Paper Info
Title
Merging two passive microwave remote sensing (SMOS and AMSR_E) datasets to produce a long term record of Soil Moisture
Abstract
This study investigated the use of physically based statistical regressions to retrieve a global and long term (e.g. 2003-2014) surface soil moisture (SSM) record based on a combination of passive microwave remote sensing observations from the Advanced Microwave Scanning Radiometer (AMSR-E; 2003-Sept. 2011) and the Soil Moisture and Ocean Salinity (SMOS; 2010-2014) sensors. Statistical regression methods based on bi-polarization (horizontal and vertical) brightness temperatures (Tb) observations obtained from AMSR-E. The coefficients of these regression equations were calibrated using SMOS level 3 SSM maps (SMOSL3) as a reference. This calibration process was carried out over the June 2010-Sept. 2011 period, over which both SMOS and AMSR-E observations coincide. Based on these calibrated coefficients global SSM maps could be computed from the AMSR-E Tb observations over the whole 2003-2011 period. In this study, the SSM maps were successfully evaluated against the SMOSL3 SSM products over the period of calibration (Jun. 2010-Sept. 2011). Correlations (R) and Root Mean Square Error (RMSE) were computed between the AMSR-E retrievals and the reference (SMOSL3) SSM products. The R (mostly > 0.75) and RMSE (mostly <; 0.04 m3/m3) maps showed a good agreement between the retrieved and SMOSL3 SSM products particularly over Australia, central USA, central Asia, and the Sahel. In conclusion, the statistical regression method is capable of retrieving a coherent "SMOS-AMSR-E" SSM time series for the period 2003-2014.
Year
DOI
Venue
2014
10.1109/IGARSS.2014.6946922
IGARSS
Keywords
Field
DocType
passive microwave remote sensing merging,amsr-e,remote sensing,ssm record,smos datasets,moisture,rmse,ad 2003 to 2014,bipolarization,regression analysis,central asia,central usa,statistical regressions,sahel,statistical regression methods,horizontal brightness temperatures,regression analyses,australia,soil moisture,long term record,vertical brightness temperatures,advanced microwave scanning radiometer,ssm maps,radiometers,amsr_e datasets,brightness,root mean square error,calibration process,soil,smos level 3,smos,regression equations,mean square error methods,soil moisture and ocean salinity,mathematical model
Meteorology,Microwave remote sensing,Computer science,Remote sensing,Water content,Merge (version control)
Conference
ISSN
Citations 
PageRank 
2153-6996
0
0.34
References 
Authors
5
12
Name
Order
Citations
PageRank
A. Al-Yaari100.34
Jean-Pierre Wigneron272077.00
A. Ducharne311.71
Yann Kerr413630.53
Patricia de Rosnay517523.79
richard de jeu69817.89
Ajit Govind700.34
Ahmad Al Bitar826126.44
Clement Albergel9153.92
Joaquín Munoz Sabater10184.66
Philippe Richaume1126930.37
Arnaud Mialon1226626.28