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Microwave remote sensing inversion of soil moisture (SM) products has gained increasing prominence in agricultural, meteorological, hydrological, and other research fields, and analyzing the regional applicability of microwave remote sensing SM data is a crucial prerequisite for their effective utilization. In order to assess the accuracy and applicability of SMAP, ASCAT, and AMSR2 remote sensing SM products in the North China Plain, we employed MERRA2 simulated SM as reference data, the triple collocation (TC) method was utilized to compare and evaluate the daily SM data obtained from remote sensing products in the region. The results of the TC analysis indicate that SMAP SM exhibited superior performance in the North China Plain. The majority of errors had a standard deviation of less than 0.023 m3 / m3, and the cumulative frequency of errors less than 0.027 m3 / m3 approached 1, surpassing ASCAT and AMSR2 overall. Additionally, SMAP exhibited the lowest deviation and root mean square error. The median correlation coefficient was highest for SMAP, followed by AMSR2 and ASCAT. Similarly, the median deviation and root mean square error were lowest for SMAP. The verification results of the evaluation index align with the TC findings. The error standard deviation of SMAP demonstrates the best performance across various land use types. The land use types with the best quality of SMAP, ASCAT and AMSR2 are cultivated land and grassland (low vegetation coverage area), among which ASCAT is better than AMSR2 in cultivated land and grassland. The error of urban construction land is the largest. This study aims to provide a scientific reference for enhancing the inversion algorithm and facilitating the extensive application of data products, and lay the foundation for future research such as im-proving product resolution and drought monitoring.
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