Abstract
Soil moisture (SM) plays important roles in surface energy conversion, crop growth, environmental protection, and drought monitoring. As crops grow, the associated vegetation seriously affects the ability of satellites to retrieve SM data. Here, we collected such data at different growth stages of maize using Bragg and X-Bragg scattering models based on the Freeman–Durden polarization decomposition method. We used the H/A/Alpha polarization decomposition approach to extract accurate threshold values of decomposed scattering components. The results showed that the H and Alpha values of bare soil areas were lower and those of vegetated areas were higher. The threshold values of the three scattering components were 0.2–0.4 H and 7–24° Alpha for the surface scattering component, 0.6–0.9 H and 22–50° Alpha for the volume scattering component, and other values for the dihedral scattering component. The SM data retrieved (using the X-Bragg model) on June 27, 2014, were better than those retrieved at other maize growth stages and were thus associated with the minimum root-mean-square error value (0.028). The satellite-evaluated SM contents were in broad agreement with data measured in situ. Our algorithm thus improves the accuracy of SM data retrieval from synthetic-aperture radar (SAR) images.
Highlights
Soil moisture content (SMC) is a key in study of agricultural production, environmental protection, and surface energy conversion, such as drought monitoring and dust storm monitoring [1,2,3]
It is difficult to distinguish the various scattering components of vegetation-covered surfaces [6]. e radar was frequently used in detecting SMC; the signals are attenuated by vegetation. erefore, the sensitivity of the radar signal detecting SMC is reduced by vegetation. is is a major problem for soil moisture retrieval from radar data [7]
To eliminate the effects of vegetation, we combined two polarization decomposition techniques (H/A/alpha angle (Alpha) and Freeman–Durden) [24]. e specific step is shown in Figure 2 for soil moisture retrieval
Summary
Soil moisture content (SMC) is a key in study of agricultural production, environmental protection, and surface energy conversion, such as drought monitoring and dust storm monitoring [1,2,3]. Erefore, the sensitivity of the radar signal detecting SMC is reduced by vegetation. Is is a major problem for soil moisture retrieval from radar data [7]. Water cloud model is widely used in evaluating low vegetation area. It is the most common retrieval method used [5]. Is model features only two scattering mechanisms: surface scattering from bare soil and volume scattering from vegetation [6]. Surface scattering changes with the growth of the crop. Erefore, we need to study the scattering at different growth stages. It is difficult to retrieve the SMC using only water cloud model at different growth stage of maize [8]
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