A Combined Optical–Microwave Method to Retrieve Soil Moisture Over Vegetated Areas

A simple approach for correcting for the effect of vegetation in the estimation of the surface soil moisture (wS) 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 wS 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.

[1]  W. Marsden I and J , 2012 .

[2]  Matthew O. Jones,et al.  Satellite passive microwave remote sensing for monitoring global land surface phenology , 2011 .

[3]  P. Wetzel,et al.  Evapotranspiration from Nonuniform Surfaces: A First Approach for Short-Term Numerical Weather Prediction , 1988 .

[4]  F. R. Schiebe,et al.  Large area mapping of soil moisture using the ESTAR passive microwave radiometer , 1995 .

[5]  Thomas J. Jackson,et al.  Soil moisture mapping using ESTAR under dry conditions from the Southern Great Plains Experiment (SGP99) , 2003, IEEE Trans. Geosci. Remote. Sens..

[6]  Thomas J. Jackson,et al.  meeting summary: GEWEX/BAHC International Workshop on Soil Moisture Monitoring, Analysis, and Prediction for Hydrometeorological and Hydroclimatological Applications , 2001 .

[7]  T. Carlson An Overview of the “Triangle Method” for Estimating Surface Evapotranspiration and Soil Moisture from Satellite Imagery , 2007, Sensors (Basel, Switzerland).

[8]  Yann Kerr,et al.  Characterizing the dependence of vegetation model parameters on crop structure, incidence angle, and polarization at L-band , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[9]  Yann Kerr,et al.  Impact of rain interception by vegetation and mulch on the L-band emission of natural grass , 2006 .

[10]  Joost C. B. Hoedjes,et al.  SMOSREX: A long term field campaign experiment for soil moisture and land surface processes remote sensing , 2006 .

[11]  T. Schmugge,et al.  Mapping surface soil moisture with microwave radiometers , 1994 .

[12]  Jean-Pierre Wigneron,et al.  Sensitivity of Passive Microwave Observations to Soil Moisture and Vegetation Water Content: L-Band to W-Band , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[13]  A. Huete,et al.  Overview of the radiometric and biophysical performance of the MODIS vegetation indices , 2002 .

[14]  Kaniska Mallick,et al.  Estimating volumetric surface moisture content for cropped soils using a soil wetness index based on surface temperature and NDVI , 2009 .

[15]  Yann Kerr,et al.  Two-Dimensional Microwave Interferometer Retrieval Capabilities over Land Surfaces (SMOS Mission) , 2000 .

[16]  Jiancheng Shi,et al.  The Soil Moisture Active Passive (SMAP) Mission , 2010, Proceedings of the IEEE.

[17]  Elfatih A. B. Eltahir,et al.  A Soil Moisture–Rainfall Feedback Mechanism: 1. Theory and observations , 1998 .

[18]  Thomas J. Jackson,et al.  Soil moisture mapping at regional scales using microwave radiometry: the Southern Great Plains Hydrology Experiment , 1999, IEEE Trans. Geosci. Remote. Sens..

[19]  Y. Kerr,et al.  Semi-empirical regressions at L-band applied to surface soil moisture retrievals over grass , 2006 .

[20]  Edward J. Kim,et al.  The NAFE'06 data set: towards soil moisture retrieval at intermediate resolution , 2008 .

[21]  Y. Kerr,et al.  Estimates of surface soil moisture under grass covers using L-band radiometry , 2007 .

[22]  Yann Kerr,et al.  Design and test of the ground-based L-band Radiometer for Estimating Water In Soils (LEWIS) , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[23]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[24]  Ann Henderson-Sellers,et al.  Sensitivity of the biosphere-atmosphere transfer scheme (BATS) to the inclusion of variable soil characteristics , 1987 .

[25]  Y. Kerr,et al.  L-band Microwave Emission of the Biosphere (L-MEB) Model: Description and calibration against experimental data sets over crop fields , 2007 .

[26]  J. Wigneron,et al.  Retrieving near-surface soil moisture from microwave radiometric observations: current status and future plans , 2003 .

[27]  Jean-Pierre Wigneron,et al.  Monitoring of water and carbon fluxes using a land data assimilation system: a case study for southwestern France , 2010 .

[28]  M. Guérif,et al.  Adjustment procedures of a crop model to the site specific characteristics of soil and crop using remote sensing data assimilation , 2000 .

[29]  Miller,et al.  The Anomalous Rainfall over the United States during July 1993: Sensitivity to Land Surface Parameterization and Soil Moisture Anomalies , 1996 .

[30]  P. Dirmeyer Using a global soil wetness dataset to improve seasonal climate simulation , 2000 .

[31]  Martha C. Anderson,et al.  Vegetation water content mapping using Landsat data derived normalized difference water index for corn and soybeans , 2004 .

[32]  Yann Kerr,et al.  Soil moisture retrieval from space: the Soil Moisture and Ocean Salinity (SMOS) mission , 2001, IEEE Trans. Geosci. Remote. Sens..

[33]  C. A. van Diepen,et al.  Crop model data assimilation with the Ensemble Kalman filter for improving regional crop yield forecasts , 2007 .

[34]  Y. Kerr,et al.  Effective soil moisture sampling depth of L-band radiometry: A case study , 2010 .

[35]  A. Huete,et al.  MODIS VEGETATION INDEX ( MOD 13 ) ALGORITHM THEORETICAL BASIS DOCUMENT Version 3 . 1 Principal Investigators , 1999 .

[36]  Yann Kerr,et al.  Airborne microwave radiometry on a semi-arid area during HAPEX-Sahel , 1997 .

[37]  J. Shukla,et al.  Impact of Initial Soil Wetness on Seasonal Atmospheric Prediction , 1999 .

[38]  Yann Kerr,et al.  Soil moisture retrievals from biangular L-band passive microwave observations , 2004, IEEE Geoscience and Remote Sensing Letters.

[39]  Yann Kerr,et al.  Two-year global simulation of L-band brightness temperatures over land , 2003, IEEE Trans. Geosci. Remote. Sens..

[40]  P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .

[41]  N. Bruguier,et al.  A simple algorithm to retrieve soil moisture and vegetation biomass using passive microwave measurements over crop fields , 1995 .