IEEE Transactions on Geoscience and Remote Sensing · 2012 · 39 citations · 37 references
Natural SciencesEarth SciencesSoil SciencesRemote SensingSoil PhysicsSoil ScienceLand Surface MonitoringSatellite SensorsSoil - Vegetation InteractionsVegetation Cover AssessmentVegetation IndicesVegetation MonitoringOptical DepthPassive Microwave SensingReflectivitySoil Moisture EstimationSoil Moisture ParameterizationSoil Moisture Remote SensingSoil Moisture RetrievalsSurface Soil Moisture Estimation
A simple approach for correcting for the effect of vegetation in the estimation of the surface soil moisture ( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">w</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">S</sub> ) from L-band passive microwave observations is presented in this study. The approach is based on semi-empirical relationships between soil moisture and the polarized reflectivity including the effect of the vegetation optical depth which is parameterized as a function of the normalized vegetation difference index (NDVI). The method was tested against in situ measurements collected over a grass site from 2004 to 2007 (SMOSREX experiment). Two polarizations (horizontal/vertical) and five incidence angles (20°, 30°, 40°, 50°, and 60°) were considered in the analysis. The best <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">w</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">S</sub> estimations were obtained when using both polarizations at an angle of 40°. The average accuracy in the soil moisture retrievals was found to be approximately 0.06 m3/m3, improving the estimations by 0.02 m3/m3 with respect to the case in which the vegetation effect is not considered. The results indicate that information on vegetation (through a vegetation index such as NDVI) is useful for the estimation of soil moisture through the semi-empirical regressions.
37
Overview of the radiometric and biophysical performance of the MODIS vegetation indices
Alfredo Huete, Kamel Didan, Tomoaki Miura et al. · Remote Sensing of Environment · 2002 · 9.6K citations
Agriculture, Ecology, Geography +14
The Soil Moisture Active Passive (SMAP) Mission
Dara Entekhabi, E. G. Njoku, Peggy O’Neill et al. · Proceedings of the IEEE · 2010 · 3.7K citations · Full text