[1]. Alavipanah, S.K., & Masoudi, M. (2000). Land Use Mapping Using Landsat TM and Geographic Information System (GIS), a Case Study: Mouk Region of Fars Province, Agriculture Science Natural Resources, 8(1), 65-75. (in Farsi)
[2]. Anys, H., Bannari, A., He, D.C., & Morin, D.) 1994(. “Texture analysis for the mapping of urban areas using airborne MEIS-II images,” Proceedings of the First International Airborne Remote Sensing Conference and Exhibition, Strasbourg, France, 3, 231-245.
[3]. Baltsavias, E., Eisenbeiss, H., Akca, D., Waser, L.T., Kuckler, M., Ginzler, C., & Thee, P. (2007). Modelling fractional shrub/tree cover and multi-temporal changes using high-resolution digital surface model and CIR-aerial images, 287-297,
http://www.photogrammetry.ethz.ch/general/perso ns/devrim-pub1.html.
[4]. Breiman, L. (2001). Random forests. Machine learning, 45(1), 5-32.
[5]. Colgan, M.S., Baldeck, C.A., Feret, J.B., & Asner, G.P. (2012). Mapping Savanna Tree Species at Ecosystem Scales Using Support Vector Machine Classification and BRDF Correction on Airborne Hyperspectral and LiDAR Data, Remote Sensing, 4, 3462-3480.
[6]. Erfanifard, S.Y. (2014). Application of ROC curve to assess pixel-based classification methods on UltraCam-D aerial imagery to discriminate tree crowns in pure stands of Brant`s oak in Zagros forests, Forest and Poplar Research, 22(4), 469-663. (in Farsi)
[7]. Fallah, A., Kalbi S., & Shataee Joibary, Sh. (2014). Forest stand types classification using tree-based algorithms and spot-hrg data, Environmental Resources Research, 2(1), 31-46.
[8]. Ghasemi Rozveh, A., Shataee Joibary, Sh., & Mohamadi, J. (2017). Capability investigation of digital aerial Ultra Cam-D images in identifying tree species in the Hyrcanian mixed forests (Case study: Shastkalate forest in Gorgan), Wood & Forest Science and Technology, 24(1), 77-89. (in Farsi)
[9]. Gualtieri, J.A., & Cromp, R.F. (1998). Support Vector Machines for Hyperspectral Remote Sensing Classification, In: Proceedings of the 27th AIPR Workshop: Advances in Computer Assisted Recognition, Washington, D.C., 221-232.
[10].Karami, J., Shataee Joibary, Sh., & Hosseini, S.M. (2010). Capability Assessment of IKONOS Images for Urban Vegetation Mapping, Wood and Forest Science and Technology, 17(2), 89-103. (in Farsi)
[11].Lohrabi, Y., Abbasi, M., Soltani, A., & Riyahi Bakhtyari, H.R. (2018). Determination of the most suitable method for forest type mapping in central Zagros using landsat-8 satellite Images. Forest Research and Development, 4(2), 191-205. (in Farsi)
[12].Ozdemir, I., Norton D. A., Ozkan, U.Y., Mert, A., & Senturk, O. (2008). Estimation of tree size diversity using object–oriented texture analysis and ASTER imagery, Sensors, 8, 4709-4724.
[13].Pouteau, R., Meyer, Y., Taputuarai, R., & Stoll, B. (2012). Support vector machines to map rare and endangered native plants in Pacific islands forests, Ecological Informatics, 9, 37-46.
[14].Rafieyan, O., Darvishsefat, A.A., Babaii, S., & Matajii, A. (2011). Evaluation of pixel-based and object-based classification methods for tree idenstification using aerial images (Case study: a forestation in Camestan-Nur), Forest, 3(1), 35-47. (in Farsi)
[15].Rashidi, M.J., Fattahi, M., Keshavarz Moulaei, S., & Delavar Qashqai, Sh. (2002). Final Report Distribution of different species of Pistachio in Bushehr Province of Iran, Agriculture and Natural Resources Research Center of Bushehr Province, Iran, 18-19. (in Farsi)
[16].Richards, J.A. & Jia, X. (2006). Remote Sensing Digital Image Analysis an Introduction; 4th Edition, Springer, Germany, Berlin, Heidelberg.
[17].Ridd, M.K. & Liu, J., (1998). A Comparison of Four Algorithms for Change Detection in an Urban Environment, Remote Sensing Environment, 63, 95-100.
[18].Shabani Pour, M., Darvishsefat, A., & Rafieyan, O. (2013). Study The Possibility of Identifying Tree Species In Digital Aerial Images Based Object Classification, The Forest and Wood Products, 67(1), 21-32. (in Farsi)
[19].Shataee Joibary, Sh., & Abdi, O. (2007). Land Cover Mapping in Mountainous Lands of Zagros Using ETM+ Data (Case Study: Sorkhab Watershed, Lorestan Province), Agricultural Science Natural Resources, 14(1), 129-139. (in Farsi)
[20].Shataee Joibary, Sh., Darvishsefat, A. A., & Sobhani H. (2007). Comparison of pixel-based and object-based approaches for forest type mapping using satellite data, the Iranian Natural Resources, 60(3), 869-881. (in Farsi)
[21].Soffianian, A., Mohamadi Towfigh, A., Khodakarami, L., & Amiri, F. (2011). Land use mapping using artificial neural network (Case study: Kaboudarahang, Razan and Khonjin- Talkhab catchment in Hamedan province), Applied RS and GIS Techniques in Natural Resource Science 2(1), 114. (in Farsi)
[22].Sohrabi, H. (2009). Application of Visuall and Digital Interpretation in Forest Inventory. Ph.D. Thesis, Faculty of Natural Resources and Marin Science, Tarbiat Modares University, 110p. (in Farsi)
[23].Strobl, R.O., & Forte, F. (2007). Artificial neural network exploration of the influential factors in drainage network derivation, Hydrological processes, 21, 2965–2978.
[24]. Treitz, P.M., & Howarth, P.J. (2000). Integrating spectral, spatial, and terrain variables for forest ecosystem classification, Photogrammetric Engineering and Remote Sensing, 66, 305-317.
[25]. Wang, T., Zhang, H., Lin, H., & Fang, C. (2015). Textural–Spectral Feature-Based Species Classification of Mangroves in Mai Po Nature Reserve from Worldview-3 Imagery, Remote Sensing, 8(24), 1-15.
[26].Wood, E.M., Pidgeon, A.M., Radeloff, V.C., & Keuler, N.S. (2012). Image texture as a remotely sensed measure of vegetation structure, Remote Sensing of Environment, 121, 516–526.
[27].Yu, Q., Gong, P., Clinton, N., Biging, G., Kelly, M., & Schirokauer, D. (2006). Object-Based detailed vegetation classification with airborn high spatial resolution semote sensing imagery, Photogrammetric Engineering and Remote Sensing, 72(7), 799-811.
[28].Yuan, F., Bauer M. E, Heinert, N. J., & Holden, G. R. (2005). Multi-level land cover mapping of thetwin cities (Minnesota) Metropolitan area with multi seasonall and sat TM/ETM+ Data, Geocarto International, 20(2), 5-13.
)