Analysis of spatial and temporal variability of soil salinity in the Yellow River delta

Constructing regression models from remote sensing data has become a hot research topic for monitoring soil salinization information, but previous studies have analyzed fewer changes in long time series. Therefore, this study constructed a remote sensing inversion model of soil salinity content based on Landsat 9 OLI multispectral images by machine learning, and validated, compared and optimized it, and then inverted soil salinity content of arable land in 2015, 2018, 2021, and 2024 in the study area based on the optimal model, which provided data support for regional salinization management. Therefore, this study constructed a remote sensing inversion model based on Landsat 9 OLI multispectral images by machine learning method, validated, compared and optimized the model, inverted the soil salinity of cultivated land in the study area in 2015, 2018, 2021, and 2024 based on the optimal model, and analyzed the change of the optimal model in a long time series, which provided data support for the management of regional salinization.