Abstract. As the use of space-based sensors to observe soil moisture is becoming more plausible, it is becoming necessary to validate the remotely sensed soil moisture retrieval algorithms. In this paper, measurements of point gauges on the ground are analyzed as a possible ground-truth source for the comparison with remotely sensed data. The design compares a sequence of measurements taken on the ground and from space. The authors review the mean square error of expected differences between the two systems by Ha and North (1994), which is applied to the Little Washita watershed using the soil moisture dynamics model developed by Entekhabi and Rodriguez-Iturbe (1994). The model parameters estimated by Yoo and Shin (1998) for the Washita `92 (relative) soil moisture data are used in this study. By considering about 20 pairs of ground- and space-based measure-ments (especially, for the same case as the Washita `92 that the space-based sensor visits the FOV once a day), the expected error was able to be reduced to approximately 10 of the standard deviation of the fluctuations of the system alone. This seems to be an acceptable level of tolerance for identifying biases in the retrieval algorithms.
[1]
Gwilym M. Jenkins,et al.
Time series analysis, forecasting and control
,
1972
.
[2]
Gerald R. North,et al.
Formalism for Comparing Rain Estimation Designs
,
1989
.
[3]
P. Young,et al.
Time series analysis, forecasting and control
,
1972,
IEEE Transactions on Automatic Control.
[4]
Dara Entekhabi,et al.
Analytical framework for the characterization of the space-time variability of soil moisture
,
1994
.
[5]
G. North,et al.
Stochastic Modeling of Multidimensional Precipitation Fields Considering Spectral Structure
,
1996
.
[6]
Chulsang Yoo,et al.
Multi-dimensional precipitation models and their application to the ground-truth problem
,
1998
.
[7]
G. North,et al.
Use of multiple gauges and microwave attenuation of precipitation for satellite verification
,
1994
.
[8]
G. North,et al.
Evaluation of the impact of rainfall on soil moisture variability
,
1998
.
[9]
G. North,et al.
Stochastic characterization of space-time precipitation: implications for remote sensing
,
1994
.