Abstract
Soil moisture and salinity are crucial parameters of the Earth’s ecosystem; how to understand the radiation properties of them is of great significance for remote sensing monitoring. In this study, the application of mixed soil dielectric models (Dobson and generalized refractive mixing dielectric model (GRMDM)) and saline soil dielectric models (Dobson-S, HQR (Qingrong Hu), and WYR (Yueru Wu)) were analyzed to select the optimal models to simulate brightness temperature based on observational data. The brightness temperature of the soil moisture and multilevel salinity was simulated by using the Q-H (parameter of polarization mixing and parameter of characterizing height) model and Holmes parameterization scheme of soil effective temperature. The results show that both the Dobson model and the GRMDM model can well reproduce the real part and imaginary part of the dielectric constant of non-saline soil, and the GRMDM model was better. With the increase of the frequency, the simulation error of the dielectric constant of the saline soil by using the Dobson-S model, HQR model, and WYR model also increased, and the simulation result of the WYR model was better in the L band. The simulated result of the brightness temperature of soil moisture between the observation value and simulation value presented a high correlation both in the horizontal polarization and vertical polarization, with R greater than 0.967 and 0.948, and the root mean square error smaller than 3.998 K and 2.766 K, respectively. Meanwhile, the correlation coefficients of the brightness temperature of the saline soil in the horizontal polarization and vertical polarization were 0.935 and 0.971, and the root mean square errors were 5.808 K and 4.65 K, respectively. The brightness temperature decreased as the soil salinity increased, and the higher the salinity content was, the quicker the brightness temperature decreased. We expect that the experimental results can be used as a reference for algorithm developers to further enhance the accuracy of soil moisture and soil salinity retrievals.
Highlights
Soil moisture is an important element of hydrothermal delivery and energy transformation in the Earth’s ecosystem, and is the most active part of the regional water cycle, and playsSensors 2020, 20, 2806; doi:10.3390/s20102806 www.mdpi.com/journal/sensorsSensors 2020, 20, 2806 a critical role in hydrological, ecological, and biogeochemical processes [1,2,3]
As the results have shown, both the Dobson model and generalized refractive mixing dielectric model (GRMDM) model can well reflect the dielectric constant of the non-saline-alkali soil
The dielectric property of bound water was introduced into the GRMDM model based on the Debye equation to perfect the dielectric model in principle, and it was regarded as a single component in the model
Summary
Soil moisture is an important element of hydrothermal delivery and energy transformation in the Earth’s ecosystem, and is the most active part of the regional water cycle, and playsSensors 2020, 20, 2806; doi:10.3390/s20102806 www.mdpi.com/journal/sensorsSensors 2020, 20, 2806 a critical role in hydrological, ecological, and biogeochemical processes [1,2,3]. Soil moisture has been considered a vital observation parameter in the research of hydrology, meteorology, and agriculture, especially for environmental issues of arid and semi-arid regions, such as hydrometeorology, oasis agriculture, ecological environment, and sustainable development [8,9]. Soil saline-alkaline as a form of land degradation has become a dominant factor restricting regional economic growth, eco-environment protection, and agricultural sustainable development [10]. Nations (FAO), the soil saline-alkaline area has reached 954 million hm , and this issue is more serious in arid and semi-arid regions [11]. Soil saline-alkaline are destructive for crop growth and production, they limit the ability of the root system to absorb moisture and nutrients, and lead to crop yield declines and agricultural productivity fades when the salinity of soil reach high levels [12]. Finding out how to monitor soil saline-alkaline effectively, to obtain soil salinity content and detect spatial–temporal patterns of change, enabling effective measures to be taken to prevent soil saline-alkaline as soon as possible, is of great significance for improving crop yields and protecting the eco-environment
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