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
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Journal ArticleDOI
Multiyear monitoring of soil moisture over Iran through satellite and reanalysis soil moisture products
TL;DR: The Standardized Soil Moisture Index (SSI) calculated from ERA-Interim, ERA-I/Land and ESA CCI SM datasets showed that the Center and Southeast regions suffered from the most severe and longest-lasting drought events in the last decade.
Journal ArticleDOI
Estimating surface soil moisture from satellite observations using a generalized regression neural network trained on sparse ground-based measurements in the continental U.S
TL;DR: In this paper, a point-surface collaborative inversion (PSCI) method was developed for the estimation of regional surface soil moisture (SSM) using a generalized regression neural network (GRNN) trained on sparse ground-based measurements.
Journal ArticleDOI
Monitoring agricultural drought in Australia using MTSAT-2 land surface temperature retrievals
Tian Hu,Tian Hu,Tian Hu,Luigi J. Renzullo,Albert van Dijk,Jie He,Siyuan Tian,Zhihong Xu,Jun Zhou,Tengjiao Liu,Tengjiao Liu,Qinhuo Liu +11 more
TL;DR: The temperature rise index (TRI) as discussed by the authors measures the anomaly of the intrinsic morning rise of the LST and is used for early warning of agricultural droughts in Australia.
Journal ArticleDOI
Earth Observation-Based Operational Estimation of Soil Moisture and Evapotranspiration for Agricultural Crops in Support of Sustainable Water Management
TL;DR: In this article, the state of the art in the use specifically of operational EO of both evapotranspiration (ET) rates and surface soil moisture (SSM) estimates is reviewed.
Journal ArticleDOI
Using multi-satellite microwave remote sensing observations for retrieval of daily surface soil moisture across China
Ke Zhang,Lijun Chao,Qing-qing Wang,Ying-chun Huang,Rong-hua Liu,Yang Hong,Tu Yong,Wei Qu,Jinyin Ye +8 more
TL;DR: In this article, a single-channel brightness radiometric algorithm was applied to estimate soil moisture from the respective brightness temperature observations of the SMAP, SMOS, AMSR2, FY3B, and FY3C satellites on the same day and then produced a daily composite dataset by averaging the individual satellite-retrieved soil moisture.
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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