SMOS L1 processor prototype: From digital counts to brightness temperatures

Gutierrez, Antonio P.; Barbosa, José; Almeida, N.; Catarino, Nuno; Freitas, Jose Cabrita A.; Ventura, M. A.; Reis, J.

doi:10.1109/igarss.2007.4423631

Cited by 10 publications

(3 citation statements)

References 12 publications

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“…Maximum spatial coverage is achieved at a viewing angle of 42.5°, while the spatial resolution is 3565 kilometers [24]. Conversion of TBr values from the coordinate system associated with the antenna (TX and TY) to the coordinate system associated with the earth's surface (TH and TV)the so-called "rotation" of the polarization vectoris carried out according to standard SMOS algorithms [24] using the SMOS-BOX package version 5.8.1 in the SNAP software environment. SMOS L1C data is referenced to the discrete geodetic grid DGG ISEA 4H9.…”

Section: Satellite Data and Phenological Phases Of Water Bodiesmentioning

confidence: 99%

Phenological Phases of Water Bodies in the Boreal and Subarctic Zone of the Northern Hemisphere According to SMOS Satellite Data and Their Relationship with the Seasonal Dynamics of CO2 Concentration in the Atmosphere

Tikhonov,

Ermakov,

Pashinov

et al. 2023

Preprint

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This paper presents the results of a comparison of the seasonal dynamics of carbon dioxide content in the atmosphere and the phenological phases of various water bodies located in the boreal and subarctic zones for 2012–2020. Six large freshwater areas were selected as research objects: Lake Baikal, Lake Ladoga, Gulf of Ob, Lake Huron, Great Bear Lake and Great Slave Lake. In addition, four areas of wetlands in Western Siberia were studied. The CO2 concentration in the air column over water bodies was obtained from CAMS global greenhouse gas reanalysis data. These data represent three-dimensional fields of aerosols and chemical components in the atmosphere, with complete coverage of the globe. The phenological phases of the water bodies were determined using data from the MIRAS microwave radiometer of the SMOS satellite. The comparison and analysis performed showed that the concentration of CO2 in the atmosphere over the studied water bodies has a seasonal cyclical nature. The minimum concentration corresponds to the summer period due to strong photosynthesis of phytoplankton and swamp vegetation, which results in the absorption of carbon dioxide. The maximum CO2 concentration over the water bodies corresponds to the end of the winter – the beginning of the spring period, when photosynthesis processes are minimal. During this period, CO2 is being accumulated in water bodies and subsequently emitted. In freezing lakes located in the boreal zone, in addition to a stable spring maximum of CO2, a strong short-term release of carbon dioxide is sometimes observed, also corresponding to the stage of destruction of the ice cover. It is associated with the release of CO2 accumulated over the winter period, which was “sealed” in the ice and in the water column under the ice. The absence of such a release in the waters of the subarctic zone is explained by the lower biological productivity of these reservoirs compared to the waters of the boreal zone.

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Section: Satellite Data and Phenological Phases Of Water Bodiesmentioning

confidence: 99%

Phenological Phases of Water Bodies in the Boreal and Subarctic Zone of the Northern Hemisphere According to SMOS Satellite Data and Their Relationship with the Seasonal Dynamics of CO2 Concentration in the Atmosphere

Tikhonov,

Ermakov,

Pashinov

et al. 2023

Preprint

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“…Among these sources of brightness, we can distinguish the direct Sky, Sun, and Moon radiations, as well as the reflected Sun radiations (Sun glint) [5]. This article focuses only on the impact of the direct solar radiations on the retrieved images.…”

Section: Introductionmentioning

confidence: 99%

A New Direct Sun Correction Algorithm for the Soil Moisture and Ocean Salinity Space Mission

Khazâal

Cabot

Anterrieu

et al. 2020

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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The interferometric measurements provided by the Soil Moisture and Ocean Salinity (SMOS) satellite are contaminated by solar radiations due to a quasi-permanent presence of the Sun in the field of view of the instrument. A correction algorithm is developed and implemented in the SMOS image reconstruction processor to remove the contribution of these radiations. Since the Sun is seen under an angle much smaller than the angular resolution of SMOS, this algorithm assimilates the Sun disc to a single source located at its center. However, strong residuals persist in the retrieved images mainly due to the presence of different distributed smaller sources of brightness in the Sun disc. Thus, the performance of the algorithm degrades rapidly as soon as the dominant source is far from the center of the disc. This behavior shows the limitation of the algorithm and its strong dependencies to the position of the Sun. In this article, we propose two other algorithms to account for the solar radiations. The first one is an iterative optimization algorithm based on estimating the position of the dominant source of brightness inside the Sun disc. The second algorithm is based on estimating the contribution of the different sources of brightness within the Sun disc using an oversampled grid by solving a constrained least square optimization problem with an explicit solution.

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“…MTS has been extensively used during the on-ground characterization of the instrument to assess the MIRAS instrument performance. Besides, it has also been used to assess the operation of the payload during the first months after launch and to cross-validate and consolidate the products up to level 1A provided by the official L1 Processor Prototype (L1PP) developed by Deimos Enginheria (Portugal) [17].…”

Section: Instrument Calibrationmentioning

confidence: 99%

Review of the CALIMAS Team Contributions to European Space Agency’s Soil Moisture and Ocean Salinity Mission Calibration and Validation

et al. 2012

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This work summarizes the activities carried out by the SMOS (Soil Moisture and Ocean Salinity) Barcelona Expert Center (SMOS-BEC) team in conjunction with the CIALE/Universidad de Salamanca team, within the framework of the European Space Agency (ESA) CALIMAS project in preparation for the SMOS mission and during its first year of operation. Under these activities several studies were performed, ranging from Level 1 (calibration and image reconstruction) to Level 4 (land pixel disaggregation techniques, by means of data fusion with higher resolution data from optical/infrared sensors). Validation of SMOS salinity products by means of surface drifters developed ad-hoc, and soil moisture products over the REMEDHUS site (Zamora, Spain) are also presented. Results of other preparatory activities carried out to improve the performance of eventual SMOS follow-on missions are presented, including GNSS-R to infer the sea state correction needed for improved ocean salinity retrievals and land surface parameters. Results from CALIMAS show a satisfactory performance of the MIRAS instrument, the accuracy and efficiency of the algorithms implemented in the ground data processors, and explore the limits of spatial resolution of soil moisture products using data fusion, as well as the feasibility of GNSS-R techniques for sea state determination and soil moisture monitoring.

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SMOS L1 processor prototype: From digital counts to brightness temperatures

Cited by 10 publications

References 12 publications

Phenological Phases of Water Bodies in the Boreal and Subarctic Zone of the Northern Hemisphere According to SMOS Satellite Data and Their Relationship with the Seasonal Dynamics of CO2 Concentration in the Atmosphere

Phenological Phases of Water Bodies in the Boreal and Subarctic Zone of the Northern Hemisphere According to SMOS Satellite Data and Their Relationship with the Seasonal Dynamics of CO2 Concentration in the Atmosphere

A New Direct Sun Correction Algorithm for the Soil Moisture and Ocean Salinity Space Mission

Review of the CALIMAS Team Contributions to European Space Agency’s Soil Moisture and Ocean Salinity Mission Calibration and Validation

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