[1] Bue, B.D. and Stepinski, T.F. (2006). Automated classification of landforms on Mars. Computers & Geosciences, 32, 604-661.
[2] Dikau, R. (1989). The application of a digital relief model to landform analysis in geomorphology. In: Raper, J. (Ed.), Three Dimensional Applications in Geographical Information Systems. Taylor & Francis, London, pp. 51-77.
[3] Darvishzadeh., A. (1991). Geology of Iran, Amirkabir Press, Tehran, Iran.
[4] Davies, D.L. and Bouldin, D.W. (1979). A cluster separation measure. IEEE Trans. Patt. Anal. Machine Intelligence, 1, 224-227.
[5] Ehsani, A.H. and Quiel, F. (2008). Geomorphometric feature analysis using morphometric parameterization and artificial neural networks. Geomorphology, 99, 1-12.
[6] Ehsani, A.H. and Quiel, F. (2008). Application of self organizing map and SRTM data to characterize yardangs in the Lut desert, Iran. Remote Sensing of Environment, 112, 3284-3294.
[7] Ehsani, A.H. and Quiel, F. (2009). Self-organizing maps for multi-scale morphometric feature identification using shuttle radar topography mission data. Geocarto International, 24, 335-355.
[8] Ehsani, A.H. et al. (2010). Effect of SRTM resolution on morphometric feature identification using neural network-self organizing map. Geoinformatica, 14, 405-424.
[9] Evans, I.S. (1972). General geomorphology, derivatives of altitude and descriptive statistics. In R.J. Chorley (Ed.), Spatial Analysis in Geomorphology (pp. 17-90). London: Methuen & Co. Ltd.
[10] Florinsky, I.V. (1998). Accuracy of local topographic variables derived from digital elevation models. International Journal of Geographical Information Science, 12, 47-61.
[11] Florinsky, I.V. (1998). Combined analysis of digital terrain models and remotely sensed data in landscape investigations. Progress in Physical Geography, 22, 33-60.
[12] Florinsky, I.V. (2002). Errors of signal processing in digital terrain modelling. International Journal of Geographical Information Science, 16, 475-501.
[13] Florinsky, I.V. (2009). Computation of the third-order partial derivatives from a digital elevation model. International Journal of Geographical Information Science, 23, 2: 213-231.
[14] Frankel, K.L. and Dolan, J.F. (2007). Characterizing arid region alluvial fan surface roughness with airborne laser swath mapping digital topographic data. Journal of Geophysical Research-Earth Surface, 112, F02025.
[15] Grebby, S (2010). Lithological mapping of the Troodos ophiolite, Cyprus, using airborne LiDAR topographic data. Remote Sensing of Environment, 114, 713-724.
[16] Hengel. T. and Router, H. (2008). Geomorphometry, Concepts, Software, Applications. Elsevier.
[17] Ji, C.Y. (2000). Land-use classification of remotely sensed data using Kohonen Self- Organizing Feature Map neural networks. Photogrammetric Engineering and Remote Sensing, 66, 1451-1460.
[18] Kohonen, T. (2001). Self Organizing Maps. 3rd Ed. Springer, New York.
[19] Prima, O.D.A., Echigo, A., Yokoyama, R. and Yoshida, T. (2006). Supervised landform classification of Northeast Honshu from DEM-derived the maticmaps. Geomorphology, 78, 373-386.
[20] Saux, E., et al.( 2004). A New Approach for a Topographic Feature-Based Characterization of Digital Elevation Data. GIS’04, 73-81.
[21] Shary, P.A., Sharaya, L.S. and Mitusov, A.V. (2002). Fundamental quantitative methods of land surface analysis. Geoderma, 107, 1-32.
[22] Wood, J. (1996). The Geomorphological Characterization of Digital Elevation Models. Ph.D. Thesis, Department of Geography, University of Leicester, UK.
[23] Zevenbergen, L.W. and Thorne, C.R. (1987). Quantitative analysis of land surface topography. Earth Surface Processes and Landforms, 12, 47-56.