Skip all navigation and jump to content Jump to site navigation
About MODIS News Data Tools /images2 Science Team Science Team Science Team

   + Home
ABOUT MODIS
MODIS Publications Link
MODIS Presentations Link
MODIS Biographies Link
MODIS Science Team Meetings Link
 

 

 

Zhao, JP; Zhang, XF; Bao, HY; Tong, QX; Wang, XY; Liao, CH (2012). Monitoring land surface soil moisture: co-inversion of visible, infrared and passive microwave sensing data. JOURNAL OF INFRARED AND MILLIMETER WAVES, 31(2), 137-0.

Abstract
To effectively retrieve large-scale daily soil moisture, this study proposed a model-level integrated approach termed co-inversion of visible, infrared and passive microwave remote sensing data. Specifically, the MODIS data are used to derive soil moisture base, and the AMSR-E data are employed to estimate daily variation of land surface soil moisture over a large area. The soil moisture information over the large area is then estimated by integrating these two parts; base and variation. Improvements inherent in the proposed approach enable daily 1 km x 1 km soil moisture estimation of the entire study area, even when some areas were covered with clouds. Verification with ground truthing data in Xinjiang, China shows that the co-inversion of thermal and passive microwave remotely sensed data can achieve better estimation of soil moisture than each single data source or model. The square correlation coefficient is 0.86 and RSME is 3.99 when the estimated soil moisture is compared with the ground truthings. The results proved that the co-inversion model outperformed either the MODIS or AMSR-E inversion of soil moisture over large areas, and can meet the needs of Xinjiang's soil moisture monitoring.

DOI:
1001-9014

ISSN:

NASA Home Page Goddard Space Flight Center Home Page