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Based on Landsat and moderate-resolution-imaging spectroradiometer (MODIS) images from 2000 to 2020, this study applied the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) algorithm to obtain similar phenological images for the month of April for the past 20 years. Based on the random forest algorithm, the surface parameters of the salinization were optimized, and the feature space index models were constructed. Combined with the measured ground data, the optimal monitoring index model of salinization was determined, and then the spatiotemporal evolution patterns of salinization and its driving mechanisms in the Yellow River Delta were revealed. The main conclusions were as follows: (1) The derived long-time-series and similar phenological-fusion images enable us to reveal the patterns of change in the dramatic salinization in the year that we examined using the ESTARFM algorithm. (2) The NDSI-TGDVI feature space salinization monitoring index model based on point-to-point mode had the highest accuracy of 0.92. (3) From 2000 to 2020, the soil salinization in the Yellow River Delta showed an aggravating trend. The average value of salinization during the past 20 years was 0.65, which is categorized as severe salinization. The degree of salinization gradually decreased from the northeastern coastal area to the southwestern inland area. (4) The dominant factors affecting soil salinization in different historical periods varied. The research results could provide support for decision-making regarding the precise prevention and control of salinization in the Yellow River Delta.<\/jats:p>","DOI":"10.3390\/rs16173332","type":"journal-article","created":{"date-parts":[[2024,9,9]],"date-time":"2024-09-09T04:15:01Z","timestamp":1725855301000},"page":"3332","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Evolution Patterns and Dominant Factors of Soil Salinization in the Yellow River Delta Based on Long-Time-Series and Similar Phenological-Fusion Images"],"prefix":"10.3390","volume":"16","author":[{"given":"Bing","family":"Guo","sequence":"first","affiliation":[{"name":"School of Civil Engineering and Geomatics, Shandong University of Technology, Zibo 255000, China"}]},{"given":"Mei","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Civil Engineering and Geomatics, Shandong University of Technology, Zibo 255000, China"}]},{"given":"Rui","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,8]]},"reference":[{"key":"ref_1","first-page":"75","article-title":"Driving Force Analysis and Prediction Simulation of Soil Salinization in Coastal Area of Yellow River Delta","volume":"40","author":"Zhao","year":"2024","journal-title":"Chin. 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