Passive Microwave Remote Sensing of Soil Moisture and Regional Drought Monitoring - Monitoring and Predicting Agricultural Drought: A Global Study - page 92

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moisture that can be expected at a high and a low microwave frequency.
If the physical temperature is determined independently, the emissivity
can be determined from T B . The physical temperature can be estimated
using surrogates based on satellite surface temperature, air temperature
observations, or model predictions (i.e., Owe and van de Griend, 2001).

Microwave Measurement and Vegetation For natural conditions, a varia-
tion in vegetation type and density is likely to be encountered. The presence
of vegetation has a major impact on the microwave measurement. Vege-
tation reduces the sensitivity of the relationship to changes in soil water
content by attenuating the soil signal and by adding its own microwave
emission to the measurement. This attenuation increases with increasing
microwave frequency, which is another important reason for using lower
frequencies. Attenuation is characterized by the optical depth of the vege-
tation canopy. Jackson and Schmugge (1991) presented a method for esti-
mating optical depth that used information on the vegetation type (typically
derived from land cover) and vegetation water content, which is estimated
using visible or near infrared remote sensing.

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So il Moisture Retrieval Algorithms

Recent efforts to develop research and operational methods for estimating
soil moisture retrieval algorithms for the advanced microwave scanning
radiometer (AMSR) instruments onboard the NASA Aqua and NASDA
ADEOS-II satellites (Njoku et al., 2000) have resulted in the formaliza-
tion of several alternative approaches. For the most part, all these methods
are based on the same basic relationships but are implemented differently.
Series of equations used to estimate soil moisture involve many variables
related to frequency, polarization, and viewing angle of the sensor, describ-
ing physical temperature and atmospheric profile (Njoku and Li, 1999).
These equations are solved using forward calculations of T B or inversions
for soil moisture.
Most research and applications involving passive microwave remote
sensing of soil moisture have emphasized low frequencies (L band). In this
range, it is possible to develop soil moisture retrievals based on a single
H polarization observation (Jackson, 1993). It is well known that with H
polarization T B is more sensitive to soil moisture than V polarization. This
approach relies on ancillary data on temperature, vegetation, land cover,
and soils. Atmospheric corrections are assumed to be negligible at these
frequencies. The single channel/ancillary data approach has been tested and
calibrated using aircraft L-band observations (Jackson et al., 1999) and
higher frequency satellite measurements (Jackson, 1997; Jackson and Hsu,
2001). Standard error of estimated values in L-band aircraft experiments
were on the order of 3% volumetric soil moisture. The higher frequency
satellite studies had larger errors ( > 5%). As noted previously, the optical
depth computation approach used in Jackson and Schmugge (1991) has

[92],