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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 observation 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 relationship between heterogeneity and soil moisture retrieval error. Finally, we conducted a controlled heterogeneity effect experiment 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 cm cm) 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 heterogeneity. [ABSTRACT FROM AUTHOR]

Highly accurate observations at various scales on the land surface are urgently needed for the studies of many areas, such as hydrology, meteorology, and agriculture. With the rapid development of remote sensing techniques, remote sensing has had the capacity of monitoring many factors of the Earth's land surface. Especially, the space-borne microwave remote sensing systems have been widely used in the quantitative monitoring of global snow, soil moisture, and vegetation parameters with their all-weather, all-time observation capabilities and their sensitivities to the characteristics of land surface factors. Based on the electromagnetic theories and microwave radiative transfer equations, researchers have achieved great successes in the microwave remote sensing studies for different sensors in recent years. This article has systematically reviewed the progresses on five research areas including microwave theoretical modeling, microwave inversion on soil moisture, snow, vegetation and land surface temperatures. Through the further enrichment of remote sensing datasets and the development of remote sensing theories and inversion techniques, remote sensing including microwave remote sensing will play a more important role in the studies and applications of the Earth systems. [ABSTRACT FROM AUTHOR]