An approach to constructing a homogeneous time series of soil moisture using SMOS

Delphine J. Leroux, Yann H. Kerr, Eric F. Wood, Alok K. Sahoo, Rajat Bindlish, Thomas J. Jackson

Research output: Contribution to journalArticlepeer-review

20 Scopus citations


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.

Original languageEnglish (US)
Article number6472062
Pages (from-to)393-405
Number of pages13
JournalIEEE Transactions on Geoscience and Remote Sensing
Issue number1
StatePublished - Jan 2014

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • General Earth and Planetary Sciences


  • Advanced Microwave Scanning Radiometer- Earth Observing System (AMSR-E)
  • Copulas
  • Cumulative density function (CDF) matching
  • Soil Moisture and Ocean Salinity (SMOS)
  • Soil moisture
  • Time series


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