1. Adhikari, K., Minasny, B., Greve, M. B., & Greve, M. H. (2015). Geoderma constructing a soil class map of Denmark based on the FAO legend using digital techniques ☆. Geoderma., 214–215, 101–113.
2. Ahmadi, N. (2018). Assessment of remotely sensed indices to estimate soil salinity. Journal of Radar and Optic Remote Sensing, 2, 55–66.
3. Akramkhanov, A., Martius, C., Park, S. J., & Hendrickx, J. M. H. (2011). Geoderma environmental factors of spatial distribution of soil salinity on flat irrigated terrain. Geoderma., 163, 55–62.
4. Azad, A., Farzin, S., Mousavi, S.-F., Firoozbakht, A., Ghorbani, S., & Heravi, F. (2016). The use of optimized artificial neural network model by the Genetic Algorithm in estimating water salinity parameters (Case study: Gorganrood River). 4th. International Congress on Civil Engineering, Architecture and Urban Development.
5. Biswas, A., & Zhang, Y. (2018). Sampling designs for validating digital soil maps: a review. Pedosphere., 28, 1–15.