Ahmadi, M., Sefyaniyan, A., khajedin, j. 1388. Preparation of land cover map of Arak city using artificial neural network classification methods and maximum likelihood. Physical Geography Research, 69(9), 31-44. (In Farsi)##Ahuja, R.L. 1993. Utilization of remote sensing date for the study taxonomic units of the Ghagger river basin of Hurgama and Punjab (India). Proceedings of the 14 Asian Conference Remote Sensing, P.2-1 PP, Acrs, 1993.##Alavi Panah, K. 2003. Application of Remote Sensing in Earth Sciences (Soil Sciences), University of Tehran Press, No. 2640. (In Farsi)##Amiri, F., Tabatabayi, T. 1399. Classification and analysis of land use change trends in urban environment using Landsat multi-time images: A case study in Bushehr region. Land management, 25(79), 42-58. (In Farsi)##Arokhi, S., Najafi, A. 1391. Evaluating the efficiency of support vector machine algorithm in land cover classification (Case study of Manesht and Qalarang protected area in Ilam province). The first national conference on environmental protection and planning. Tehran. (In Farsi)##Chen, Z., Wang, L., Wei, A., Gao, J., Lu, Y., Zhou, J. 2019. Land-use change from arable lands to orchards reduced soil erosion and increased nutrient loss in a small catchment. Science of the Total Environment, 648, 1097-104.##Dontree. S. 2003. Land use dynamics from multitemporal remotely - sensed date: a case study Northern Thailand. Proceedings of Map Asia. Malaysia.##Ganjalikhani, M., Delgarm, S., Ghaderi, K. 2013. Using the support vector machine method in calculating daily evapotranspiration. First National Conference on Water Consumption Optimization. Gorgan University of Agricultural Sciences and Natural Resources. (In Farsi)##Hasmadi M, Pakhriazad H and Shahrin M. 2017. Evaluating supervised and unsupervised techniques for land cover mapping using remote sensing data. Geografia-Malaysian Journal of Society and Space, 5(1), 132-147.##Huang, C., B. Wylie, L. Yang, C. Homer and G. Zylstra. 2002. Derivation of a tasseled cap transformation based on Landsat 7 at satellite reflectance. International Journal of Remote Sensing. 23, 1741- 1748.##Kia, S. 2017. Soft Computing in MATLAB. Kian Rayaneh Sabz Publications, 624 pp. (In Farsi)##Lefsky, M. A. and W. B. Cohen. 2003. Selection of remotely sensed data. In M. A. Wulder and S. E. ##Franklin (Eds), Remote Sensing of Forest Environments: Concepts and case studies. pp. 13–46, Kluwer Academic Publishers, Boston, USA.##Lu. D. and Q. Weng. 2007. A survey of image classification methods and techniques for improving classification performance. International Journal of Remote Sensing, 28 (5), 823–870.##Mather, P. M. 2005. Computer processing of remotely–sensed images, 3rd Ed, John Wiley & Sons, Ltd. pp.319.##Moradi, H.R., Fazelpour, M.R., Sadeghi, S.H.R., and Hossieni, S.Z. 2008. The study of land use change on desertification using remote sensing in Ardakan area. Iranian Iranian Journal of Range and Desert Research, 15, 1-12.##Noble, W.S. 2006. What is a support vector machine? Nature Biotechnology, 24(12), 1565-1567.##Nosakhare, O.K., Aighewi, I.T., Chi, A.Y., Ishaque, A.B., Mbamalu, G., 2012. Land useland cover changes in the lower Eastern Shore watersheds and coastal bays of Maryland: 1986-2006. Journal of Coastal Research, 28, 54-62.##Ojigi, L.M. 2006. Analysis of spatial variations of Abuja land use and land cover from image classification algorithms. In Proceedings of the ISPRS Commission VII Mid-term Symposium Remote Sensing: From Pixels to Processes. Enschede, The Netherlands.##Paneque-Gálvez, J., Mas, J. F., Moré, G., Cristóbal, J., Orta-Martínez, M., Luz, A. C., Guèze, M., Macía, M. J., Reyes-García, V. 2013. Enhanced land use/cover classification of heterogeneous tropical landscapes using support vector machines and textural homogeneity, International Journal of Applied Earth Observation and Geoinformation, 23, 372–383.##Saunders, C., Stitson M.O., Weston J., Bottou L., Scholkopf B., Smola A. 1998. Support Vector Machine Reference Manual. Royal Holloway Technical Report CSD-TR-98-03, published by Royal Holloway.##Solani, A., Soltani, M. 1397. Application of Landsat Satellite Images and Artificial Neural Network Algorithm in Investigating Land Use Changes in Ilam Dam Basin. Desert Ecosystem Engineering, 7(19), 33-46. (In Farsi) ##Vapnik, V., and Chervonenkis A. Theory of Pattern Recognition, Nauka, Moscow, Russia, 1995.##Wolberg. G. 1990. Digital image warping. Los Alamitos, CA: IEEE Computer Society Press, pp. 318.##Yin H, Pflugmacher D, Li A, Li Z and Hostert P. 2018. Land use and land cover change in Inner Mongolia-understanding the effects of China’s re-vegetation programs. Remote Sensing of Environment, 204, 918- 930.##Zobeyri, M., Majd, A. 1385. Familiarity with remote sensing and application in natural resources. University of Tehran Press, 317 pp. (In Farsi)##Zoungrana, B.J., Conrad, C., Thiel, M., Amekudzi, L.K. and Da, E.D. 2019. MODIS NDVI trends and fractional land cover change for improved assessments of vegetation degradation in Burkina Faso, West Africa. Journal of Arid Environments, 153, 66-75.##
