J.-P. Wigneron

French National Institute for Agricultural Research, Lutetia Parisorum, Île-de-France, France

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Publications (154)207.86 Total impact

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    ABSTRACT: Global Level-3 surface soil moisture (SM) maps derived from the passive microwave SMOS (Soil Moisture and Ocean Salinity) observations at L-band have recently been released. In this study, a comparative analysis of this Level 3 product (referred to as SMOSL3) along with another Surface SM (SSM) product derived from the observations of the Advanced Microwave Scanning Radiometer (AMSR-E) at C-band is presented (this latter product is referred to as AMSRM). SM-DAS-2, a SSM product produced by the European Centre for Medium Range Weather Forecasts (ECMWF) Land Data Assimilation System (LDAS) was used to monitor both SMOSL3 and AMSRM qualities. The present study was carried out from 03/2010 to 09/2011, a period during which both SMOS and AMSR-E products were available at global scale. Three statistical metrics were used for the evaluation; the correlation coefficient (R), the Root Mean Squared Difference (RMSD), and the bias. Results were analysed using maps of biomes and Leaf Area Index (LAI). It is shown that both SMOSL3 and AMSRM captured well the spatio-temporal variability of SM-DAS-2 for most of the biomes. In terms of correlation values, the SMOSL3 product was found to better capture the SSM temporal dynamics in highly vegetated biomes (“tropical humid”, “temperate humid”, etc.) while best results for AMSRM were obtained over arid and semi-arid biomes (“desert temperate”, “desert tropical”, etc.). Finally, we showed that the accuracy of the remotely sensed SSM products is strongly related to LAI. Both the SMOSL3 and AMSRM (marginally better) SSM products correlated well with the SM-DAS-2 product over regions with sparse vegetation for values of LAI ≤ 1 (these regions represent almost 50% of the pixels considered in this global study). In regions where LAI >1, SMOSL3 showed better correlations with SM-DAS-2 than AMSRM: SMOSL3 had a consistent performance up to LAI = 6, whereas the AMSRM performance deteriorated with increasing values of LAI. This study reveals that SMOS and AMSR-E complement one another in monitoring SSM over a wide range in conditions of vegetation density and that there are valuable satellite observed SSM data records over more than 10 years, which can be used to study land–atmosphere processes.
    Remote Sensing of Environment 01/2014; 149:181–195. · 5.10 Impact Factor
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    ABSTRACT: Global surface soil moisture (SSM) datasets are being produced based on active and passive microwave satellite observations and simulations from land surface models (LSM). This study investigates the consistency of two global satellite-based SSM datasets based on microwave remote sensing observations from the passive Soil Moisture and Ocean Salinity (SMOS; SMOSL3 version 2.5) and the active Advanced Scatterometer (ASCAT; version TU-Wien-WARP 5.5) with respect to LSM SSM from the MERRA-Land data product. The relationship between the global-scale SSM products was studied during the 2010–2012 period using (1) a time series statistics (considering both original SSM data and anomalies), (2) a space–time analysis using Hovmöller diagrams, and (3) a triple collocation error model. The SMOSL3 and ASCAT retrievals are consistent with the temporal dynamics of modeled SSM (correlation R > 0.70 for original SSM) in the transition zones between wet and dry climates, including the Sahel, the Indian subcontinent, the Great Plains of North America, eastern Australia, and south-eastern Brazil. Over relatively dense vegetation covers, a better consistency with MERRA-Land was obtained with ASCAT than with SMOSL3. However, it was found that ASCAT retrievals exhibit negative correlation versus MERRA-Land in some arid regions (e.g., the Sahara and the Arabian Peninsula). In terms of anomalies, SMOSL3 better captures the short term SSM variability of the reference dataset (MERRA-Land) than ASCAT over regions with limited radio frequency interference (RFI) effects (e.g., North America, South America, and Australia). The seasonal and latitudinal variations of SSM are relatively similar for the three products, although the MERRA-Land SSM values are generally higher and their seasonal amplitude is much lower than for SMOSL3 and ASCAT. Both SMOSL3 and ASCAT have relatively comparable triple collocation errors with similar spatial error patterns: (i) lowest errors in arid regions (e.g., Sahara and Arabian Peninsula), due to the very low natural variability of soil moisture in these areas, and Central America, and (ii) highest errors over most of the vegetated regions (e.g., northern Australia, India, central Asia, and South America). However, the ASCAT SSM product is prone to larger random errors in some regions (e.g., north-western Africa, Iran, and southern South Africa). Vegetation density was found to be a key factor to interpret the consistency with MERRA-Land between the two remotely sensed products (SMOSL3 and ASCAT) which provides complementary information on SSM. This study shows that both SMOS and ASCAT have thus a potential for data fusion into long-term data records.
