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

Abstract

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

Intercomparison of Soil Moisture Retrievals From In Situ, ASAR, and ECV SM Data Sets Over Different European Sites

“…urban, water bodies, and snow and ice). Furthermore, and as demonstrated in Wagner et al (2008), the temporal stability of soil moisture fields gives rise to an associated temporal stability in the backscatter signal. Strong correlations between local and regional backscatter is usually a good indicator of high sensitivity to soil moisture dynamics at the local scale (similarly, if the signal observed at the local scale correlates with the coarse scale measurement, then the local scale measurement is sensitive to the dynamics at the coarse scale).…”

“…The network comprises of 20 soil moisture monitoring stations, each using a Stevens Hydra probe sensor integrated over a depth of 0 -5cm below the surface. The network has been used for several purposes, including calibration and validation campaigns in support of the SMOS mission (Sanchez et al, 2012), and the evaluation of different satellite derived soil moisture products Wagner et al, 2008;Albergel et al, 2012).…”

Can C-band synthetic aperture radar be used to estimate soil organic carbon storage in tundra?

“…Due to the limited data availability, normalization cannot be applied as for the GM data (approach by Wagner et al, 2008;Sabel et al, 2012). Sabel et al (2012) and Wagner et al (2008) exploit the availability of a representative range of incidence angles for a certain location by using acquisitions from several overlapping orbits. A conventional method which corrects for local terrain-related effects only (as available with the free NEST toolbox by the European Space Agency) has been used instead.…”

“…The model provides an estimate of the slope in units of decibels per degree of incidence angle, which characterizes the decrease in the radar backscatter from near range to far range. The model is calibrated for each pixel separately using the acquisitions from overlapping orbits (Wagner et al, 2008). No data can be processed with the tools used for orthorectification (SGRT) for scenes which cross the dateline.…”

“…Applications across scale and instruments are common. EN-VISAT ASAR data acquired in Wide Swath (WS, ∼ 120 m) and Global Monitoring (GM, ∼ 1 km) mode were used, for example, to downscale soil-moisture-related patterns (Wagner et al, 2008;Pathe et al, 2009) or bias-correct (Högström and Bartsch, 2016) information from scatterometer. The applicability of similar multitemporal analyses for both GM and WS data has already been demonstrated for forest growing stock volume retrieval (Santoro et al, 2011).…”