The SMOS Soil Moisture Retrieval Algorithm
Yann Kerr,Philippe Waldteufel,P. Richaume,Jean-Pierre Wigneron,Paolo Ferrazzoli,A. Mahmoodi,Ahmad Al Bitar,Francois Cabot,C. Gruhier,S. Juglea,Delphine Leroux,Arnaud Mialon,Steven Delwart +12 more
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TLDR
A retrieval algorithm to deliver global soil moisture (SM) maps with a desired accuracy of 0.04 m3/m3 is given, discusses the caveats, and provides a glimpse of the Cal Val exercises.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°, 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.read more
Citations
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Journal ArticleDOI
Land Geoparcel-Based Spatial Downscaling for the Microwave Remotely Sensed Soil Moisture Product
TL;DR: In this paper , a land geoparcel-based spatial downscaling technique for the Soil Moisture Active Passive (SMAP) satellite products is developed by combining XGBoost (eXtreme Gradient Boosting) machine learning algorithm with the support of geo-vector vector data and a variety of auxiliary raster data.
Book ChapterDOI
Mapping and Monitoring of Soil Moisture, Evapotranspiration, and Agricultural Drought
TL;DR: In this paper, three distinct proven methods to estimate soil moisture, ET, and agricultural drought using satellite and ancillary data are introduced, and then, some example maps and their validation results against the ground truth will be presented.
Proceedings ArticleDOI
Seasonal Analysis of Surface Soil Moisture Dry-Downs in a Land-Atmosphere Hotspot as Seen by LSM and Satellite Products
TL;DR: A seasonal analysis of temporal e-folding decay of surface soil moisture dry-downs using ORCHIDEE land surface model and SMOS observations over South Eastern South America shows that the soil drying process depends on both location and season, and that the modeled drying velocity is faster than the observed one, even when modeled data is sampled at the same frequency as the observations.
Proceedings ArticleDOI
Analysis of soil moisture retrieval from airborne passive/active L-band sensor measurements in SMAPVEX 2012
TL;DR: In this article, the authors focused on analyzing the Passive/Active L-band Sensor observations of sites covered during the Soil Moisture Validation Experiment 2012 (SMAPVEX12) and analyzed the observed data, parameterizing vegetation covered surface model, modeling inversion algorithm and analyzing observed soil moisture changes over the time period of six weeks.
Proceedings ArticleDOI
Intercomparison of Multiply Soil Surface Roughness Data Sets Over the Tibetan Plateau
Menglei Han,Hui Lu,Kun Yang +2 more
TL;DR: Since similar surface roughness parameterization and values were adopted in SMOS and SMAP algorithm, their soil moisture products show consistent spatiotemporal pattern, which could benefit the merging of various soil moisture Products across different sensors and platforms.
References
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Book
Microwave Remote Sensing, Active and Passive
TL;DR: In this article, the authors present a model of a MICROWAVE REMOTE SENSING FUNDAMENTALS and RADIOMETRY, which is based on the idea of surface scattering.
Journal ArticleDOI
The Soil Moisture Active Passive (SMAP) Mission
Dara Entekhabi,Eni G. Njoku,Peggy O'Neill,Kent Kellogg,Wade T. Crow,W. Edelstein,Jared Entin,Shawn D Goodman,Thomas J. Jackson,Joel T. Johnson,John S. Kimball,Jeffrey R. Piepmeier,Randal D. Koster,Neil R.W. Martin,Kyle C. McDonald,Mahta Moghaddam,Susan Moran,Rolf H. Reichle,Jiancheng Shi,Michael W. Spencer,Samuel W Thurman,Leung Tsang,Jakob van Zyl +22 more
TL;DR: The Soil Moisture Active Passive mission is one of the first Earth observation satellites being developed by NASA in response to the National Research Council's Decadal Survey to make global measurements of the soil moisture present at the Earth's land surface.
Journal ArticleDOI
Microwave Dielectric Behavior of Wet Soil-Part II: Dielectric Mixing Models
TL;DR: In this paper, the authors evaluated the microwave dielectric behavior of soil-water mixtures as a function of water content and soil textural composition for the 1.4-to 18-GHz region.
Journal ArticleDOI
The SMOS Mission: New Tool for Monitoring Key Elements ofthe Global Water Cycle
Yann Kerr,Philippe Waldteufel,Jean-Pierre Wigneron,Steven Delwart,Francois Cabot,Jacqueline Boutin,Maria-José Escorihuela,Jordi Font,Nicolas Reul,C. Gruhier,S. Juglea,Mark R. Drinkwater,Achim Hahne,Manuel Martin-Neira,Susanne Mecklenburg +14 more
TL;DR: The SMOS satellite was launched successfully on November 2, 2009, and 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.
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The Soil Moisture Active Passive (SMAP) Mission
Dara Entekhabi,Eni G. Njoku,Peggy O'Neill,Kent Kellogg,Wade T. Crow,W. Edelstein,Jared Entin,Shawn D Goodman,Thomas J. Jackson,Joel T. Johnson,John S. Kimball,Jeffrey R. Piepmeier,Randal D. Koster,Neil R.W. Martin,Kyle C. McDonald,Mahta Moghaddam,Susan Moran,Rolf H. Reichle,Jiancheng Shi,Michael W. Spencer,Samuel W Thurman,Leung Tsang,Jakob van Zyl +22 more