    Remote Sensing of Environment 01/2014; 152:614–626. · 5.10 Impact Factor
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    ABSTRACT: 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.
    IEEE Transactions on Geoscience and Remote Sensing 01/2013; 51(5):3200-3200. · 3.47 Impact Factor
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    ABSTRACT: In this letter, a monofrequent dielectric model for moist soils taking into account dependences on the temperature and texture is proposed, in the case of an electromagnetic frequency equal to 1.4 GHz. The proposed model is deduced from a more general model proposed by Mironov and Fomin (2009) that provides estimations of the complex relative permittivity (CRP) of moist soils as a function of frequency, temperature, moisture, and texture of soils. The latter employs the physical laws of Debye and Clausius-Mossotti and the law of ion conductance to calculate the CRP of water solutions in the soil. The parameters of the respective physical laws were determined by using the CRPs of moist soils measured by Curtis (1995) for a wide ensemble of soil textures (clay content from 0% to 76%), moistures (from drying at 105 °C to nearly saturation), temperatures (10 °C -40 °C), and frequencies (0.3-26.5 GHz). This model has standard deviations of calculated CRPs from the measured values equal to 1.9 and 1.3 for the real and imaginary parts of CRP, respectively. In the model proposed in this letter, the respective standard deviations were decreased to the values of 0.87 and 0.26. In addition, the equations to calculate the complex dielectric permittivity as a function of moisture, temperature, and texture were represented in a simple form of the refractive mixing dielectric model, which is commonly used in the algorithms of radiometric and radar remote sensing to retrieve moisture in the soil.
    IEEE Geoscience and Remote Sensing Letters 01/2013; 10(3):419-423. · 1.82 Impact Factor
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    ABSTRACT: In 2009 and 2010 the L-band microwave Cooperative Airborne Radiometer for Ocean and Land Studies (CAROLS) campaign was performed in southwestern France to support the calibration and validation of the new Soil Moisture and Ocean Salinity (SMOS) satellite mission. The L-band Microwave Emission of the Biosphere (L-MEB) model was used to retrieve surface soil moisture (SSM) and the vegetation optical depth (VOD) from the CAROLS brightness temperature measurements. The CAROLS SSM was compared with in situ observations at 11 sites of the SMOSMANIA (Soil Moisture Observing System-Meteorological Automatic Network Integrated Application) network of Météo-France. For eight of them, significant correlations were observed (0.51 ≤ r ≤ 0.82), with standard deviation of differences ranging from 0.039 m3 m-3 to 0.141 m3 m-3. Also, the CAROLS SSM was compared with SSM values simulated by the A-gs version of the Interactions between Soil, Biosphere and Atmosphere (ISBA-A-gs) model along 20 flight lines, at a resolution of 8 km × 8 km. A significant spatial correlation between these two datasets was observed for all the flights (0.36 ≤ r ≤ 0.85). The CAROLS VOD presented significant spatial correlations with the vegetation water content (VWC) derived from the spatial distribution of vegetation types used in ISBA-A-gs and from the Leaf Area Index (LAI) simulated for low vegetation. On the other hand, the CAROLS VOD presented little temporal changes, and no temporal correlation was observed with the simulated LAI. For low vegetation, the ratio of VOD to VWC tended to decrease, from springtime to summertime. The ISBA-A-gs grid cells (8 km × 8 km) were sampled every 5 m by CAROLS observations, at a spatial resolution of about 2 km. For 83% of the grid cells, the standard deviation of the sub-grid CAROLS SSM was lower than 0.05 m3 m-3. The presence of small water bodies within the ISBA-A-gs grid cells tended to increase the CAROLS SSM spatial variability, up to 0.10 m3 m-3. Also, the grid cells characterised by a high vegetation cover heterogeneity presented higher standard deviation values, for both SSM and VOD.
