Publications des scientifiques de l'IRD

Jackson T.J., Bindlish R., Cosh M.H., Zhao T.J., Starks P.J., Bosch D.D., Seyfried M., Moran M.S., Goodrich D.C., Kerr Yann, Leroux D. (2012). Validation of Soil Moisture and Ocean Salinity (SMOS) Soil Moisture Over Watershed Networks in the U.S. IEEE Transactions on Geoscience and Remote Sensing, 50 (5), p. 1530-1543. ISSN 0196-2892.

Titre du document
Validation of Soil Moisture and Ocean Salinity (SMOS) Soil Moisture Over Watershed Networks in the U.S
Année de publication
2012
Type de document
Article référencé dans le Web of Science WOS:000303205200016
Auteurs
Jackson T.J., Bindlish R., Cosh M.H., Zhao T.J., Starks P.J., Bosch D.D., Seyfried M., Moran M.S., Goodrich D.C., Kerr Yann, Leroux D.
Source
IEEE Transactions on Geoscience and Remote Sensing, 2012, 50 (5), p. 1530-1543 ISSN 0196-2892
Estimation of soil moisture at large scale has been performed using several satellite-based passive microwave sensors and a variety of retrieval methods over the past two decades. The most recent source of soil moisture is the European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission. A thorough validation must be conducted to insure product quality that will, in turn, support the widespread utilization of the data. This is especially important since SMOS utilizes a new sensor technology and is the first passive L-band system in routine operation. In this paper, we contribute to the validation of SMOS using a set of four in situ soil moisture networks located in the U. S. These ground-based observations are combined with retrievals based on another satellite sensor, the Advanced Microwave Scanning Radiometer (AMSR-E). The watershed sites are highly reliable and address scaling with replicate sampling. Results of the validation analysis indicate that the SMOS soil moisture estimates are approaching the level of performance anticipated, based on comparisons with the in situ data and AMSR-E retrievals. The overall root-mean-square error of the SMOS soil moisture estimates is 0.043 m(3)/m(3) for the watershed networks (ascending). There are bias issues at some sites that need to be addressed, as well as some outlier responses. Additional statistical metrics were also considered. Analyses indicated that active or recent rainfall can contribute to interpretation problems when assessing algorithm performance, which is related to the contributing depth of the satellite sensor. Using a precipitation flag can improve the performance. An investigation of the vegetation optical depth (tau) retrievals provided by the SMOS algorithm indicated that, for the watershed sites, these are not a reliable source of information about the vegetation canopy. The SMOS algorithms will continue to be refined as feedback from validation is evaluated, and it is expected that the SMOS estimates will improve.
Plan de classement
Bioclimatologie [072] ; Télédétection [126]
Identifiant IRD
PAR00008809
Contact