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Defining the Range of Uncertainty Associated with Remotely
Sensed Soil Moisture
Introduction
As science and technology continue to advance towards establishing a
capability to remotely sense soil moisture, we must periodically evaluate
our progress. From such introspection, we gain insights into our strengths
and weakness and can identify research foci. Retrieval of soil moisture
information by remote sensing requires, among other things, soil property
information and corrections for surface roughness and vegetation optical
depth. Current correction procedures are based on empirical relationships
of limited breadth. Extending ground-based techniques to space-based systems
requires using remote sensing to provide estimates of the input variables
and parameters. The applicability of doing this was recently demonstrated
during the Southern Great Plains 1997 (SGP97) Hydrology Experiment (Jackson
et al., 1999). However, the potential errors in the soil moisture estimates
were not addressed. Therefore, a study was conducted to define the extent
to which errors in estimating algorithm input parameters at regional scale
result in uncertainty in the true value of soil moisture. From a review
of procedures used to estimate the variables and parameters required to
retrieve soil moisture at regional scale, we defined the range of errors
generally associated with each measurement. The model was run while varying
one parameter at a time over a range of values (errors) to quantify the
effects individual parameters have on soil moisture retrieval. The parameters
that produced the greatest effect were varied in paired combinations to
characterize potential compounded effects. We then recalculate soil moisture
for the Southern Great Plains 1997 Hydrology Experiment using random combinations
of errors in the input data. These results are compared with the initial
calculations.
Results
Although errors in estimating most soil moisture algorithm parameters
at regional scale yield total variations of less than about ±2% volumetric
water content (vwc), errors in estimating vegetation water content, vegetation
b parameter, percent clay, and surface roughness yield much larger uncertainty
in estimated soil moisture (Figure 1). The
effects of these parameter variations on calculated soil moisture are greater
for wetter soils (above 25% vwc) and can result in total errors in soil
moisture retrieval of up to ±12% vwc. Errors in estimating these
same parameters have a compound effect on calculated soil moisture when
they vary collectively, and may yield variations in soil moisture retrieval
as high as 38% vwc (-12%, +26%) for wet soil. Even under drier conditions
between 10% and 25% vwc, parameter errors result in soil moisture uncertainties
of ±4.5% to ±7.5%. Such uncertainties are unacceptably high
for many applications and may preclude using these data where individual
pixel values are of interest.
When combinations of random errors in vegetation water content, percent
clay, and surface roughness are imposed on the Southern Great Plains 1997
(SGP97) Hydrology Experiment input data set, the macrostructure is reproduced
but the resulting soil moisture field is significantly more heterogeneous
than the original soil moisture field (Figure
2). Parameter estimation in SGP97 based on field observations and a
supervised land cover classification contributed to a relatively low soil
moisture uncertainty (±2) of ±3% vwc for most brightness
temperatures (Figure 3). The calculations
with larger parameter errors resulted in a larger soil moisture uncertainty
of ±5% vwc for given brightness temperatures. This represents the
maximum uncertainty associated with a large number of measurements using
available regional scale data to estimate algorithm input parameters.
In summary, errors in regional scale estimates of vegetation water content,
the b parameter, percent clay and surface roughness may lead to very substantial
errors in retrieved soil moisture. These errors are particularly high for
wetter soils. Such errors may preclude using these data where individual
pixel values are of interest. On a regional scale, however, where samples
sizes are large, uncertainties in remotely sensed soil moisture are within
acceptable limits for most disciplines.
For Further Information:
Laymon, C., Manu, A., Crosson, W., and Jackson, T., 1999, Defining the range
of uncertainty associated with remotely sensed soil moisture estimates with
microwave radiometers, EOS/SPIE Symposium on Remote Sensing, Florence, Italy,
Sept. 20-24.
Manu, A., Laymon, C., Archer, F., and Coleman, T., 1999, Sensitivity of
Soil Moisture Remote Sensing Algorithms at L and S Band to Variations in
Input Parameters, EOS/SPIE Symposium on Remote Sensing, Florence, Italy,
Sept. 20-24.
More on SGP97 can be found at: http://hydrolab.arsusda.gov/sgp97/
Reference Cited:
Jackson, T.J., Le Vine, D. M., Hsu, A. Y., Oldak, A., Starks, P. J., Swift,
C. T., Isham, J. D., and Haken, M., 1999, Soil moisture mapping at regional
scales using microwave radiometry: the Southern Great Plains Hydrology Experiment,
IEEE Trans. Geosci. Remote Sens., v.37, 2136-2151.
Responsible Official: Dr. James E. Arnold (jim.arnold@msfc.nasa.gov)
Technical Contact: Charles Laymon (charles.laymon@msfc.nasa.gov)
Page Curator: Diane Samuelson (diane.samuelson@msfc.nasa.gov)
Last Updated: December 30, 1999
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