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AirSAR/MASTER
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Estimation of Soil Moisture with Vegetated Surface by Multi-Temporal Measurements
Data Analysis Under Multi-Temporal Measurements Configuration
The temporal variability of surface roughness and vegetation cover are generally at much longer time scale than that of soil moisture. Unless there is a human activity we may reasonably assume that both surface roughness and vegetation cover are same at time interval from a few days to a week. The change in SAR measurements between the repeat passes, therefore, is resulted from the change of ground dielectric properties or soil moisture. Under this configuration, using two repeat pass polarimetric SAR measurements, we can write the difference of the first components
and the ratio of the second components by (4) as
Where the number after pp in either superscript or subscript represents the first and second SAR measurements. At L-band, the surface roughness parameter RMS height is small in comparison of the incidence wavelength so that we could approximate the polarization amplitude as that in the small perturbation model
-ann which are only depends only on the surface dielectric constant
es and incidence angle
q. Where app is given by
As we noticed in (9), the polarization amplitude is exactly same as the surface reflectivity for HH polarization. Under assumption of the surface roughness do not change between two SAR measurements, we have
Furthermore, using (7), (8) and (10), we obtain
and
Therefore, we can decompose or directly estimate the volume and surface scattering components by (11) and (12) for HH polarization measurements.
The SAR data used in this study was from the Washita '92 experiment. During the experiment from June 10-18, 1992, a time series of spatially distributed hydrologic data focusing on soil moisture and evaporative fluxes were collected. At the same time, the AIRSAR sensor aboard the NASA DC-8 aircraft collected a sequence of 6 L band radar images over an agricultural test site located just outside the watershed. The Washita '92 experiment was conducted immediately following a series of heavy rainfalls that ended on June 9. Thereafter, no more rain occurred throughout the entire series of the AIRSAR flights, thus allowing observation of a drying-down sequence. From any two of 6 sequence SAR measurements, we can estimated the surface and volume backscattering components using (11) and (12). Furthermore, the relative change in dielectric property of any pair from 6 sequence SAR measurements can be estimated by (10).
Figure 1. Comparison of the normalized cross product of the decomposed even reflection components with that of reflection coefficients calculated from field measurements data.
Reference
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E. T. Engman and N. Chauhan, " Status of Microwave Soil Measurements with Remote Sensing", Remote Sensing Environ., vol 51, no. 1, pp. 189-198, 1995.
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- F. T. Ulaby, P. C. Dubois, and J. J. Van Zyl, "Radar Mapping of Surface Soil Moisture", J. of Hydrology, 184, 57-84, 1996.
- J. Shi, J. Wang, A. Hsu, P. O'Neill, and E. T. Engman, "Estimation of bare surface soil moisture and surface roughness parameters using L-band SAR image data", In press, IEEE Transactions on Geoscience and Remote Sensing, 1997.
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