1167 
USING OPTICAL-MICROWAVE SYNERGY FOR ESTIMATING SURFACE 
ENERGY FLUXES OVER SEMI-ARID RANGELAND 
D.TROUFLEAU 1 , A. VIDAL 1 , A. BEAUDOIN 1 , M.S. MORAN 2 , M.A. WELTZ 3 , D.C. GOODRICH 3 , 
J. WASHBURN 4 , A.F. RAHMAN 5 
1 CEMAGREF-ENGREF Remote Sensing Laboratory, B.P. 5095, 34033 Montpellier France 
2 USDA-ARS U.S. Water Conservation Laboratory, 4331 E. broadway, Phoenix, Az., 85044 USA 
3 USDA-ARS Southwest Watershed Research Center, 2000 E. Allen, Tucson, Az., 85719 USA 
4 Univ. of Arizona, Dept, of Hydrology and Water Resources, Tucson, Az., 85719 USA 
5 Univ. of Arizona, Dept, of Soil and Water Science, Tucson, Az., 85719 USA 
ABSTRACT 
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 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 RMSE of 1.3% of soil moisture. In a second step a semi-empirical approach based on energy 
balance relates soil temperature Ts to this estimated surface soil moisture. Vegetation temperature is then 
deduced from Ts and Landsat TM composite temperature in order to estimate sensible heat flux according to a 
two-layer type model providing an RMSE of 29 W/m 2 . 
Keywords. ERS-1 SAR images, soil moisture, thermal-microwave synergy, sensible heat flux, two-layer model. 
1. INTRODUCTION 
Estimation of distributed surface fluxes over heterogeneous terrain and surface cover is of great interest to most 
agricultural, hydrologic and climatological studies as it is a required first step for aggregation or upscaling to 
produce regional-scale flux estimates. Remote sensing techniques for estimation of surface fluxes provides one 
of the few, if only, viable methods for large area flux estimation (Seguin et al., 1991). Unfortunately, when 
considering remotely sensed estimation of sensible and latent heat flux with optical data (mainly visible, near 
infrared (NIR) and thermal infrared data), it appears that operational methods are currently applied only to 
agricultural fields with quite homogeneous surfaces. 
In the case of sparse vegetation, such as immature crops or semi-arid rangelands, two-layer 
models, accounting for the specific contributions of soil and vegetation to fluxes, have proved to describe quite 
well surface energy exchanges of heterogeneous surfaces with only a few controlling parameters and variables 
(Lhomme et al., 1994; Choudhury, 1989). Nevertheless, one of the limiting aspects of these models when run 
with remote sensing data is the need of the specific soil and vegetation temperatures since thermal observation 
from space provides only a composite signal of these two components. A multi-sensor approach can then be 
designed to retrieve components temperature using microwaves sensitivity to surface soil moisture (related to its 
temperature), surface thermal emission and spectral vegetation indices (vegetation cover). 
The study presented here will focus at first on the possibility of using radar ERS-1 products to 
monitor the near surface soil moisture (0-5 cm) over mixed grass and bush rangeland of a semi-arid watershed 
in Arizona (Walnut Gulch). The second part will then propose a way of combining the resulting estimated soil 
moisture with thermal infrared data to improve sensible heat flux estimation with the use of a two-layer type 
model.