    Hydrology and Earth System Sciences 06/2012; · 3.59 Impact Factor
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    ABSTRACT: SMOS, successfully launched on November 2, 2009, uses an L Band radiometer with aperture synthesis to achieve a good spatial resolution.. It was developed and made under the leadership of the European Space Agency (ESA) as an Earth Explorer Opportunity mission. It is a joint program with the Centre National d'Etudes Spatiales (CNES) in France and the Centro para el Desarrollo Tecnologico Industrial (CDTI) in Spain. SMOS carries a single payload, an L band 2D interferometric,radiometer in the 1400-1427 MHz protected band. This wavelength penetrates well through the vegetation and with the atmosphere being almost transparent, it enables us to infer both soil moisture and vegetation water content. SMOS achieves an unprecedented spatial resolution of 50 km at L-band maximum (43 km on average) with multi angular-dual polarized (or fully polarized) brightness temperatures over the globe and with a revisit time smaller than 3 days. SMOS is now acquiring data and has undergone the commissioning phase. The data quality exceeds what was expected, showing very good sensitivity and stability. The data is however very much impaired by man made emission in the protected band, leading to degraded measurements in several areas including parts of Europe and China. Many different international teams are now performing cal val activities in various parts of the world, with notably large field campaigns either on the long time scale or over specific targets to address the specific issues. These campaigns take place in various parts of the world and in different environments, from the Antarctic plateau to the deserts, from rain forests to deep oceans. SMOS is a new sensor, making new measurements and paving the way for new applications. It requires a detailed analysis of the data so as to validate both the approach and the quality of the retrievals, and allow for monitoring and the evolution of the sensor. To achieve such goals it is very important to link efficiently ground measurement to satellite measurements through field campaigns and related airborne acquisitions. Comparison with models and other satellite products are necessary. It is in this framework that CESBIO has been involved with many groups to assess the data over many areas in close collaboration. This paper aims at summarising briefly the results (presented in detail in other presentations) to give a general overview and a general first taste of SMOS' performance, together with the identified gaps and next steps to be taken. This presentation could be the general introduction to Cal Val activities.
    EGU 2012; 04/2012
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    ABSTRACT: The SMOS (Soil Moisture and Ocean Salinity) satellite was successfully launched in November 2009. This ESA led mission for Earth Observation is dedicated to provide soil moisture over continental surface (with an accuracy goal of 0.04 m3/m3) and ocean salinity. These two geophysical features are important as they control the energy balance between the surface and the atmosphere. Their knowledge at a global scale is of interest for climatic and weather researches in particular in improving models forecasts. The purpose of this communication is to present the mission results after more than two years in orbit as well as some outstanding results already obtained. A special attention will be devoted to level 2 products. Modeling multi-angular brightness temperatures is not straightforward. The radiative model transfer model L-MEB (L-band Microwave Emission) is used over land while different models with different approaches as to the modeling of sea surface roughness are used over ocean surfaces. Over land the approach is based on semi-empirical relationships, adapted to different type of surface. The model computes a dielectric constant leading to surface emissivity. Surface features (roughness, vegetation) are also considered in the models. However, considering SMOS spatial resolution a wide area is seen by the instrument with strong heterogeneity. The L2 soil moisture retrieval scheme takes this into account. Brightness temperatures are computed for every classes composing a working area. A weighted function is applied for the incidence angle and the antenna beam. Once the brightness temperature is computed for the entire working area, the minimizing process starts. If no soil moisture is derived (not attempted or process failed) a dielectric constant is still derived from an simplified modeled (the cardioid model). SMOS data enabled very quickly to infer Sea surface salinity fields. As salinity retrieval is quite challenging, retrieving it enable to assess very finely the characteristics of the complete system in terms of stability, drift etc. Some anomalies such as the ascending descending temperature differences, temporal drifts or land sea contamination were used to infer issues and improve data quality. The modeling has to account for several perturbing factors 'galactic reflection, sea state, atmospheric path and Faraday rotation etc…as the useful signal is quite small when compared to the perturbing factors impact as well as the instrument sensitivity. Over sea ice several studies showed that it was possible to infer thin ice (first year ice, 50 cm or less) from SMOS measurements. Other studies focused on the Antarctic plateau with also very interesting new results. This presentation will show in detail the SMOS in flight results. The retrieval schemes have been developed to reach science requirements, that is to derive the surface soil moisture over continental surface with an accuracy better than 0,04m3/m3. Over the ocean the goals are not yet satisfied but results are already getting close to the requirements.
