Title | Spatial characterization of soil moisture using SAR data |
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Author | Merzouki, A; Teillet, P M; Bannari, A; King, D J |
Source | IEEE International Geoscience and Remote Sensing Symposium proceedings 4241751, 2006 p. 2332-2335, https://doi.org/10.1109/IGARSS.2006.603 |
Year | 2006 |
Alt Series | Natural Resources Canada, Contribution Series 20181421 |
Publisher | IEEE |
Document | serial |
Lang. | English |
Media | paper; on-line; digital |
File format | pdf |
Subjects | geophysics; remote sensing |
Program | Canada Centre for Remote Sensing Divsion |
Released | 2006 07 01 |
Abstract | In this paper, we report on the assessment of the spatial variability of soil moisture using synthetic aperture radar (SAR) data. The imagery was acquired during five different periods over the Roseau
River watershed in southern Manitoba, Canada. For validation purposes, ground measurements were carried out at 62 locations simultaneous with the satellite data acquisitions. The first step in this analysis was to assess the performance of the
Integral Equation Model (IEM) in simulating backscatter coefficients for selected bare soils. In order to reduce the surface roughness effect on radar backscatter behaviour, the semi-empirical calibration technique proposed in [1] was implemented.
This calibrated model was then implemented in a simplex inversion routine in order to estimate and map soil moisture. Derived spatial patterns of near-surface moisture content were then examined using exponential semivariogram analyses for spatial
extents ranging from tens of meters to kilometers. Despite a dependence of soil moisture on spatial extent, the semivariogram ranges (around 100 m) were found to be similar to previous studies in the literature. Scale analysis of soil moisture maps
shows a log-log linear spatial scale with statistical moments. Concave shape dependency of the corresponding slopes with the moment order was observed during all radar acquisition periods. The latter indicates the presence of multiscale effects.
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GEOSCAN ID | 311776 |
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