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Remote Sens. 2010, 2(5), 1273-1286; doi:10.3390/rs2051273
Article

Sensitivity Analysis of b-factor in Microwave Emission Model for Soil Moisture Retrieval: A Case Study for SMAP Mission

* ,
 and
NOAA-Cooperative Remote Sensing Science & Technology Center (NOAA-CREST), City University of New York, NY 10031, USA
* Author to whom correspondence should be addressed.
Received: 10 February 2010 / Revised: 28 April 2010 / Accepted: 29 April 2010 / Published: 4 May 2010
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Abstract

Sensitivity analysis is critically needed to better understand the microwave emission model for soil moisture retrieval using passive microwave remote sensing data. The vegetation b-factor along with vegetation water content and surface characteristics has significant impact in model prediction. This study evaluates the sensitivity of the b-factor, which is function of vegetation type. The analysis is carried out using Passive and Active L and S-band airborne sensor (PALS) and measured field soil moisture from Southern Great Plains experiment (SGP99). The results show that the relative sensitivity of the b-factor is 86% in wet soil condition and 88% in high vegetated condition compared to the sensitivity of the soil moisture. Apparently, the b-factor is found to be more sensitive than the vegetation water content, surface roughness and surface temperature; therefore, the effect of the b-factor is fairly large to the microwave emission in certain conditions. Understanding the dependence of the b-factor on the soil and vegetation is important in studying the soil moisture retrieval algorithm, which can lead to potential improvements in model development for the Soil Moisture Active-Passive (SMAP) mission.
Keywords: soil moisture; passive microwave; L-band; b-factor soil moisture; passive microwave; L-band; b-factor
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).
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Seo, D.; Lakhankar, T.; Khanbilvardi, R. Sensitivity Analysis of b-factor in Microwave Emission Model for Soil Moisture Retrieval: A Case Study for SMAP Mission. Remote Sens. 2010, 2, 1273-1286.

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