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Journal ArticleDOI

Assessment of the SMAP Passive Soil Moisture Product

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TLDR
The Level 2 Passive Soil Moisture Product (L2_SM_P) as discussed by the authors was developed by the National Aeronautics and Space Administration (NASA) soil moisture active passive (SMAP) satellite mission and is available from the Distributed Active Archive Center at the National Snow and Ice Data Center.
Abstract
The National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) satellite mission was launched on January 31, 2015. The observatory was developed to provide global mapping of high-resolution soil moisture and freeze-thaw state every two to three days using an L-band (active) radar and an L-band (passive) radiometer. After an irrecoverable hardware failure of the radar on July 7, 2015, the radiometer-only soil moisture product became the only operational soil moisture product for SMAP. The product provides soil moisture estimates posted on a 36 km Earth-fixed grid produced using brightness temperature observations from descending passes. Within months after the commissioning of the SMAP radiometer, the product was assessed to have attained preliminary (beta) science quality, and data were released to the public for evaluation in September 2015. The product is available from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center. This paper provides a summary of the Level 2 Passive Soil Moisture Product (L2_SM_P) and its validation against in situ ground measurements collected from different data sources. Initial in situ comparisons conducted between March 31, 2015 and October 26, 2015, at a limited number of core validation sites (CVSs) and several hundred sparse network points, indicate that the V-pol Single Channel Algorithm (SCA-V) currently delivers the best performance among algorithms considered for L2_SM_P, based on several metrics. The accuracy of the soil moisture retrievals averaged over the CVSs was 0.038 m3/m3 unbiased root-mean-square difference (ubRMSD), which approaches the SMAP mission requirement of 0.040 m3/m3.

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Citations
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Journal ArticleDOI

Validation of SMAP surface soil moisture products with core validation sites

TL;DR: The NASA Soil Moisture Active Passive (SMAP) mission has utilized a set of core validation sites as the primary methodology in assessing the soil moisture retrieval algorithm performance as mentioned in this paper.
Journal ArticleDOI

The global distribution and dynamics of surface soil moisture

TL;DR: In this article, the authors introduce a metric of soil moisture memory and use a full year of global observations from NASA's Soil Moisture Active Passive mission to show that surface soil moisture, a storage believed to make up less than 0.001% of the global freshwater budget by volume, and equivalent to an, on average, 8mm thin layer of water covering all land surfaces.
Journal ArticleDOI

Ground, Proximal, and Satellite Remote Sensing of Soil Moisture

TL;DR: Soil moisture (SM) is a key hydrologic state variable that is of significant importance for numerous Earth and environmental science applications that directly impact the global environment and human society.
Journal ArticleDOI

Development and assessment of the SMAP enhanced passive soil moisture product

TL;DR: This article covers the development and assessment of the SMAP Level 2 Enhanced Passive Soil Moisture Product (L2_SM_P_E) and affirmed that the Single Channel Algorithm using the V-polarized TB channel (SCA-V) delivered the best retrieval performance among the various algorithms implemented for L2-SM-P, a result similar to a previous assessment.
References
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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.
Reference EntryDOI

Microwave Remote Sensing

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An Empirical Model for the Complex Dielectric Permittivity of Soils as a Function of Water Content

TL;DR: In this paper, a simple empirical model was proposed to describe the dielectric behavior of the soil-water mixtures and the model employed the mixing of either the Dielectric constants or the refraction indices of ice, water, rock and air, and treated the transition moisture value as an adjustable parameter.
Journal ArticleDOI

The SMOS Soil Moisture Retrieval Algorithm

TL;DR: 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.
Journal ArticleDOI

A methodology for surface soil moisture and vegetation optical depth retrieval using the microwave polarization difference index

TL;DR: The methodology uses a radiative transfer model to solve for surface soil moisture and vegetation optical depth simultaneously using a nonlinear iterative optimization procedure and does not require any field observations of soil moisture or canopy biophysical properties for calibration purposes and may be applied to other wavelengths.
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