Abdelmalik, K. (2018). Role of statistical remote sensing for Inland water quality parameters prediction. The Egyptian Journal of Remote Sensing and Space Science, 21(2), 193-200.
Ansari, M., and Akhoondzadeh, M. (2019). Water Salinity Mapping of Karun Basin Located in Iran Using the Svr Method. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 42, 97-101. https://doi.org/10.5194/isprs-archives-XLII-4-W18-97-2019.
Ansari, M., and Akhoondzadeh, M. (2020). Mapping water salinity using Landsat-8 OLI satellite images (Case study: Karun basin located in Iran). Advances in Space Research, 65(5), 1490-1502.https:// doi.org/ 10.1016/j.asr.2019.12.007.
Baban, S. M. (1997). Environmental monitoring of estuaries; estimating and mapping various environmental indicators in Breydon Water Estuary, UK, using Landsat TM imagery. Estuarine, coastal and shelf science, 44(5), 589-598.
Chang, C.-C., and Lin, C.-J. (2011). LIBSVM: A library for support vector machines. ACM transactions on intelligent systems and technology (TIST), 2(3), 27.
Chen, X.-L., Zhao, H.-M., Li, P.-X., and Yin, Z.-Y. (2006). Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes. Remote sensing of environment, 104(2), 133-146.
Da Silva, I. N., Spatti, D. H., Flauzino, R. A., Liboni, L. H. B., and dos Reis Alves, S. F. (2017). Artificial neural networks. Cham: Springer International Publishing.
Fassnacht, F., Hartig, F., Latifi, H., Berger, C., Hernández, J., Corvalán, P., and Koch, B. (2014). Importance of sample size, data type and prediction method for remote sensing-based estimations of aboveground forest biomass. Remote Sensing of Environment, 154, 102-114.
Holland, J. H. (1975). Adaptation in natural and artificial systems Ann Arbor. The University of Michigan Press, 1, 975.
Karamouz, M., Mahjouri, N., and Kerachian, R. (2004). River water quality zoning: a case study of Karoon and Dez River system. Iran J Environ Healt, 1, 16-27.
Khadim, F. K., Su, H., and Xu, L. (2017). A spatially weighted optimization model (SWOM) for salinity mapping in Florida Bay using Landsat images and in situ observations. Physics and Chemistry of the Earth, Parts A/B/C, 101, 86-101.
Khorram, S. (1985). Development of water quality models applicable throughout the entire San Francisco Bay and delta. Photogrammetric Engineering and Remote Sensing, 51, 53-62.
Lavery, P., Pattiaratchi, C., Wyllie, A., and Hick, P. (1993). Water quality monitoring in estuarine waters using the Landsat Thematic Mapper. Remote Sensing of Environment, 46(3), 268-280.
Mary, L., and Yegnanarayana, B. (2004). Autoassociative neural network models for language identification. Paper presented at the International Conference on Intelligent Sensing and Information Processing, 2004. Proceedings of.
Messner, J. W., Mayr, G. J., and Zeileis, A. (2017). Nonhomogeneous boosting for predictor selection in ensemble postprocessing. Monthly Weather Review, 145(1), 137-147.
Naddafi, K., Honari, H., and Ahmadi, M. (2007). Water quality trend analysis for the Karoon River in Iran. Environmental monitoring and assessment, 134(1-3), 305-312.
Nazeer, M., and Bilal, M. (2018). Evaluation of ordinary least square (OLS) and geographically weighted regression (GWR) for water quality monitoring: A case study for the estimation of salinity. Journal of Ocean University of China, 17(2), 305-310.
Nguyen, P. T., Koedsin, W., McNeil, D., and Van, T. P. (2018). Remote sensing techniques to predict salinity intrusion: application for a data-poor area of the coastal Mekong Delta, Vietnam. International journal of remote sensing, 39(20), 6676-6691.
Pappu, S. M. J., and Gummadi, S. N. (2017). Artificial neural network and regression coupled genetic algorithm to optimize parameters for enhanced xylitol production by Debaryomyces nepalensis in bioreactor. Biochemical engineering journal, 120, 136-145.
Shan, J., Alkheder, S., and Wang, J. (2008). Genetic algorithms for the calibration of cellular automata urban growth modeling. Photogrammetric Engineering and Remote Sensing, 74(10), 1267-1277.
Shareef, M. A., Toumi, A., and Khenchaf, A. (2014). Prediction of water quality parameters from SAR images by using multivariate and texture analysis models. Paper presented at the SAR Image Analysis, Modeling, and Techniques XIV.
Sivanandam, S., and Deepa, S. (2008). Genetic algorithms. In Introduction to genetic algorithms (pp. 15-37): Springer.
Urquhart, E. A., Zaitchik, B. F., Hoffman, M. J., Guikema, S. D., and Geiger, E. F. (2012). Remotely sensed estimates of surface salinity in the Chesapeake Bay: A statistical approach. Remote Sensing of Environment, 123, 522-531.
US Geological Survey (USGS) (2019). Science for a chanding word. Retrieved from https://earthexplorer. usgs.gov/
Vapnik, V. N. (1995). The nature of statistical learning. Theory.
Vuille, M., and Baumgartner, M. F. (1993). Hydrologic investigations in the north Chilean Altiplano using landsat‐MSS and‐TM data. Geocarto International, 8(3), 35-45.
Wang, F., and Xu, Y. J. (2008). Development and application of a remote sensing-based salinity prediction model for a large estuarine lake in the US Gulf of Mexico coast. Journal of Hydrology, 360(1-4), 184-194.
Wang, L. a., Zhou, X., Zhu, X., Dong, Z., and Guo, W. (2016). Estimation of biomass in wheat using random forest regression algorithm and remote sensing data. The Crop Journal, 4(3), 212-219.
Xie, Z., Zhang, C., and Berry, L. (2013). Geographically weighted modelling of surface salinity in Florida Bay using Landsat TM data. Remote sensing letters, 4(1), 75-83.
Yousefi, S., Pourghasemi, H. R., Hooke, J., Navratil, O., and Kidová, A. (2016). Changes in morphometric meander parameters identified on the Karoon River, Iran, using remote sensing data. Geomorphology, 271, 55-64.
Yu, H., and Kim, S. (2012). SVM tutorial—classification, regression and ranking. Handbook of Natural computing, 479-506.
Zhang, C., Xie, Z., Roberts, C., Berry, L., and Chen, G. (2012). Salinity assessment in Northeast Florida bay using Landsat TM data. southeastern geographer, 52(3), 267-281.
Zhao, J., Temimi, M., and Ghedira, H. (2017). Remotely sensed sea surface salinity in the hyper-saline Arabian Gulf: Application to landsat 8 OLI data. Estuarine, Coastal and Shelf Science, 187, 168-177.