Multi-algorithm comparison for predicting soil salinity

• Published in: Geoderma Vol. 365; p. 114211
• Main Authors: Wang, Fei, Shi, Zhou, Biswas, Asim, Yang, Shengtian, Ding, Jianli
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 15.04.2020
• Subjects: Algorithms; biotic factors; China; climatic factors; data collection; dry environmental conditions; Environmental covariates; land degradation; land use; Landsat; monitoring; normal distribution; oases; prediction; Predictive mapping; pruning; Random forest; regression analysis; remote sensing; salinity; soil salinity; Soil salinization; soil types; soil water; surface temperature; temporal variation; uncertainty; vegetation index; China; Environmental covariates; Soil salinization; Random forest; Algorithms; Predictive mapping

•Soil-landscape relationship is dominant factor for accurate predicting soil salinity.•RF was recommended for mapping soil salinity in Xinjiang, China.•No algorithm that is superior for all soil depths.•Best linear and non-linear algorithms were LMSLR and RF.•Complexity of the algorithm did not alwa...