Objective  The spatio-temporal variations of soil salt content (SSC) at seasonal and inter-annual scales will be inversed in the Yellow River Delta from 2005 to 2018.

  Method  This study derived 30-m resolution high-frequency surface reflectance data over the Yellow River Delta from 2005 to 2018 with the integration of the Moderate-resolution Imaging Spectroradiometer (MODIS) and Landsat series sensors data via the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM). Based on soil sampling data in 2005 and the Landsat-5 Thematic Mapper (TM) surface reflectance data, a random forest model was established to model the relationship between SSC and spectral reflectance. The model was used to estimate multi-temporal SSC data from 2005 to 2018, based on which the spatio-temporal variations in SSC were analyzed.

  Result  The ESTARFM performed well for deriving Landsat-like reflectance data with an overall uncertainty < 4%. On seasonal scales, SSC showed a downward trend from February to April, with an occasional short-term rise in SSC from March to April. From April onwards, SSC decreased significantly, shown as the increasing proportions of non-saline soils and slightly saline soils. On inter-annual scales, SSC first increased and then decreased from 2005–2018. The highest SSC value appeared in 2009 (4.262 g kg⁻¹), and the lowest SSC value appeared in 2005 (3.604 g kg⁻¹). Since 2009, the area of slightly saline soils has increased significantly, which means a substantial improvement in soil salinization.

  Conclusion  The ESTARFM method can be used for high-frequency SSC mapping, which promotes our understanding towards intra- and inter-annual dynamics of soil salinity.