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| DOI：10.13522/j.cnki.ggps.20180134 |
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| Using Remote Sensing to Evaluate Soil Salinization Distribution Over the Irrigation Areas in the Manas River Basin |
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SHI Xiaoyan, LI Weidi, YU Lu, WANG Haijiang*, SONG Jianghui, ZHU Yongqi
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Department of Resources and Environmental Sciences, College of Agronomy, Shihezi University, Shihezi 832000, China
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| Abstract: |
| 【Objective】Remote sensing has been increasingly used in agronomic management and in this paper, we studied the feasibility of using it to estimate saline soil distribution in an irrigation area.【Method】 We took Manas River basin in Xinjiang as an example. Landsat 8 OLI remote sensing data was used to analyze the relationship between NDSI (Normalized Difference Soil Index), Surface Albedo Index (Albedo), Bright, Green, Normalized Difference Vegetation Index (NDVI), Wet, Blue Band (B), Red Band (R), Middle Infrared Band (SWIR1) and Indexes of Ferric Oxide ([IFe2O3]), based on the principal analysis method. The results were then used to construct functional relationship between these indices for soils with different salinization degree. The threshold of soil salinity was determined comparing real salinity measurements and the raster map for soils with different salinization degree, from which the maps of salinized soil were created.【Result】 Comparing the measured data from soil samples and those calculated from the RS data revealed that the accuracy of the estimated soil salinity was approximately 76.42%, of which the accuracy for slightly salinized soil was 68.97%, moderate salinized soil was 76.47%, and severe salinized soil was 83.83%. 【Conclusion】 Combining RS data with measured soil salt content can improve the estimation of salinized soil in large river basins. |
| Key words: soil; salinization; remote sense; principle analysis; evaluate |
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