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    ABSTRACT: Soil moisture is one of the most important variables regarding climate evolution ans plays a major role in the transfers between the soil and the atmosphere ([1]). Soil moisture needs to be considered as a global variable to improve our global comprehension of the climate. Several approaches have been developed to either model soil moisture or to retrieve it from satellite data. The European Center for Medium range Weather Forecasting (ECMWF) provides global maps of modeled soil moisture but there exists also regional climate models such as SIM, ???. Recently, satellite missions, specially designed for soil moisture monitoring such as the Soil Moisture and Ocean Salinity,(SMOS) have been proposed. SMOS was indeed successfully launched in November 2009 and SMAP (Soil Moisture Active Passive) is scheduled for launch in November 2014. Several algorithms have been created to retrieve soil moisture from higher frequencies measurements obtained from existing satellites such as : SMMR (1978-87), SSM/I (1987), AMSR-E (2004), ERS-ASCAT (1991-2006). Even if their lowest frequencies (5-20 GHz) are not the most suitable for soil moisture retrievals (very sensitive to vegetation growth and atmosphere), it remains a valuable time series from 1979 until now. All these products are obtained at a coarse resolution (typically around 50 km) and it is not always straight-forward to relate them to point measurements for the validation purposes especially at a global scale. It is thus necessary to validate coarse scale soil moisture estimates with model outputs or area representative points. SMOS validation has been performed on a number of sites but it is also necessary to inter-compare with other existing products (satellite products and model outputs) to identify the overall behavior at the global scale. The present paper deals with this topic.
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    ABSTRACT: The studies were designed to ensure correct inclusion of profiles into our model. These promising results will be followed by a validation stage. To do that, we have experimental data sets. We have moisture measurements (with the presence of gradients) and emissivities from the site of SMOSREX (nearly no temperature gradients). On the other hand, we have measurements of high temperature gradients, moisture, emissivity and bi static scattering coefficients from a measurement site in Siberia [8].
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    ABSTRACT: This study investigates the temporal behavior of the gravimetric vegetation water content (Mg) derived from SMOS (L-band) optical depth (τ) values. The analysis is done for the year 2010 over a coniferous forest site in the U.S. Resulting values of Mg are compared to values of leaf water potential obtained with the Soil-Plant-Atmosphere model and in situ data. A significant nonlinear correlation is found between the two (R=0.72, p
    Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International; 01/2012
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    ABSTRACT: The Soil Moisture and Ocean Salinity (SMOS) mission is European Space Agency (ESA's) second Earth Explorer Opportunity mission, launched in November 2009. It is a joint program between ESA Centre National d'Etudes Spatiales (CNES) and Centro para el Desarrollo Tecnologico Industrial. SMOS carries a single payload, an L-Band 2-D interferometric radiometer in the 1400–1427 MHz protected band. This wavelength penetrates well through the atmosphere, and hence the instrument probes the earth surface emissivity. Surface emissivity can then be related to the moisture content in the first few centimeters of soil, and, after some surface roughness and temperature corrections, to the sea surface salinity over ocean. The goal of the level 2 algorithm is thus to deliver global soil moisture (SM) maps with a desired accuracy of 0.04 m3/m3. To reach this goal, a retrieval algorithm was developed and implemented in the ground segment which processes level 1 to level 2 data. Level 1 consists mainly of angular brightness temperatures (TB), while level 2 consists of geophysical products in swath mode, i.e., as acquired by the sensor during a half orbit from pole to pole. In this context, a group of institutes prepared the SMOS algorithm theoretical basis documents to be used to produce the operational algorithm. The principle of the SM retrieval algorithm is based on an iterative approach which aims at minimizing a cost function. The main component of the cost function is given by the sum of the squared weighted differences between measured and modeled TB data, for a variety of incidence angles. The algorithm finds the best set of the parameters, e.g., SM and vegetation characteristics, which drive the direct TB model and minimizes the cost function. The end user Level 2 SM product contains SM, vegetation opacity, and estimated dielectric constant of any surface, TB computed at 42.5 $^{\circ}$, flags and quality indices, and other parameters of interest. This paper gives an overview of the algorithm, discusses the caveats, and provides a glimpse of the Cal Val exercises.
