Detection of soil salinity changes and mapping land cover types based upon remotely sensed data
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ORIGINAL PAPER
Detection of soil salinity changes and mapping land cover types based upon remotely sensed data Hamid Reza Matinfar & Sayed Kazem Alavi Panah & Farhad Zand & Kamal Khodaei
Received: 5 February 2011 / Accepted: 22 August 2011 / Published online: 4 September 2011 # Saudi Society for Geosciences 2011
Abstract Soil salinity is a major environmental hazard. The global extent of primary and secondary salt affected soils is about 955 and 77 Mha, respectively. Soil salinity tends to increase in spite of considerable effort dedicated to land reclamation. This requires careful monitoring of the soil salinity status. The objectives of this study were: (a) to evaluate the capability of thematic mapper (TM) and multispectral scanner (MSS) imagery for mapping land cover types, (b) to analyse the spectral features of sail crusts relative to bare soil and gravely soil surface conditions, and (c) to detect the soil salinity changes during the period 1975–2004 in the Ardakan area located in the central Iranian Deserts. The Landsat MSS and TM on two different dates of September 14, 1975 and September 11, 2004, respectively, were used. Due to great confusion between some classes, the TM 6 was included in the band combination. The result of the image classification based on the combination of TM bands 3, 4, 5, and 6 showed of
H. R. Matinfar (*) Soil science Department, Collage of Agriculture, Lorestan University, Khoramabad, Iran e-mail: [email protected] S. K. Alavi Panah Cartography Department, College of Geography, Tehran University, Tehran, Iran F. Zand Department of geography, Mysore University, Mysore, India K. Khodaei Research Institute of Applied Science (ACECR), Tehran, Iran
the classification results. For multi-temporal analysis, both TM and MSS images were classified with the same method but with a different number of training classes. The TM-classified image was regrouped to make it comparable with MSS regrouped classified image. The comparison between the classified images showed about 39% of the total area had changed in 29 years. The result of this study revealed the possibility of detecting important soil salinity changes by using Landsat satellite data Keywords Image classification . Soil salinity . Change detection . Surface crust . TM imagery . Landsat MSS imagery
Introduction In the future, more dry lands will be put into agricultural production. This will mainly be achieved with irrigation and will expand the salinization hazard. Desertification has attracted wide concerns since hundreds of millions of people in the world are affected by manifestations of desertification such as soil salinity and soil erosion. Properties of top soils are highly related to land degradation. In arid area, wind and water erosion strongly affects top soil grain size. Rain crust is formed by raindrops, which cause a segregation of fine particles at the surface of the soil. This can increase runoff and lead to soil erosion (Ben-Dor 2001). The crust in effect is more pronounced in saline soil and has been well studie
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