Abstract: The validation of large-scale soil moisture products in passive microwave remote sensing takes a key role for global climate change and data assimilation studies. However, it is difficult to obtain the real soil moisture values that can represent the soil moisture values and reflect spatial heterogeneity of large-scale passive microwave remote sensing products. It has become a key issue for the validation of passive microwave soil moisture products. At present, two technical approaches were used to build soil moisture observation network: the scale-up methods and the multi-source information fusion methods. Both two approaches involved the ground observation, simultaneous observation, and scale conversion, etc. The progress made in validation methods of large-scale soil moisture products was reviewed in this paper, and five typical methods were summarized, including the measured sample test, image data cross-test, model simulation test, influencing factor test and traditional geostatistical test. The first two methods belongs to the “spot generation” scale conversion test, and they attach importance to the spatial representation of the ground sample. Theoretical basis of the model simulation test and influencing factor test is the relationship between soil moisture and prior knowledge. However, these two methods neglect the importance of sample data. Traditional geostatistical test takes into account both sample points and prior knowledge, but it is insufficient in the comprehensive utilization of prior knowledge information of multi-source data types. Currently, the Bayesian maximum entropy method is widely used in spatial prediction. In some studies, this method has been applied to multi-source data fusion. The advantage of Bayesian maximum entropy test provides a flexible way of data utilization. This method allows multiple sources and types of data sets to be used for spatial analysis of satellite observation scale at the same time, generates high resolution reference map of soil moisture observation field, completes the validation of soil moisture products, and provides a basis for the authenticity test of large-scale soil moisture products. Thus, it would provide a new way for the validation of large-scale soil moisture products.

Key words: soil moisture, validation, Bias maximum entropy