    IEEE Transactions on Geoscience and Remote Sensing 01/2012; 50(5):1384-1403. · 3.47 Impact Factor
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    ABSTRACT: Numerous studies showed the impact of droughts events on the seasonal dynamic of satellite-based vegetation index but validation and relation to ground observations is still lacking. Focusing on the impacts of 2003 and 2011 droughts events, we defined and validated forest health indicators using extensive in-situ damage inventories carried out on all French forests. Analysis of vegetation indices dynamics (EVI, LAI) at the national scale was performed using MODIS and SPOT VEGETATION products (MOD13A2 V5 and CYCLOPES V3.1). Satellite-based indicators of (i) crown condition - which is itself a commonly used forest health indicator - and (ii) leaf phenology anomalies were calibrated and validated. In our study, average of CYCLOPES LAI during the growing season is a good proxi of crown condition (r2=0.79, p
    Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International; 01/2012
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    ABSTRACT: We evaluate a new 3-D numerical modeling approach for calculating the rough-surface scattering and emission of a soil layer. The approach relies on the use of Ansoft's numerical computation software High-Frequency Structure Simulator, which solves Maxwell's equations directly using the finite-element method. The interest of this approach is that it can be easily extended to studies of heterogeneous media. However, before being applied in this way, it must first be validated for the rough-surface case. In this letter, we perform this validation by comparing the results of rough-surface scattering and emission with the results of the method of moments (MoM) for a range of different roughness and permittivity conditions and with both Gaussian and exponential rough-surface autocorrelation functions. For the scattering case, we obtain results that are in agreement with the MoM to within approximately 1-3 dB for angles up to and including 40° and 2-4 dB for angles from 50° to 70°. Agreement for emissivity is to within 3.2 and 3.6 K for low and high roughness conditions, respectively. We then illustrate the application of the new approach by calculating the emission of a two-layer system with rough surfaces, representing the soil-litter system in forests.
    IEEE Geoscience and Remote Sensing Letters 10/2011; · 1.82 Impact Factor
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    ABSTRACT: The Soil Moisture and Ocean Salinity (SMOS) satellite mission, based on an aperture synthesis L-band radiometer was successfully launched in November 2009. In the context of a validation campaign for the SMOS mission, intensive airborne and in situ observations were performed in southwestern France for the SMOS CAL/VAL, from April to May 2009 and from April to July 2010. The CAROLS (Cooperative Airborne Radiometer for Ocean and Land Studies) bi-angular (34°–0°) and dual-polarized (V and H) L-band radiometer was designed, built and installed on board the French ATR-42 research aircraft. During springs of 2009 and 2010, soil moisture observations from the SMOSMANIA (Soil Moisture Observing System–Meteorological Automatic Network Integrated Application) network of Météo-France were complemented by airborne observations of the CAROLS L-band radiometer, following an Atlantic–Mediterranean transect in southwestern France. Additionally to the 12 stations of the SMOSMANIA soil moisture network, in situ measurements were collected in three specific sites within an area representative of a SMOS pixel. Microwave radiometer observations, acquired over southwestern France by the CAROLS instrument were analyzed in order to assess their sensitivity to surface soil moisture (wg). A combination of microwave brightness temperature (Tb) at either two polarizations or two contrasting incidence angles was used to retrieve wg through regressed empirical logarithmic equations with good results, depending on the chosen configuration. The regressions derived from the CAROLS measurements were applied to the SMOS Tb and their retrieval performance was evaluated. The retrievals of wg showed significant correlation (p-value
    Remote Sensing of Environment 07/2011; · 5.10 Impact Factor
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    ABSTRACT: 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 m<sup>3</sup> ·m<sup>-3</sup> and 0.52 kg ·m<sup>-2</sup> , 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.
