The datasets used in global research literature to assess the modeling accuracy of remote sensing estimates of soil salinity across various locations.

This study conducted a detailed literature search on remote sensing monitoring of soil salinity using a specific combination of keywords in the Web of Science database. Through the search for "soil salt content (Topic) AND remote sensing (Topic) AND 2000 - 2024 (Year Published)", a total of 227 related papers were retrieved. Similarly, using the keywords "soil salinization (Topic) AND remote sensing (Topic) AND 2000 - 2024 (Year Published)", 477 related papers were acquired. Additionally,
the search for "soil salinity (Topic) AND remote sensing (Topic) AND 2024 (Year Published)" yielded 77 papers. The query "soil salinity (Topic) AND remote sensing (Topic) AND 2000 - 2018 (Year Published)" resulted in 750 papers, while employing "soil salinity (Topic) AND remote sensing (Topic) AND 2019 - 2023 (Year Published)" produced 991 papers. By integrating these search results, a total of 2,522 academic papers related to remote sensing monitoring of soil salinity were identified, covering studies from 2000 to June 2024. For the 2,522 papers on remote sensing salinization, the screening was conducted based on the following criteria: the papers must employ remote sensing technology, use satellite or unmanned aerial vehicle (UAV) data, and estimate surface soil salinity using modeling techniques. Additionally, the papers must provide details on the sampling depth, sensor type and name, sensor spatial resolution, the data volume of both the modeling and validation sets, the model type, the environmental covariates associated with the model, methods of measuring soil salinity, and the R² value of the validation or test set. As a result, 84 papers were selected.