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Remote Sens Appl: Soc Environ 13:415–425. Ībuelgasim A, Ammad R (2019) Mapping soil salinity in arid and semi-arid regions using Landsat 8 OLI satellite data. In:MODSIM 2007: International Congress on Modellig and Simulation: land, Water and Environmental Management: Intergrated Systems for Sustainability: 2632–2638.Ību YMA, Biswas RK, Chowdhury AI, Billah SM (2018) Modeling soil salinity using direct and indirect measurement techniques: a comparative analysis. Using remote sensing techniques for appraisal of irrigated soil salinity. In the last 15 years, the soil salinity at depth of 30–40 cm experienced a decreased trend of fluctuating, while the soil salinity at depth of 90–100 cm showed fluctuating increasing trend.Ībbas M A,Khan, S. The soil salinization level of the coastal shoreline was higher in contrast, lower soil salinization level occurred in the central YRD. From 2003 to 2018, the soil salinity showed a distinct spatial heterogeneity. The accuracy of the PLSR model performed better than that of the MLR model, with the R 2 of 0.642, RMSE of 0.283, and MAE of 0.213 at 30–40 cm depth, and with the R 2 of 0.450, RMSE of 0.276, and MAE of 0.220 at 90–100 cm depth.
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The results indicated that the estimates of soil salinity by the optimized prediction model were in good agreement with the measured soil salinity. By comparing multiple linear regression (MLR) and partial least squares regression (PLSR) models with considering the correlation between predictive factors and soil salinity, we established the optimized prediction model which integrated the multi-parameter (including SWIR1, SI9, MSAVI, Albedo, and SDI) optimization approach to detect soil salinization in the YRD from 2003 to 2018. A multi-dimensional model was built for mapping soil salinity, in which five types of predictive factors derived from Landsat satellite images were exacted and tested, 94 in-situ measured soil salinity samples with depths of 30–40 cm and 90–100 cm were collected to establish and validate the predicting model result. In this study, we proposed an optimized remote sensing-based model for detecting soil salinity in different depths across the Yellow River Delta (YRD), China. It is necessary to develop effective methods for monitoring the spatiotemporal distribution of soil salinity at a regional scale. Soil salinization is recognized as a key issue negatively affecting agricultural productivity and wetland ecology.