DocumentCode :
75273
Title :
An Approach to Constructing a Homogeneous Time Series of Soil Moisture Using SMOS
Author :
Leroux, Delphine J. ; Kerr, Yann H. ; Wood, Eric F. ; Sahoo, Abhaya Kumar ; Bindlish, Rajat ; Jackson, Thomas J.
Author_Institution :
Jet Propulsion Lab., California Inst. of Technol., Pasadena, CA, USA
Volume :
52
Issue :
1
fYear :
2014
fDate :
Jan. 2014
Firstpage :
393
Lastpage :
405
Abstract :
Overlapping soil moisture time series derived from two satellite microwave radiometers (the Soil Moisture and Ocean Salinity (SMOS) and the Advanced Microwave Scanning Radiometer-Earth Observing System) are used to generate a soil moisture time series from 2003 to 2010. Two statistical methodologies for generating long homogeneous time series of soil moisture are considered. Generated soil moisture time series using only morning satellite overpasses are compared to ground measurements from four watersheds in the U.S. with different climatologies. The two methods, cumulative density function (CDF) matching and copulas, are based on the same statistical theory, but the first makes the assumption that the two data sets are ordered the same way, which is not needed by the second. Both methods are calibrated in 2010, and the calibrated parameters are applied to the soil moisture data from 2003 to 2009. Results from these two methods compare well with ground measurements. However, CDF matching improves the correlation, whereas copulas improve the root-mean-square error.
Keywords :
moisture; remote sensing; soil; AD 2003 to 2010; Advanced Microwave Scanning Radiometer; Earth Observing System; SMOS; cumulative density function; homogeneous time series; ocean salinity; root-mean-square error; satellite microwave radiometers; soil moisture; Correlation; Meteorology; Microwave radiometry; Satellites; Sensors; Soil moisture; Time series analysis; Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E); Soil Moisture and Ocean Salinity (SMOS); copulas; cumulative density function (CDF) matching; soil moisture; time series;
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
Publisher :
ieee
ISSN :
0196-2892
Type :
jour
DOI :
10.1109/TGRS.2013.2240691
Filename :
6472062
Link To Document :
بازگشت