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Proceedings Paper

Analysis of soil moisture retrieval from airborne passive/active L-band sensor measurements in SMAPVEX 2012
Author(s): Liang Chen; Hongting Song; Lei Tan; Yinan Li; Hao Li
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Paper Abstract

Soil moisture is a key component in the hydrologic cycle and climate system. It is an important input parameter for many hydrologic and meteorological models. NASA’S upcoming Soil Moisture Active Passive (SMAP) mission, to be launched in October 2014, will address this need by utilizing passive and active microwave measurements at L-band, which will penetrate moderately dense canopies. In preparation for the SMAP mission, the Soil Moisture Validation Experiment 2012 (SMAPVEX12) was conducted from 6 June to 17 July 2012 in the Carment-Elm Creek area in Manitoba, Canada. Over a period of six weeks diverse land cover types ranging from agriculture over pasture and grassland to forested sites were re-visited several times a week. The Passive/Active L-band Sensor (PALS) provides radiometer products, vertically and horizontally polarized brightness temperatures, and radar products. Over the past two decades, successful estimation of soil moisture has been accomplished using passive and active L-band data. However, remaining uncertainties related to surface roughness and the absorption, scattering, and emission by vegetation must be resolved before soil moisture retrieval algorithms can be applied with known and acceptable accuracy using satellite observations. This work focuses on analyzing the Passive/Active L-band Sensor observations of sites covered during SMAPVEX12, investigating the observed data, parameterizing vegetation covered surface model, modeling inversion algorithm and analyzing observed soil moisture changes over the time period of six weeks. The data and analysis results from this study are aimed at increasing the accuracy and range of validity of SMAP soil moisture retrievals via enhancing the accuracy for soil moisture retrieval.

Paper Details

Date Published: 8 November 2014
PDF: 6 pages
Proc. SPIE 9260, Land Surface Remote Sensing II, 92600S (8 November 2014); doi: 10.1117/12.2071225
Show Author Affiliations
Liang Chen, China Academy of Space Technology (China)
Hongting Song, China Academy of Space Technology (China)
Lei Tan, Beijing Nomal Univ. (China)
Yinan Li, China Academy of Space Technology (China)
Hao Li, China Academy of Space Technology (China)


Published in SPIE Proceedings Vol. 9260:
Land Surface Remote Sensing II
Thomas J. Jackson; Jing Ming Chen; Peng Gong; Shunlin Liang, Editor(s)

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