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yaghobi S, komaki C B, karimzadeh H. Zoning and Studying of the Soil Salinity Trend by using Remote Sensing Data and Land Statistics (Case Study: Segzi Plain, Isfahan). Degradation and Rehabilitation of Natural Land. 2020; 1 (1) :92-104
URL: http://drnl.sanru.ac.ir/article-1-146-en.html
Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran
Abstract:   (1228 Views)
Soil salinity is one of the most important characteristics of the soil. Salinity accumulation is strong in arid areas and it has become a serious environmental problem. Identification and mapping of saline soils often due to temporal and spatial variability and the need for sampling and laboratory work is difficult. In recent decades using geostatistic and remote sensing have been developed for mapping salinity and sodicy of surface soil and monitoring it heir changes. The objective of this research was soil salinity zonation and comparing the capability of geostatistic and remote sensing for mapping soil salinity- in Segzi plain, Esfehan province. For this purpose, 29 soil samples from the study area were randomly sampled and measured the electrical conductivity. TM LandSat 7 images from August 1997 at the same time field sampling were applies to prepare for mapping soil salinity. Then Image processing like image enhancement and PCA were applied on the data. The results indicated that the ordinary kriging (OK) with exponential semivariogram the best method for modeling and interpolating soil salinity. With a significance level analysis and measure study between ground data and output of models, best salinity method selected and extraction soil salinity map. The results showed that the PCA234 method has the highest correlation with the sampling point.  With the results of two periods of 1997 and 2018, it was found that the salinity levels of medium and high classes were reduced in 1997, then in 2018, respectively. Added to the Very high and extreme salinity classes in 2018.
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Type of Study: Research |
Received: 2020/09/12 | Accepted: 2020/11/24 | Published: 2021/01/5

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