Estimating surface soil moisture and soil roughness over semiarid areas
from the use of the copolarization ratio
R.D. Magagi
a,
*, Y.H. Kerr
b
a
INRS-Eau, 2800 rue Einstein, Case Postale 7500, Sainte-Foy, Quebec, Canada G1V 4C7
b
CESBIO, 18 avenue E. Belin, BPi. 2801, 31401 Toulouse cedex 4, France
Received 28 February 2000; accepted 21 August 2000
Abstract
This paper presents a new method to retrieve soil moisture and roughness from ERS-1. Wind scatterometer (WSC) data measured over the
HAPEX-Sahel area (semiarid environment). The retrieval algorithm makes full use of the multiangular acquisitions and the high temporal
repetition of the measured backscattering coefficients. The vegetation contribution to the signal is taken into account through a first-order
radiative transfer model. The soil moisture and roughness are subsequently retrieved, throughout the rainy season, using the copolarization
ratio as expressed by Oh et al. [IEEE Transactions on Geoscience and Remote Sensing GE-30 (1992) 370±381.]. The paper describes the
data and the approach used, together with the results gained. A good sensitivity of the backscattering coefficient to soil moisture is obtained.
The results are compared with data collected during the HAPEX-Sahel campaign. D 2001 Elsevier Science Inc. All rights reserved.
1. Introduction
Soil moisture measurements are a prerequisite for many
research and application topics. In this paper, the term soil
moisture (obtained from microwave data) will refer to the
amount of water contained in the very first centimeters of
the soil. Actually, soil moisture is of crucial importance for
characterizing the water exchanges between the surface and
the atmosphere (Chanzy & Kustas, 1995), for the derivation
of fluxes at the surface atmosphere interface, and as input
(Pielke, Dalu, Snook, Lee, & Kittel, 1991) in global
circulation models (GCMs), to name but a few. Beljaars,
Viterbo, Miller, and Betts (1996) showed that the knowl-
edge of soil moisture significantly improves the accuracy in
rainfall estimates. Surface soil moisture is also of prime
importance in surface hydrology since, coupled with the
roughness, it sets the conditions for runoff/infiltration as a
function of rain rates.
Similarly, in vegetation growth models, it is necessary to
have an estimate of all the growth limiting factors, i.e.,
water, temperature, insolation, and nutrients. In arid and
semiarid areas the most limiting factor is water availability.
Even though soil moisture is not a solution for water
availability, methods have been developed for the derivation
of root zone water content through the knowledge of surface
soil moisture, rainfall and soil characteristics (Bernard,
Vauclin, & Vidal-Madjar, 1981; Jackson, 1986).
However, in spite of the high demand, there are no means
for the time being to gather information on soil moisture on
a global scale. The previous nonimaging spaceborne scatte-
rometers were in orbit during a short period of time (summer
1973 for Skylab and summer 1978 for SEASAT) and
operated in K-band (13.8 GHz). Therefore, they were not
suitable to allow useful temporal monitoring of soil moist-
ure. It seemed useful to test the potential of the low-
frequency active microwave satellite system, the ERS-1
wind scatterometer (WSC), to derive surface soil moisture.
Due to the relationships between the backscattering coeffi-
cient (s
0
) and surface characteristics (soil roughness, soil
moisture, and vegetation), many studies have shown the
possibility of inferring land surface parameters from active
microwave data (Alphonse, 1988; Benallegue, Taconet,
Vidal-Madjar, & Normand, 1995; Bouman, 1991; Dobson
& Ulaby, 1986a, 1986b; Engman 1991; Mo, Wang, &
Schmugge, 1988; Prevot, Champion, & Guyot, 1993; Pre-
vot, Dechambre, et al., 1993). However, these studies
mainly showed that radar signal could be related to soil
* Corresponding author. Tel.: +1-418-654-3784; fax: +1-418-654-
2600.
E-mail address: magagira@inrs-eau.uquebec.ca (R.D. Magagi).
www.elsevier.com/locate/rse
Remote Sensing of Environment 75 (2001) 432 ± 445
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