Abstract: Soil moisture products based on remote sensing are crucial for investigating climatic change and hydrological effects on a regional scale. However, there is a lack of verification and application of long-term soil moisture datasets in China due to factors such as inconsistent observation standards and instrument upgrades. Using the agro-meteorological dataset from the China Meteorological Administration and soil moisture data from the International Soil Moisture Network (ISMN), this study constructed a monthly dataset of soil moisture in eastern China covering the period from 1981 to 2013. Accordingly, this study analyzed and compared the performance of four microwave remote sensing-based soil moisture products developed by the European Space Agency’s Climate Change Initiative (ESA CCI): active, passive, combined, and combined adjusted products. The results indicate that active and passive products underestimated and overestimated soil moisture in eastern China, respectively. The maximum deviations from active products were found in the northern and northwestern regions, with relative deviations of -30.9% and -29.6%, respectively. In contrast, the passive products showed relative deviations of 39.1% and 26.5%, respectively for soil moisture in northeastern and northwestern regions. The combined products mitigated the underestimation of the active products and the overestimation of the passive product in these regions, reducing the relative deviations to 24.3% and 3.7%, respectively. Regarding the variation characteristics of regional monthly average soil moisture, both the active and combined products performed best for soil moisture in the Yangtze-Huaihe (YH) region, with the highest correlation coefficient of 0.66. The passive and combined products yielded correlation coefficients of 0.44 and 0.47, respectively for soil moisture in the northeastern region and performed poorly for soil moisture in the northern and northwestern regions. The analysis of the variance sources of the remote sensing-based products indicates that the active products enjoyed more advantages in describing the evolutionary characteristics of soil moisture, the passive products demonstrated greater accuracy, and the combined products yielded the highest accuracy overall. Additionally, this study investigated the impacts of changes in the integrated satellite equipment of CCI on product performance. The results indicate that the active products exhibited consistent performance for soil moisture in the northeastern and northwestern regions in different periods. However, passive sensors still exhibited gaps in reproducing the variations in soil moisture. The combined products exhibited better overall variance than both active and passive products. However, these products yielded comparable correlation coefficients with the active products for soil moisture in the northeastern and northwestern regions. The combined products presented no notable improvement after correction, proving that it is feasible to conduct long-term research using the combined products of CCI. The results of this study contribute to a deeper understanding of the error structures and characteristics of various satellite product datasets, providing evidence for researchers to select appropriate data products and conduct research on long time series.