Document Type : Research Paper



This research was done in order to submit a model for salinity map made with TM satellite data and salinity values in a Buienzahra. The necessary processings such as principal component analysis and producing of different indices was done on the main bands. The 38 soil samples using random sampling (with 10×10 km dimension) from different horizons were designed and performed on the study area. The position of each node was registered with global positioning system (GPS), and the surface electric conductivity of samples was measured using EC meter instrument in soil saturation extract. Correlation between spectral values (main bands, produced indices) with electrical conductivity values were investigated for 80% of the samples. The regression analysis of ECe showed that there is a significant correlation between ECe with spectral data in all of main bands and with BI, NDMI, SI1, SI2, SI3 indices in 99% levels. The accuracy assessment of estimations using validation 20% samples was done. Results showed the produced ECe model could predict the soil salinity with ME and RMSE of 0.08 and 2.53 dS/m respectively. At finally, Salinity map with different salinity classes ( 0-2, 2-4, 4-16, 16-32, 32< dS m-1) was produced.


[1] Abdinam, A. (2004). An investigation on preparing of the soil salinity map using correlation method between imagery and soil salinity data in the Qazvin plain, Journal of Pazhouhesh and Sazandegi, 64, 33-38.
[2] Abdel-Hamid, M.A., Sherestha, D. and Valenzuela, C. (1992). Delineating, Mapping and Monitoring of Soil Salinity in the Northern Nile Delta (Egypt). Using Landsat Data and a Geographic Information System, Egypt, J. Soil Sci, 32,(3).
[3] Alavi Panah, S.K. (2000). Investigation and evaluation of the use of the soil salinity map, Journal of desert, 5, 1-15.
[4] Amini, M. (1999). Geostatistical assessment of soil salinity and alkalinity in selected soils from Rudasht area, M.Sc. thesis of pedology, Isfahan University of technology, College of Agriculture, Department of Soil Science, 119p.
[5] Brunner, P.H.T.L. and Kinzelbach, W. (2007). Generating soil electrical conductivity maps at regional level by integrating measurements on the ground and remote sensing data, International Journal of Remote Sensing, 28(15), 3341-3361.
[6] Darvishsefat, M., Jafari, M. and Zehtabian, Gh. (1999). Study on feasibility salt affected soil classification by Landsat Imagery, Journal of desert, 5(2).
[7] Dwivedi, R.S. and Rao, B.R.M. (1992). The selection of the best possible Landsat TM band combination for delineating salt-affected soils, International Journal of Remote Sensing, 13, 2051-2058.
[8] Hillel, D. (2000). Salinity management for sustainable irrigation: integrating science, environment and economics, The World Bank: Washington,. D.C.
[9] Jafari Gorzin, B. (2002). Study of landsat ETM+ capability in detecting salt affected lands (a case study in Gorgan Plain), A thesis of presented for M.Sc. Gorgan university of Agriculture and Natural Resource Science, College of Range and Watershed Management, 127p.
[10] Metternicht, G.I. and Zinck, J.A. (1997). Spatial discrimination of salt- and sodium affected soil surfaces, International Journal of Remote Sensing, 18, 2571-2586.
[11] Noroozi, A.A. (2011). A model for soil salinity prediction integrated multi spatial-temporal satellite imagery with spatial statistic model, Ph.D. thesis. Tarbiat Modares University, 172 pp.
[12] Postel, S. (1999). Pillar of Sand: Can the Irrigation Miracle Last? W.W. Norton and Co., New York, NY.
[13] Saleh, A. A-H. (2009). Remote sensing of soil salinity in arid areas in Saudi Arabia, International Journal of Civil & Environmental Engineering IJCEE-IJENS.
[14] Tajgardan, T., Ayoubi, SH., Shataii, SH. and Khormali, F. (2009). Mapping soil surface salinity using remote sensing data of ETM+ (Case study: North of Agh Ghala, Golestan Province), Water and Soil Conservation Journal, 16(2).
[15] Tajgardan, T., Ayoubi, S., Shataee, S. and Sahrawat, K.L. (2010). Soil Surface Salinity Prediction Using ASTER Data: Comparing Statistical and Geostatistical Models, Australian Journal of Basic and Applied Sciences, 4(3): 457-467.
[16] Verma, K.S., Saxena, R.K., Barthwal, A.K. and Deshmukh, S.N. (1993). Remote Sensing Technique for Mapping Salt Affected Soils, Int. J. Remote Sensing, 15(9).