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Remote Sensing for the Detection of Salinized Soil Using a Multispectral Sensor in the Zeravshan River Basin

Author(s): Mbugua Jacqueline Muthoni, Yoshiya Touge, So Kazama, So Kazama, Kenji Tanaka, tanaka kenji.6u

Linked Author(s): Yoshiya Touge, So Kazama, So Kazama, tanaka kenji.6u

Keywords: Aral Sea Basin; Zeravshan river basin; MODIS; Soil salinization;

Abstract: The Aral Sea Basin in Central Asia is a region plagued by a severe water crisis caused by the rapid expansion of irrigated land during the 19th century. This has in turn resulted in some emerging environmental problems including increased soil salinization. In order to understand the problem of salinity in farmlands, this study attempted to detect salinized soil in the Zeravshan river basin in Uzbekistan using satellite analysis. 15 salinity indices computed from MODIS spectral bands were applied. These indices were derived from existing techniques and consist of both the direct and indirect methods of salinized soil detection. Evaluation of Electrical Conductivity (EC) measurements collected from canals in this basin in August 2017 and MODIS reflectance data showed that all bands have a sensitivity to salinity changes. Results show that vegetation indices generally decreased with an increase in salinity, while reflectance indices increased with an increase in salinity. However, all of the indices reviewed had a low correlation with the EC measured. The R2 value for some of the vegetative indices was: 0.0493 for Ratio Vegetative Index (RVI) and 0.0674 for Normalized Difference Vegetative Index (NDVI) while that of Salinity Indices was: 0.1109 for Salinity Index SI2, 0.1001 for Salinity Index S3 and 0.0976 for Salinity Index SI1. These results reflect on the negative impact of salinity on vegetation since the vegetation based indices decreased with an increase in salinity.


Year: 2019

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