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In this paper,we studied the effect of spatial distribution of soil parameters on passive soil moisture retrieval at pixel scale.First,we evaluated the forward microwave emission model and soil moisture retrieval algorithm accuracy through the observa-tion of field experiments.Then,we used soil parameters in different spatial distribution patterns,including random,normal,and uniform distribution,to determine the different levels of heterogeneity on soil moisture retrieval,in order to seek the rela-tionship between heterogeneity and soil moisture retrieval error.Finally,we conducted a controlled heterogeneity effect ex-periment measurements using a Truck-mounted Multi-frequency Radiometer(TMMR) to validate our simulation results.This work has proved that the soil moisture retrieval algorithm had a high accuracy(RMSE=0.049 cm3 cm 3) and can satisfy the need of this research.The simulation brightness temperatures match well with observations,with RMSE=9.89 K.At passive microwave remote sensing pixel scale,soil parameters with different spatial distribution patterns could have different levels of error on soil moisture estimation.Overall,we found that soil moisture with a random distribution in a satellite pixel scale can cause the largest error,with a normal distribution being the second,and a uniform distribution the least due to the smallest het-erogeneity.
In this paper, we studied the effect of spatial distribution of soil parameters on passive soil moisture retrieval at pixel scale. First, we evaluated the forward microwave emission model and soil moisture retrieval algorithm accuracy through the observa-tion of field experiments. Shen, we used soil parameters in different spatial distribution patterns, including random, normal, and uniform distribution, to determine the different levels of heterogeneity on soil moisture retrieval, in order to seek the rela-tionship between heterogeneity and soil moisture retrieval error. a controlled heterogeneity effect ex-periment measurements using a Truck-mounted Multi-frequency Radiometer (TMMR) to validate our simulation results. This work has proved that the soil moisture retrieval algorithm had a high accuracy (RMSE = 0.049 cm3 cm3) and can satisfy the need of this research. The simulation of brightness with match well with observations, with RMSE = 9.89 K.At passive microwave remote se nsing pixel scale, soil parameters with different spatial distribution patterns could have different levels of error on soil moisture estimation. Overall, we found that soil moisture with a random distribution in a satellite pixel scale can cause the largest error, with a normal distribution being the second, and a uniform distribution the least due to the smallest het-erogeneity.