    IEEE Transactions on Geoscience and Remote Sensing 05/2011; · 3.47 Impact Factor
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    ABSTRACT: The “Cooperative Airborne Radiometer for Ocean and Land Studies” (CAROLS) L-Band radiometer was designed and built as a copy of the EMIRAD II radiometer constructed by the Technical University of Denmark team. It is a fully polarimetric and direct sampling correlation radiometer. It is installed on board a dedicated French ATR42 research aircraft, in conjunction with other airborne instruments (C-Band scatterometer—STORM, the GOLD-RTR GPS system, the infrared CIMEL radiometer and a visible wavelength camera). Following initial laboratory qualifications, three airborne campaigns involving 21 flights were carried out over South West France, the Valencia site and the Bay of Biscay (Atlantic Ocean) in 2007, 2008 and 2009, in coordination with in situ field campaigns. In order to validate the CAROLS data, various aircraft flight patterns and maneuvers were implemented, including straight horizontal flights, circular flights, wing and nose wags over the ocean. Analysis of the first two campaigns in 2007 and 2008 leads us to improve the CAROLS radiometer regarding isolation between channels and filter bandwidth. After implementation of these improvements, results show that the instrument is conforming to specification and is a useful tool for Soil Moisture and Ocean Salinity (SMOS) satellite validation as well as for specific studies on surface soil moisture or ocean salinity.
    Sensors 01/2011; · 2.05 Impact Factor
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    ABSTRACT: The first products derived over France in 2010 from the L-band brightness temperatures (Tb) measured by the SMOS (Soil Moisture and Ocean Salinity) satellite, launched in November 2009, were compared with the surface soil moisture (SSM) estimates produced by the C-band Advanced Scatterometter, ASCAT, launched in 2006 on board METOP-A. SMOS and ASCAT SSM products were compared with the simulations of the ISBA-A-gs model and with in situ measurements from the SMOSMANIA network, including 21 stations located in southern France. ASCAT tended to correlate better than SMOS with ISBA-A-gs. The significant anomaly correlation coefficients between in situ observations and the SMOS (ASCAT) product ranged from 0.23 to 0.48 (0.35 to 0.96). However, in wet conditions, similar results between the two satellite products were found. An attempt was made to derive SSM from regressed empirical logarithmic equations using a combination of SMOS Tb at different incidence angles and different polarizations, and the Leaf Area Index (LAI) modeled by ISBA-A-gs. The analysis of the intercept coefficient of the regression showed an impact of topography. A similar analysis applied to ASCAT and SMOS SSM values showed a more limited impact of topography on the intercept coefficient of the SMOS SSM product, while fewer residual geographic patterns were found for the ASCAT SSM.
    Hydrology and Earth System Sciences Discussions 01/2011; · 3.59 Impact Factor
  • Progress In Electromagnetics Research Symposium (PIERS). 01/2011;
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    ABSTRACT: It is now well understood that data on soil moisture and sea surface salinity (SSS) are required to improve meteorological and climate predictions. These two quantities are not yet available globally or with adequate temporal or spatial sampling. It is recognized that a spaceborne L-band radiometer with a suitable antenna is the most promising way of fulfilling this gap. With these scientific objectives and technical solution at the heart of a proposed mission concept the European Space Agency (ESA) selected the Soil Moisture and Ocean Salinity (SMOS) mission as its second Earth Explorer Opportunity Mission. The development of the SMOS mission was led by ESA in collaboration with the Centre National d'Etudes Spatiales (CNES) in France and the Centro para el Desarrollo Tecnologico Industrial (CDTI) in Spain. SMOS carries a single payload, an L-Band 2-D interferometric radiometer operating in the 1400–1427-MHz protected band [1]. The instrument receives the radiation emitted from Earth's surface, which can then be related to the moisture content in the first few centimeters of soil over land, and to salinity in the surface waters of the oceans. SMOS will achieve an unprecedented maximum spatial resolution of 50 km at L-band over land (43 km on average over the field of view), providing multiangular dual polarized (or fully polarized) brightness temperatures over the globe. SMOS has a revisit time of less than 3 days so as to retrieve soil moisture and ocean salinity data, meeting the mission's science objectives. The caveat in relation to its sampling requirements is that SMOS will have a somewhat reduced sensitivity when compared to conventional radiometers. The SMOS satellite was launched successfully on November 2, 2009.
