Ahmadi, A., Taranjozar, H. and Kazemi, A. (2019). Surface salinity zonation in saline lands of Bolagh Saveh using geostatistical methods. Nat. Environ. Hazard., 8(19), 1-14. [In Persian]
Ahmadi, Z., Abbasi Kloo, A., Shahabi, M. and Bouali, A. (2020). Comparison of decision tree methods and artificial neural network in predicting soil salinity in the west of Lake Urmia. Destruct. Rehabilit. Nat. Land., 1(1), 82-91 [In Persian].
Akramkhanov, A., Brus, D. J. and Walvoort, D. J. J. (2014). Geostatistical monitoring of soil salinity in Uzbekistan by repeated EMI surveys. Geoderm., 213, 600–607.
Amini, A., Kolahchi, A. A., Al-Ansari, N., Moghadam, M. K., and Mohammad, T. (2019). Application of TRMM precipitation data to evaluate drought and its effects onwater resources instability. Applied Sciences (Switzerland), 9(24) doi:10.3390/app9245377
Azhirabi, R., Kamkar, B. and Abdi, O. (2015). Comparison of different indices adopted from Landsat images to map soil salinity in the army field of Gorgan. J. Soil Manage. Sust. Prod., 5(1), 173-176 [In Persian].
Behnam, V., Gholamalizadeh, A., Rahmanian, M. and Bameri, A. (2019). Investigation of spatial distribution of some physical and chemical properties of soil using Geostatistical methods (Case study: Zabol to Zahedan route). Environ. Water Eng., 5(3), 251-263 [In Persian].
Debeljak, M. and Džeroski, S. (2011). Decision trees in ecological modelling. In: Jopp, F., Reuter, H., Breckling, B. (eds), Modelling complex ecological dynamics. (197-209). Springer, Berlin, Heidelberg.
Foroughifar H., Jafarzadah A. A., Torabi Gelsefidi H., Aliasgharzadah N., Toomanian N. and Davatgar, N. (2010). Spatial variations of surface soil physical and chemical properties on different landforms of Tabriz plain. J. Soil Water Sci., 21(3), 1-21 [In Persian]
Gholami, S., Hosseini, S. M., Mohammadi, J. and Mahini, A. S. (2011). Spatial variability of soil macrofauna biomass and soil properties in riparian forest of Karkhe River. J. Water Soil, 25, 248-257 [In Persian].
Hassani Pak, A. (2010). Geostatistics. University of Tehran Press, 3rd Ed., p 325, Tehran [In Persian].
Hossein Abadi, S., Khozeime Nezhad, H. and Khashei Sioki., A. (2021). Evaluation of gene expression model in spatial prediction of groundwater salinity and comparison with geostatistical models Case Study: Mashhad Plain. Echo. Hydrol., 8(3), 855-866.
Haykin, S. (1994). Neural network: A comprehensive foundation. 2nd Ed. Macmillan. New York.
Isaaks, E. H. and Srivastava, R. M. (1989). An introduction to applied geostatistics: Oxford University Press, 561.
Jahantigh, M. and Jahantigh M. (2019). Study effect of flood productivity on vegetation changes using field work and Landsat satellite images (Case study: Shandak of Sistan region). J. RS GIS Nat. Resour., 10(4), 57-73 [In Persian].
Juan P., Mateu, J. Jordan, M. M, Mataix-Solera, J., Meléndez-Pastor, I. and Navarro-Pedreño. J. (2011). Geostatistical methods to identify and map spatial variations of soil salinity. J. Geochem. Explor., 108, 66-72.
Moonjun, R., Farshad A., Shrestha, D. P. and Vaiphasa, C. (2010). Artificial neural network and decision tree in predictive soil mapping of Hoi NumRin Sub-Watershed, Thailand, Digital Soil Mapping. Prog. Soil Sci., 2(23), 151-164.
Moradian, S., Nabiollahi, K. and Taghizadeh Mehrjerdi, R. (2017). Prediction of soil salinity using tree regression and artificial neural network in Qorveh region of Kurdistan province. Soil Manage. Sustain. Product., 7(4), 115-129 [In Persian].
Nawar, S., Reda, M., Farag, F. and El-Nahry, A. (2011). Mapping soil salinity in El-Tina plain in Egypt using geostatistical approach. Geoinformatics Forum, Salzburg, Austria. 211-216.
Nikbakht Shahbazi, A., Zahraei, B. and Naseri, M. (2012). Seasonal forecast of meteorological drought using support vector machines. Water Wastewater, 2(23), 73-85 [In Persian].
Nikpour, M. R., Thanikhani, H., Mahmoudi Babalan, S. and Mohammadi, A. (2017). Application of SVM, ANN, WNN and GEP models in rainfall-runoff simulation of Khiavachai river. Echo. Hydrol., 4(2), 627-639 [In Persian].
Ranjbar, F. and Jalali, M. (2016). The combination of geostatistics and geochemical simulation for the site-specific management of soil salinity and sodicity. Comput. Electron. Agri., 121, 301-322.
Sharma, V., Negi, S. C., Rudra, R. P. and Yang, S. (2003). Neural networks for predicting nitrate-nitrogen in drainage. Agri. Water Manage., 63, 169–183.
Siasar, H. and Honar, T. (2019). Application of support vector machine models, chad and random forest in estimating daily reference transpiration evaporation in northern Sistan and Baluchestan province. Irrig. Drain. Iran., 2(13), 378-388 [In Persian].
Sitharam, T. G., Samui, P. and Anbazhagan, P. (2008). Spatial variability of rock depth in temperate forests. Geotech. Geol. Eng., 26(5), 503-517.
Sokouti Scoei, R., Mahdian, R. and Mahmoodi, S. H. (2007). Comparing the applicability of semigeostatistc methods to predict the variability of soil salinity, a case study of Uromia plain. Pajuhesh Sajandegi, 74, 90-98 [In Persian].
Soleimani, K., Habibnejad, M., Abkar, A. and Bani Asadi, M. (2006). Analysis of depth, surface and continuity curves using geostatistical methods in arid and semi-arid rainfall areas (D.A.D) Case study: Sirizjan salt pan). J. Desert, 11(1), 32-41 [In Persian].
Taghizadeh, R., Minasny. B., Sarmadian, F. and Malone, P. B. (2016). Digital mapping of soil salinity in Ardakan region, central Iran. Geoderm., 213(56), 15-28.
Wang, Y. and Witten, I. H. (1997). Inducing model trees for continuous classes. In Proceedings of the Ninth European Conference on Machine Learning. 128-137.
Watt, M. and Palmer, S. (2010). Use of regression kriging to develop a Carbon: Nitrogen ratio surface for New Zealand. Geoderm, 183,49-57.
Yu, H., Liu, M, Du, B., Wang, Z., Hu, L. and Zhang, B. (2018). Mapping Soil Salinity/Sodicity by using Landsat OLI Imagery and PLSR Algorithm over Semiarid West Jilin Province, China. Sensor., 18(4), 1043-1017.