Optical‐microwave synergy for estimating surface sensible heat flux over a semi‐arid rangeland

This study reports the first results of the Walnut Gulch’ 92 experiment concerning the combined use of radar backscattering (ERS‐1) and thermal infrared (Landsat TM) data to estimate surface sensible heat flux. The purpose is to use the radar/thermal synergy to retrieve both vegetation and soil temperatures required by a two‐layer type model. The first step investigates the potential use of ERS‐1 SAR images for surface soil moisture monitoring of the watershed using five calibrated images acquired during the year 1992 (dry to wet conditions). Results show that despite the typical low level of biomass of semi‐arid rangeland, an attenuation of the soil backscatter (up to 2 dB) can occur during the rainy season mainly due to the vegetation characteristics. A statistical relationship is then used to retrieve the volumetric surface soil moisture from ERS‐1 backscattering (sensitivity of 0.23 dB/% moisture) with a resulting root mean square error (RMSE) of 1.3% of soil moisture. In a second step a semi‐empirica...

[1]  M. S. Moran,et al.  Determination of sensible heat flux over sparse canopy using thermal infrared data , 1989 .

[2]  J. Lagouarde,et al.  The assessment of regional crop water conditions from meteorological satellite thermal infrared data , 1991 .

[3]  Robert J. Gurney,et al.  The theoretical relationship between foliage temperature and canopy resistance in sparse crops , 1990 .

[4]  L. Prévot,et al.  Estimating the characteristics of vegetation canopies with airborne radar measurements , 1993 .

[5]  C. Ottlé,et al.  Evaluation of the ERS 1/Synthetic Aperture Radar Capacity to Estimate Surface Soil Moisture: Two-Year Results Over the Naizin Watershed , 1995 .

[6]  A. Chehbouni,et al.  Determination of sensible heat flux over Sahelian fallow savannah using infra-red thermometry , 1994 .

[7]  S. Idso,et al.  Canopy temperature as a crop water stress indicator , 1981 .

[8]  A. Beaudoin,et al.  SAR observations and modeling of the C-band backscatter variability due to multiscale geometry and soil moisture , 1990 .

[9]  Kamal Sarabandi,et al.  Preliminary analysis of ERS-1 SAR for forest ecosystem studies , 1992, IEEE Trans. Geosci. Remote. Sens..

[10]  André Chanzy,et al.  Significance of soil surface moisture with respect to daily bare soil evaporation , 1993 .

[11]  F. Ulaby,et al.  Vegetation modeled as a water cloud , 1978 .

[12]  M. S. Moran,et al.  Use of ground‐based remotely sensed data for surface energy balance evaluation of a semiarid rangeland , 1994 .

[13]  T. Schmugge,et al.  Vegetation effects on the microwave emission of soils , 1991 .

[14]  J. Deardorff A Parameterization of Ground-Surface Moisture Content for Use in Atmospheric Prediction Models , 1977 .

[15]  Brent Clothier,et al.  ESTIMATION OF SOIL HEAT FLUX FROM NET RADIATION DURING THE GROWTH OF ALFALFA , 1986 .

[16]  M. S. Moran,et al.  Sensible heat flux - Radiometric surface temperature relationship for eight semiarid areas , 1994 .

[17]  M. S. Moran,et al.  Ground and aircraft infrared observations over a partially-vegetated area , 1990 .

[18]  M. S. Moran,et al.  Estimating crop water deficit using the relation between surface-air temperature and spectral vegetation index , 1994 .

[19]  P. S. Eagleson,et al.  Estimation of subpixel vegetation cover using red-infrared scattergrams , 1990 .

[20]  John L. Monteith,et al.  A four-layer model for the heat budget of homogeneous land surfaces , 1988 .