Paper Info
Title
Calibration of SMOS Soil Moisture Retrieval Algorithm: A Case of Tropical Site in Malaysia
Abstract
Soil Moisture and Ocean Salinity (SMOS) mission has successfully contributed to global soil moisture products since 2009. Validation and calibration activities were conducted worldwide, yet some of the validation results do not fulfill the targeted accuracy of ±0.04 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{m}^{3}\text{m}^{-3}$ </tex-math></inline-formula> . This paper presented the site-specific calibration of the V620 retrieval algorithm with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</italic> data collected at selected agricultural sites in the humid tropical regions, Malaysia. This set of data has been validated where low accuracy of SMOS soil moisture products was found. To improve the SMOS soil moisture retrieval, calibration of SMOS soil moisture retrieval algorithm based on the L-band Microwave Emission and Biosphere model and SMOS Level 1C <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{T}_{\mathrm {B}}$ </tex-math></inline-formula> products, considering the local parameters was conducted. The calibration proves that these site-specific parameters improve the product’s accuracy. Validation of SMOS Level 2 product with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</italic> data showed bias, root-mean-square error (RMSE), and unbiased RMSE (ubRMSE) ranging from 0.050 to 0.118 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{m}^{3}\text{m}^{-3}$ </tex-math></inline-formula> , 0.068 to 0.142 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{m}^{3}\text{m}^{-3}$ </tex-math></inline-formula> , and 0.069 to 0.103 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{m}^{3}\text{m}^{-3}$ </tex-math></inline-formula> , respectively. The soil moisture retrieval based on the calibrated model showed an improved bias of 0.020–0.056 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{m}^{3}\text {m}^{-3}$ </tex-math></inline-formula> and RMSE of 0.026–0.065 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{m}^{3}\text{m}^{-3}$ </tex-math></inline-formula> . The ubRMSE ranges from 0.017 to 0.034 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{m}^{3}\text{m}^{-3}$ </tex-math></inline-formula> . Recently released SMOS-IC V105 product was also validated, where small improvements were noticed when compared to the accuracy of SMOS Level 2. This paper shows the importance of local parameters in retrieving soil moisture with higher accuracy compared to the use of global generalized parameters that are used in the original SMOS soil moisture retrieval algorithm.
Year
DOI
Venue
2019
10.1109/TGRS.2018.2888535
IEEE Transactions on Geoscience and Remote Sensing
Keywords
Field
DocType
Soil moisture,Moisture,Calibration,Vegetation mapping,Optical sensors
Remote sensing,Microwave emission,Mean squared error,Salinity,Water content,Retrieval algorithm,Mathematics,Calibration,Biosphere model
Journal
Volume
Issue
ISSN
57
6
0196-2892
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Chuen Siang Kang101.35
Kasturi Devi Kanniah253.84
Yann Kerr313630.53