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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.


Soil moisture scaling parameters clr (left) and dlr (right) derived from ASAR image time series.
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f10-sensors-08-01174: Soil moisture scaling parameters clr (left) and dlr (right) derived from ASAR image time series.

Mentions: The retrieved maps of clr and dlr are shown in Figure 10. One can see that clr tends to be positive for forests and settlements and predominantly negative over the agricultural areas. Similar but inverted patterns are observed in dlr which takes on values below one for dense vegetation and settlements and values above one for agricultural land. These results suggests that in forests and more dense vegetation, surface soil moisture conditions are less variable compared to the surrounding agricultural land. Within the agricultural area, clr and dlr show comparably little spatial variation, with the exception of some agricultural fields. These outliers may be related to irrigation, which is applied in the study area and cause clr to reach higher and dlr to reach lower values comparable to non-irrigated fields. An example of the irrigation effect on coefficients clr and dlr is observed at the ASAR pixel closest to the REMEDHUS station Q8 (Table 1). Thus, this measurement was excluded from further statistical comparisons. Equally, it is not unlikely that irrigation is responsible for the behaviour of clr and dlr in and near settlements.


Temporal Stability of Soil Moisture and Radar Backscatter Observed by the Advanced Synthetic Aperture Radar (ASAR)
Soil moisture scaling parameters clr (left) and dlr (right) derived from ASAR image time series.
© Copyright Policy
Related In: Results  -  Collection

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

f10-sensors-08-01174: Soil moisture scaling parameters clr (left) and dlr (right) derived from ASAR image time series.
Mentions: The retrieved maps of clr and dlr are shown in Figure 10. One can see that clr tends to be positive for forests and settlements and predominantly negative over the agricultural areas. Similar but inverted patterns are observed in dlr which takes on values below one for dense vegetation and settlements and values above one for agricultural land. These results suggests that in forests and more dense vegetation, surface soil moisture conditions are less variable compared to the surrounding agricultural land. Within the agricultural area, clr and dlr show comparably little spatial variation, with the exception of some agricultural fields. These outliers may be related to irrigation, which is applied in the study area and cause clr to reach higher and dlr to reach lower values comparable to non-irrigated fields. An example of the irrigation effect on coefficients clr and dlr is observed at the ASAR pixel closest to the REMEDHUS station Q8 (Table 1). Thus, this measurement was excluded from further statistical comparisons. Equally, it is not unlikely that irrigation is responsible for the behaviour of clr and dlr in and near settlements.

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.