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Received：08 July 2019，
Published：07 March 2020
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被动微波遥感反演土壤水分对应的土壤深度是土壤水分产品真实性检验和应用中必须确定的问题。本研究利用理论模型对影响土壤热采样深度的参数进行了分析。在此基础上，通过回归分析的方法发展了一个估算被动微波遥感土壤热采样深度的统计模型，并通过微波辐射测量实验对模型进行了验证。研究证明，理论模型模拟裸露地表发射率平均误差为0.032，基于理论模型发展的热采样深度统计模型的误差在0.5 cm左右。该统计模型可以通过土壤含水量、温度、质地和观测频率4个较容易获取的参数计算土壤微波辐射的热采样深度，为被动微波遥感土壤水分产品的真实性检验工作中地面土壤水分测量以及土壤水分遥感产品的应用提供参考。
One of the greatest advantages of microwave remote sensing over other remote sensing techniques is penetrability. Quantitatively estimating the sensing depth of passive microwave remote sensing is meaningful for simulation of satellite signals and validation of land surface parameters to estimate the sensing depth of passive microwave remote sensing. In this paper
a simple statistical model for estimating the thermal sampling depth in microwave frequencies of soil was developed and validated.
Thermal Sampling Depth (TSD) was introduced to describe the source of the main signals of passive microwave remote sensing. To develop a simple statistical model for estimating the TSD of soil
a theoretical model was introduced to describe the emission characteristics of a three-layer case
which incorporates all multiple reflections at the two boundaries. Based on radiative transfer theory
the total emission of the three layers was calculated. Sensitivity analysis was then performed to demonstrate the effects of the soil properties and frequency on the TSD based on a simulation database covering a wide range of soil characteristics and frequencies. Based on the sensitivity analysis results
a statistical model for estimating TSD was developed. This model can estimate the TSD using four common and easily acquired parameters: soil moisture
temperature
frequency
and soil specific surface area. For validation
a controlled field experiment using a Truck-mounted Multi-frequency Microwave Radiometer (TMMR) was designed and performed.
The total Root Mean Square Error (RMSE) between the TSD measured in field experiment and estimated using the statistical model was approximately 0.5 cm for the TRMM’s four frequencies.
The results indicated that the developed statistical model offers a relatively accurate and simple way to estimate the TSD.
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