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.     

Two-dimensional synthetic aperture images over a land surface scene

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     

A composite discrete-continuous approach to model the microwaveemission of vegetation

A new approach to model the microwave emission of vegetation is described in the paper. The modeling is based on the combination of both the discrete approach to simulate single scattering albedo ω and the continuous approach to simulate vegetation scattering effects. This composite model COMPOS is designed first to account for absorption effects in a more accurate way than the continuous approach and secondly to remain relevant for inversion procedures. Sensitivity studies showed that the use of a priori information about the vegetation structure is relevant to simulate ω. So, a reduced number of input parameters can be used in the composite model. Simulations of single scattering albedo ω, of canopy opacity and of wheat emissivity have been compared with several sets of radiometric data. The comparisons show that the composite approach simulations are consistent with the microwave observations     

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 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.     

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

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.     

Flagging the Topographic Impact on the SMOS Signal

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.     

Soil moisture retrieval from space: the Soil Moisture and OceanSalinity (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     

Plant water content and temperature of the Amazon forest fromsatellite microwave radiometry

An attempt is made to derive the evolution of the temperature and the water status of the Amazon forest canopy from satellite microwave radiometry. The Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) temperature-corrected tapes data are analyzed for the 6.6, 10.7, 18, and 37 GHz frequencies, at daytime and nighttime, over a zone near Manaus (3°S, 60°W), Brazil. Two periods are investigated: the wet (April-May) and dry (July-August) seasons of 1985. After separating forest- from river-contaminated pixels, atmospheric corrections are performed for water vapor, clouds, and rain, using surface and satellite data. Algorithms are developed to model the microwave thermal emission of vegetation following a continuous approach and a discrete approach. A sensitivity study is performed in order to determine which frequencies are relevant to retrieve land surface parameters. The models are then used along with an optimization procedure so as to carry out the inversion of the canopy structure parameters. The vegetation temperature and water content are retrieved through the continuous model     

The b-factor as a function of frequency and canopy type at H-polarization

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 (/spl tau//sub o/) and vegetation water content (W), given by /spl tau//sub o/=b/spl middot/W. 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/(/spl 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/spl middot/log(/spl 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.