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Temporal Stability of Soil Moisture and Radar Backscatter Observed by the Advanced Synthetic Aperture Radar (ASAR)

View Article: PubMed Central - PubMed

ABSTRACT

The high spatio-temporal variability of soil moisture is the result of atmospheric forcing and redistribution processes related to terrain, soil, and vegetation characteristics. Despite this high variability, many field studies have shown that in the temporal domain soil moisture measured at specific locations is correlated to the mean soil moisture content over an area. Since the measurements taken by Synthetic Aperture Radar (SAR) instruments are very sensitive to soil moisture it is hypothesized that the temporally stable soil moisture patterns are reflected in the radar backscatter measurements. To verify this hypothesis 73 Wide Swath (WS) images have been acquired by the ENVISAT Advanced Synthetic Aperture Radar (ASAR) over the REMEDHUS soil moisture network located in the Duero basin, Spain. It is found that a time-invariant linear relationship is well suited for relating local scale (pixel) and regional scale (50 km) backscatter. The observed linear model coefficients can be estimated by considering the scattering properties of the terrain and vegetation and the soil moisture scaling properties. For both linear model coefficients, the relative error between observed and modelled values is less than 5 % and the coefficient of determination (R2) is 86 %. The results are of relevance for interpreting and downscaling coarse resolution soil moisture data retrieved from active (METOP ASCAT) and passive (SMOS, AMSR-E) instruments.

No MeSH data available.


Coefficient of determination R2 (left) and standard error of estimate (SEE) expressed in decibels (right) of the linear backscatter scaling model. The forest and settlement polygons from the land cover map are overlain over the images for orientation purposes.
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f6-sensors-08-01174: Coefficient of determination R2 (left) and standard error of estimate (SEE) expressed in decibels (right) of the linear backscatter scaling model. The forest and settlement polygons from the land cover map are overlain over the images for orientation purposes.

Mentions: Spatial images of the coefficient of determination (R2) and the standard error of estimate (SEE) of the linear backscatter scaling model (16) are shown in Figure 6. As expected, R2 in general is high over agricultural areas and other sparsely vegetated terrain with values up to about 0.8. The correlation decreases with increasing vegetation density and becomes smaller than 0.2 over dense forests and urban areas. The standard error of estimate shows very similar spatial patterns. Over areas characterised by relatively stable backscatter (and hence low R2) SEE may be as low as 0.6 dB which corresponds to the noise of the ASAR Wide Swath measurements. With decreasing vegetation density SEE increases. One important reason for this is that over bare or sparsely vegetated terrain, backscatter shows a pronounced incidence angle dependency. Therefore, uncertainties related to the normalisation Equation (21) have a stronger effect on the accuracy of σ0(30) over these areas compared to more densely vegetated areas. Also, agricultural activities such as ploughing or harvesting may cause outliers. Nevertheless, SEE does not exceed 2 dB even over agricultural fields characterised by a steep σ0(ϑ) curve. Therefore, it is concluded that the linear time-invariant backscatter model (26) is well suited for describing the spatio-temporal behaviour of radar backscatter across different spatial scales. This also corroborates the finding from the analysis of the in-situ measurements that spatial soil moisture patterns in general exhibit a high degree of temporal persistence.


Temporal Stability of Soil Moisture and Radar Backscatter Observed by the Advanced Synthetic Aperture Radar (ASAR)
Coefficient of determination R2 (left) and standard error of estimate (SEE) expressed in decibels (right) of the linear backscatter scaling model. The forest and settlement polygons from the land cover map are overlain over the images for orientation purposes.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3927501&req=5

f6-sensors-08-01174: Coefficient of determination R2 (left) and standard error of estimate (SEE) expressed in decibels (right) of the linear backscatter scaling model. The forest and settlement polygons from the land cover map are overlain over the images for orientation purposes.
Mentions: Spatial images of the coefficient of determination (R2) and the standard error of estimate (SEE) of the linear backscatter scaling model (16) are shown in Figure 6. As expected, R2 in general is high over agricultural areas and other sparsely vegetated terrain with values up to about 0.8. The correlation decreases with increasing vegetation density and becomes smaller than 0.2 over dense forests and urban areas. The standard error of estimate shows very similar spatial patterns. Over areas characterised by relatively stable backscatter (and hence low R2) SEE may be as low as 0.6 dB which corresponds to the noise of the ASAR Wide Swath measurements. With decreasing vegetation density SEE increases. One important reason for this is that over bare or sparsely vegetated terrain, backscatter shows a pronounced incidence angle dependency. Therefore, uncertainties related to the normalisation Equation (21) have a stronger effect on the accuracy of σ0(30) over these areas compared to more densely vegetated areas. Also, agricultural activities such as ploughing or harvesting may cause outliers. Nevertheless, SEE does not exceed 2 dB even over agricultural fields characterised by a steep σ0(ϑ) curve. Therefore, it is concluded that the linear time-invariant backscatter model (26) is well suited for describing the spatio-temporal behaviour of radar backscatter across different spatial scales. This also corroborates the finding from the analysis of the in-situ measurements that spatial soil moisture patterns in general exhibit a high degree of temporal persistence.

View Article: PubMed Central - PubMed

ABSTRACT

The high spatio-temporal variability of soil moisture is the result of atmospheric forcing and redistribution processes related to terrain, soil, and vegetation characteristics. Despite this high variability, many field studies have shown that in the temporal domain soil moisture measured at specific locations is correlated to the mean soil moisture content over an area. Since the measurements taken by Synthetic Aperture Radar (SAR) instruments are very sensitive to soil moisture it is hypothesized that the temporally stable soil moisture patterns are reflected in the radar backscatter measurements. To verify this hypothesis 73 Wide Swath (WS) images have been acquired by the ENVISAT Advanced Synthetic Aperture Radar (ASAR) over the REMEDHUS soil moisture network located in the Duero basin, Spain. It is found that a time-invariant linear relationship is well suited for relating local scale (pixel) and regional scale (50 km) backscatter. The observed linear model coefficients can be estimated by considering the scattering properties of the terrain and vegetation and the soil moisture scaling properties. For both linear model coefficients, the relative error between observed and modelled values is less than 5 % and the coefficient of determination (R2) is 86 %. The results are of relevance for interpreting and downscaling coarse resolution soil moisture data retrieved from active (METOP ASCAT) and passive (SMOS, AMSR-E) instruments.

No MeSH data available.