lack in the skill to properly understand the behavior of the data, a statistical approach is often adopted. In this paper, we present the retrieval of wheat plant water content (PWC) and soil moisture content (SMC) profiles from the measured H-polarized and V-polarized brightness temperatures at 1.4 (L-band), and 10.65 (X-band) GHz by an error propagation learning back propagation (EPLBP) neural network. The PWC is defined as the total water content in the vegetation. The brightness temperatures were taken by the PORTOS radiometer over wheat fields through three month growth cycles in 1993 (PORTOS-93) and 1996 (PORTOS-96). Note that, through the neural network, there is no requirement of ancillary information on the complex surface parameters such as vegetation biomass, surface temperature, and surface roughness, etc. During both field campaigns, the L-band radiometer was used to measure brightness temperatures at incident angles from 0 to 50[degrees] at L-band and at an incident angle of 50[degrees] at X-band. The SMC profiles were measured to the depths of 10 cm in 1993 and 5 cm in 1996. The wheat was sampled approximately once a week in 1993 and 1996 to obtain its dry and wet biomass (i.e., PWC). The EPLBP neural network was trained with observations randomly chosen from the PORTOS-93 data, and evaluated by the remaining data from the same set. The trained neural network is further evaluated with the PORTOS-96 data. Index Terms--Neural network, plant water content, soil moisture.

The Soil Moisture and Ocean Salinity (SMOS) space mission is currently undergoing phase-B studies at the European Space Agency. The SMOS payload is an L-band interferometric radiometer based on a two-dimensional aperture synthesis concept. This paper presents the first images obtained by a demonstrator of the SMOS instrument over land surfaces at the Avignon test site in 1999. Index Terms--L-Band radiometry, passive microwave remote sensing, soil moisture, 2-D interferometer.

This work investigates the potential use of passive and active microwave observations to monitor soil moisture and vegetation biomass over a soybean cover. The work is based on a sensitivity analysis from a large set of data generated by radiative-transfer models. Some appropriate configurations are identified. In particular, the combined use of passive data at 1.4 GHz, with multiangle active measurements at 5 GH(sub z), is found to be promising.