1. Aitkenhead, M.J. and I.H. Aalders. 2008. Classification of Landsat Thematic Mapper Imagery for land Cover Using Neural Networks. Remote Sensing, 29: 2075-2084.
2. Alavipanah, S.K. 2002. Application of Remote Sensing in Earth Science (Soil Science)., University of Tehran Press, 438 pp (in persian).
3. Anderson, J., E. Hardy, J. Roach and R.E. Witmer. 1976. A Land Use and Land Cover Classification System for Use with Remote Sensor Data., Professional Paper 964, United States Government Printing office, Washington.
4. Barati Ghahfarokhi, S., S. Soltani, S.J. Khajeddin and B. Rayegani. 2009. Investigation of Land Use Changes in Qale Shahrokh Basin Using Remote Sensing (1975-2002). Science and Technology of Agriculture and Natural Resources, 13: 349-365 (In persian).
5. Chavez jr, P.S. 1988. An Improved Dark-Object Subtraction Technique for Atmospheric Scattering Correction of Multispectral Data. Remote Sensing of Environment, 24: 459-479.
6. Foody, G.M. 2000. Mapping Land Cover from Remotely Sensed Data with a Softened Feedforward Neural Network Classification. Robotics System, 29: 433-449.
7. Gahegan, M., G. German and G. West. 1999. Improving Neural Network Performance on the Classification of Complex Geographic Datasets. Geographical Systems, 1: 3-22.
8. Gibson, P.J. and C.H. Power. 2000. Introductory Remote Sensing: Digital Image Processing and Applications, Routledge, 249 pp.
9. Imani Harsini, J., M. Kaboli, J. Feghhi, A. Taherzadeh and A. Asadi. 2014. Studying Land Use-Cover Changes During the Last Three Decades in Hamedan Province Using Satellite Images. Natural Environment, 67: 1-12 (In persian).
10. Jianjun, J., Z. Jie, W. Hong’an, A. Li, Z. Hailong, Z. Li and X. Jun. 2005. Land Cover Changes in the Rural-Urban Interaction of Xi’an Regionusing Landsat TM/ETM data. Geographical Sciences, 15: 423-430.
11. Lillesand, T.M. and R.W. Kiefer. 1999. Remote Sensing and Image interpretation. 4th., New York, 724 pp.
12. Lo´pez, E., G. Bocco, M. Mendoza, A. Vela´zquez and J. Rogelio Aguirre-Rivera. 2006. Peasant emigration and land-use change at the watershed level: a gis-based approach in central mexico. Agricultural Systems, 90: 62-78.
13. Lu, D., P. Mausel, E. Brondi´zio and E. Moran. 2004. Change detection techniques. Remote Sensing, 25: 2365-2407.
14. Mallupattu, P.K. and J.R. Sreenivasula Reddy. 2013. Analysis of Land Use/Land Cover Changes Using Remote Sensing Data and GIS at an Urban Area, Tirupati, India. The Scientific World, 2013: 1-7.
15. Mazaheri, M.R., M. Esfandiari, M.H. Masih Abadi and A. Kamali. 2013. Detecting Temporal Land Use Changes Using Remote Sensing and GIS Techniqes (Case Study: Jiroft, Kerman Province). Applied RS & GIS Techniques in Natural Resource Science, 4: 25-39 (In persian).
16. Paola, J.D. and R.A. Schowengerdt. 1997. The Effect of Neural-Networkstructure on a Multispectral Land-USE/Land-Coverclassification. Photogrammetric Engineering & Remote Sensing, 63: 535-544.
17. Poulami, P. and B. Bindu. 2012. A Spatio-Temporal Land Use Change Analysis of Waghodia Taluka Using Rsand GIS. Geoscience Research, 3: 96-99.
18. Rasouli, A.A . 2009. Principles of Applied remote Sensing, Presses Universitaires de Tabriz, Tabriz, 777 pp (In persian).
19. Sanjari, S. and N. Boroomand. 2013. Land Use/Cover Change Detection in Last Three Decades Using Remote sensing Technique (Case Study: Zarand Region, Kerman Province). Applied RS & GIS Techniques in Natural Resource Science, 4: 57-67 (In persian).
20. Sehgal, S. 2012. Remotely Sensed Landsat Image Classification Using Neuralnetwork Approaches, Engineering Research and Applications, 2: 043-046.
21. Seto, K., R. Kaufmann and C. Woodcock. 2002. Monitoring Land Use Change in the Pearl River Delta Using Landsat TM. Remote Sensing, 23: 69-90.
22. Sundarakumar, K., M. Harika, S.A. Begum, S. Yamini and K. Balakrishna. 2012. Land Use and Land Cover Change Detection and Urban Sprawl Analysis of Vijayawada City Using a Landsat Data. Engineering Science & Technology, 4: 170-178.
