【Objective】Soil salinization, one of the most critical ecological problems in agriculture, is a progressive soil degradation process that reduces soil quality and hence crop yield and agricultural production. Therefore, it is necessary to monitor soil salinity for prevention and mitigation of land degradation in the arid regions. Producers and decision-makers also require updated accurate soil salinity maps of agronomically and environmentally relevant regions. 【Method】A total of 147 soil samples were collected from the Ebinur Lake wetland, Xinjiang Uyghur Autonomous Region of China, during the rainy season (May) and dry season (September) in 2017 for analysis of electrical conductivity (EC) when prepared into suspensions, 1:5 in soil and distilled water ratio, and for acquisition of Vis-NIR (visible-near infrared) reflectance spectra in the laboratory. Spectra were resampled in line with Landsat8 OLI sensor’s resolution, i.e., band 1 (Coastal) 433～453 nm, band 2 (Blue) 450～515 nm, band 3 (Green) 525～600 nm, band 4 (Red) 630～680 nm, band 5 (Red) 845～885 nm, band 6 (SWIR 1) 1 560～1 660 nm, and band 6 (SWIR 7) 2 100～2 300 nm. Furthermore, NDSI (Normalized Difference Vegetation Index), SI (Salinity Index), SI1 (Salinity Index 1), SI2 (Salinity Index 2), SI3 (Salinity Index 3), S1 (Salinity Index, S1)、S2 (Salinity Index), S3 (Salinity Index), S5 (Salinity Index), S6 (Salinity Index), Int1 (Intensity Index 1), Int2 (Intensity index 2) and COSRI (Combined Spectral Response Index) were also calculated in this study. A quantitative estimating model was constructed based on partial least squares regression (PLSR), and evaluated in light of its root mean square error (RMSE), determination coefficient (R²) and ratio of performance to deviation (RPD). 【Result】Results show that the surface soil of the Ebinur lake wetland was strongly salt-affected, with soil salinity during the rainy season (23.90 mS•cm^-1) being much higher than that during the dry season (11.62 mS•cm^-1). 2) The PLSR model based on resampled spectral data and 13 spectral indexes performed quite ideally in predicting soil EC in the study area, with quite high accuracy (R² = 0.91, RMSE = 6.48 mS•cm^-1, and RPD = 2.45), which indicates that the model constructed in the study could be used to predict quantitatively EC in the Ebinur Lake wetland; and 3), the areas of slightly saline soil and saline soil decreased, while those of moderately and heavily salinized soils increased during the study period (from May to September). 【Conclusion】In the present study, the model, established by combining two types of remote sensing data different in resolution, has obviously improved the traditional optical remote sensing (Landsat8 OLI) model in precison, as well as elevated the Vis-NIR spectral data to the pixel scale, thus providing certain scientific reference for remote sensing extraction of soil salinity information. The performance of Vis-NIR-based prediction of soil salinity might be affected by adsorption capacity of soluble salts in these electromagnetic ranges being lower than that of: water, soil iron, organic matter, certain types of clay minerals, and some other soil components. To further improve the prediction accuracy, further efforts should be done to define the most dominated factor affecting spectral reflectance of soils different in salinity degree.