Abstract: Soil moisture, as a strong indicators for soil water content, is a critical element for crop growth in Hebei Plain, one of the main crop production bases in Hebei Province. Scientific monitoring of soil relative moisture in Hebei Plain is vital for sustainable development of agriculture in the province. With respect to research on soil relative moisture monitoring, a series of soil relative moisture inversion models have been established. Inversion models based on thermal inertia and temperature vegetation index have been the most widely used models in recent years. However, the single use of any inversion model has always posed certain limitations in application scope. In terms of the advantages and disadvantages of the above two models, this paper used MODIS data and measured soil relative moisture data to retrieve soil moisture in Hebei Plain by integrating Apparent Thermal Inertia (ATI) model and Temperature Vegetation Dryness Index (TVDI) model. NDVI was employed as the division factor in March, April, May, October and November. TVDI model was used in area with NDVI > 0.2 for each ten days; in the area withNDVI ≤ 0.2, ATI model was used. TVDI model was used alone to retrieve soil relative moisture in June, July, August and September. Because of low vegetation coverage and missing measured soil relative moisture data in January, February and December, ATI model was used to invert soil relative moisture. The models were tested through P value, which was generally less than 0.01 for all the models. The retrieval results showed that soil relative moisture in Hebei Plain had two cycles, which changed from increasing to decreasing in the year. In the first cycle, from December to June of the next year, soil relative moisture increased from December to March and then decreased from March to June, with the maximum value in March. In the second cycle, from June to December, soil relative moisture increased from June to August and then decreased from August to December, with the peak value in August. While the average annual maximum value was in August, the average annual minimum value was in June. The spatial distribution of soil relative moisture was influenced mainly by precipitation, irrigation and land use patterns. During the same period, soil relative moisture in the east Hebei Plain and coastal plain in Cangzhou was relatively higher than that in other regions of the plain. The soil relative moisture in the piedmont plains of Taihang Mountain and Yanshan Mountain was relatively higher in spring. The point-to-point validation of three representative months (May, July, October) showed that the average relative errors of retrieval results were 21.4%, 19.25% and 22.22%, respectively, consistent with what was in the literature. The study showed that soil relative moisture from remote sensing inversion was in good correlation with field-measured data. The average relative error of the union of ATI and TVDI models was less than those from separate ATI and TVDI model.