23. Aitkenhead, M.J. and I.H. Aalders. 2008. Classification of Landsat Thematic Mapper Imagery for land Cover Using Neural Networks. Remote Sensing, 29: 2075-2084. [
DOI:10.1080/01431160701373739]
24. Alavipanah, S.K. 2002. Application of Remote Sensing in Earth Science (Soil Science)., University of Tehran Press, 438 pp (in persian).
25. Anderson, J., E. Hardy, J. Roach and R.E. Witmer. 1976. A Land Use and Land Cover Classification System for Use with Remote Sensor Data., Professional Paper 964, United States Government Printing office, Washington.
26. Barati Ghahfarokhi, S., S. Soltani, S.J. Khajeddin and B. Rayegani. 2009. Investigation of Land Use Changes in Qale Shahrokh Basin Using Remote Sensing (1975-2002). Science and Technology of Agriculture and Natural Resources, 13: 349-365 (In persian).
27. Chavez jr, P.S. 1988. An Improved Dark-Object Subtraction Technique for Atmospheric Scattering Correction of Multispectral Data. Remote Sensing of Environment, 24: 459-479. [
DOI:10.1016/0034-4257(88)90019-3]
28. Foody, G.M. 2000. Mapping Land Cover from Remotely Sensed Data with a Softened Feedforward Neural Network Classification. Robotics System, 29: 433-449.
29. Gahegan, M., G. German and G. West. 1999. Improving Neural Network Performance on the Classification of Complex Geographic Datasets. Geographical Systems, 1: 3-22. [
DOI:10.1007/s101090050002]
30. Gibson, P.J. and C.H. Power. 2000. Introductory Remote Sensing: Digital Image Processing and Applications, Routledge, 249 pp.
31. Imani Harsini, J., M. Kaboli, J. Feghhi, A. Taherzadeh and A. Asadi. 2014. Studying Land Use-Cover Changes During the Last Three Decades in Hamedan Province Using Satellite Images. Natural Environment, 67: 1-12 (In persian).
32. Jianjun, J., Z. Jie, W. Hong'an, A. Li, Z. Hailong, Z. Li and X. Jun. 2005. Land Cover Changes in the Rural-Urban Interaction of Xi'an Regionusing Landsat TM/ETM data. Geographical Sciences, 15: 423-430. [
DOI:10.1007/BF02892149]
33. Lillesand, T.M. and R.W. Kiefer. 1999. Remote Sensing and Image interpretation. 4th., New York, 724 pp.
34. Lo´pez, E., G. Bocco, M. Mendoza, A. Vela´zquez and J. Rogelio Aguirre-Rivera. 2006. Peasant emigration and land-use change at the watershed level: a gis-based approach in central mexico. Agricultural Systems, 90: 62-78. [
DOI:10.1016/j.agsy.2005.11.001]
35. Lu, D., P. Mausel, E. Brondi’zio and E. Moran. 2004. Change detection techniques. Remote Sensing, 25: 2365-2407. [
DOI:10.1080/0143116031000139863]
36. Mallupattu, P.K. and J.R. Sreenivasula Reddy. 2013. Analysis of Land Use/Land Cover Changes Using Remote Sensing Data and GIS at an Urban Area, Tirupati, India. The Scientific World, 2013: 1-7. [
DOI:10.1155/2013/268623]
37. Mazaheri, M.R., M. Esfandiari, M.H. Masih Abadi and A. Kamali. 2013. Detecting Temporal Land Use Changes Using Remote Sensing and GIS Techniqes (Case Study: Jiroft, Kerman Province). Applied RS & GIS Techniques in Natural Resource Science, 4: 25-39 (In persian).
38. Paola, J.D. and R.A. Schowengerdt. 1997. The Effect of Neural-Networkstructure on a Multispectral Land-USE/Land-Coverclassification. Photogrammetric Engineering & Remote Sensing, 63: 535-544.
39. Poulami, P. and B. Bindu. 2012. A Spatio-Temporal Land Use Change Analysis of Waghodia Taluka Using Rsand GIS. Geoscience Research, 3: 96-99.
40. Rasouli, A.A . 2009. Principles of Applied remote Sensing, Presses Universitaires de Tabriz, Tabriz, 777 pp (In persian).
41. Sanjari, S. and N. Boroomand. 2013. Land Use/Cover Change Detection in Last Three Decades Using Remote sensing Technique (Case Study: Zarand Region, Kerman Province). Applied RS & GIS Techniques in Natural Resource Science, 4: 57-67 (In persian).
42. Sehgal, S. 2012. Remotely Sensed Landsat Image Classification Using Neuralnetwork Approaches, Engineering Research and Applications, 2: 043-046.
43. Seto, K., R. Kaufmann and C. Woodcock. 2002. Monitoring Land Use Change in the Pearl River Delta Using Landsat TM. Remote Sensing, 23: 69-90. [
DOI:10.1080/01431160110075532]
44. Sundarakumar, K., M. Harika, S.A. Begum, S. Yamini and K. Balakrishna. 2012. Land Use and Land Cover Change Detection and Urban Sprawl Analysis of Vijayawada City Using a Landsat Data. Engineering Science & Technology, 4: 170-178.