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Selection of Best Band Combination for Soil Salinity Studies using ETM+ Satellite Images (A Case study: Nyshaboor Region,Iran)

Authors: Sanaeinejad, S. H.; A. Astaraei, . P. Mirhoseini.Mousavi, M. Ghaemi,

Abstract:

One of the main environmental problems which affect extensive areas in the world is soil salinity. Traditional data collection methods are neither enough for considering this important environmental problem nor accurate for soil studies. Remote sensing data could overcome most of these problems. Although satellite images are commonly used for these studies, however there are still needs to find the best calibration between the data and real situations in each specified area. Neyshaboor area, North East of Iran was selected as a field study of this research. Landsat satellite images for this area were used in order to prepare suitable learning samples for processing and classifying the images. 300 locations were selected randomly in the area to collect soil samples and finally 273 locations were reselected for further laboratory works and image processing analysis. Electrical conductivity of all samples was measured. Six reflective bands of ETM+ satellite images taken from the study area in 2002 were used for soil salinity classification. The classification was carried out using common algorithms based on the best composition bands. The results showed that the reflective bands 7, 3, 4 and 1 are the best band composition for preparing the color composite images. We also found out, that hybrid classification is a suitable method for identifying and delineation of different salinity classes in the area.

Keywords: Soil salinity, Remote sensing, Image processing, ETM+, Nyshaboor

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1332478

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References:


[1] Taghizadeh Mehrjardi.R,Sh. Mahmoodi,M. Taze and E. Sahebjalal.(2008).Accuracy Assessment of Soil Salinity Map in Yazd- Ardakan Plain, Central Iran, Based on Land sat ETM+ Imagery, American-Eurasian J. Agric. & Environ. Sci., 3 (5): 708-712, 2008
[2] Farifteh,J.,Farshad,A.,&GeorgeR.J.(2006).Assessing salt-affected soils using remote sensing, solute modeling, and geophysics.Geoderma,Volume30,3-4,191-206.
[3] Dwivedi.R.S., K. Sreenivas (1998). Delineation of salt-acted soils and waterlogged areas in the Indo-Gangetic plains using IRS-1C LISS-III data. International Journal of Remote Sensing, 19:14, 2739 - 2751
[4] Darvishsefat,A.A; M.H. Damavandi; M. Jafari and G. R. Zehtabiyan (2000). Assessing of Landsat TM images for using in soil salinity classification. Journal of Desert. Vol. 5, No. 2.
[5] Saha, S.K., M.Kudrat, and S.K. Bhan,(1990). Digital processing of land sat TM data for watershed mapping in parts of Aligarh District, Uttar Pradesh, India. International Journal of remote sensing , vol.11:485-492.
[6] Ferna' ndez-Bucesa,.N, C. Siebea, S. Cramb, J.L. Palacio.(2006). Mapping soil salinity using a combined spectral response index for bare soil and vegetation: A case study in the former lake Texaco, Mexico. Journal of Arid Environments65 644-667
[7] Soil and Water Research Institute (SWRI) (2004), Mapping of resources assessment and land potential in Khorasan Razavi. Technical report, Ministry of Agriculture, Tehran, Iran.
[8] Huete.A.,(2004).Remote Sensing for Natural Resources Management and Environmental Monitoring: Manual of remote sensing3 ed., Vol. 4. University of Arizona.