    Proceedings of the IEEE 06/2010; · 6.91 Impact Factor
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    ABSTRACT: ESA's Soil Moisture and Ocean Salinity (SMOS) mission, successfully launched in November, 2009, acquires brightness temperatures relying on an L-band (1.4 GHz) interferometric radiometer. Within the context of the preparation for this mission over land, the Valencia Anchor Station (VAS) experimental site, in Spain, was selected to be one of the main test sites in Europe for the SMOS Calibration/Validation (Cal/Val) activities. It is a semiarid environment with low annual precipitation (around 400mm) and is characterized by an extensive network of measurements in the atmosphere and in the soil. The objective of this research is to propose a parametrization of a radiative transfer model in order to simulate the passive microwave brightness temperature at SMOS scale (an average of 50km²) at three different bands: L-band (1.4 GHz), C-band (6.7 GHz) and X-band (10.9 GHz). In this framework, a coupled SVAT (Soil-Vegetation-Atmosphere-Transfer) - radiative transfer model was considered for modelling the soil moisture and the resulting microwave emission. The hydrological processes are simulated using a SVAT model named ISBA (Interactions between Soil Biosphere Atmosphere), while the microwave emission is simulated using the L-MEB (L-band Microwave Emission of the Biosphere) model. L-MEB is adapted regarding the surface features of VAS area and is computed using the new parametrisation in order to simulate brightness temperature at L, C and X-band. The results obtained were compared with remote sensing data from SMOS and AMSR-E (Advanced Microwave Scanning Radiometer of the Earth Observing System (EOS)). A very high correlation coefficient (more than 0.90) is obtained when comparing with AMSR-E data at C and X-band. This method allows simulating the brightness temperature at different frequencies for a wide area and is of first interests as passive sensors (SMOS, AMSR-E) have a large footprint (several tens of km) so to better understand the signal is interesting to focus over large areas.
    04/2010; 12:12602.

Publication Stats

2k Citations
207.86 Total Impact Points


  • 1999–2013
    • French National Institute for Agricultural Research
      • Ecologie Fonctionnelle et Physique de l'Environnement (EPHYSE)
      Lutetia Parisorum, Île-de-France, France
  • 2010
    • Université Bordeaux 1
      Talence, Aquitaine, France
  • 2009
    • Chinese Academy of Sciences
      Peping, Beijing, China
  • 2007–2009
    • University of Cambridge
      • Department of Geography
      Cambridge, ENG, United Kingdom
  • 2003–2009
    • VU University Amsterdam
      • Department of Hydrology and Geo-environmental Sciences
      Amsterdam, North Holland, Netherlands
  • 2001–2009
    • Centre D'Etudes Spatiales De La Biosphere
      Tolosa de Llenguadoc, Midi-Pyrénées, France
    • National Central University
      • Center for Space and Remote Sensing Research
      Taoyuan City, Taiwan, Taiwan
  • 2008
    • Institut Pierre Simon Laplace
      Lutetia Parisorum, Île-de-France, France
  • 2007–2008
    • European Center For Medium Range Weather Forecasts
      Shinfield, England, United Kingdom
  • 1995–2007
    • Météo-France
      Lutetia Parisorum, Île-de-France, France
  • 2006
    • Beijing Normal University
      • State Key Laboratory of Remote Sensing Sciences
      Peping, Beijing, China
    • French National Centre for Scientific Research
      • Laboratoire d'étude des transferts en hydrologie et environnement (LTHE)
      Paris, Ile-de-France, France
  • 1999–2006
    • University of Rome Tor Vergata
      • Facoltà di Ingegneria
      Roma, Latium, Italy
  • 2002
      Bremen, Bremen, Germany