Journal of Geographic Information System

Volume 12, Issue 4 (August 2020)

ISSN Print: 2151-1950   ISSN Online: 2151-1969

Google-based Impact Factor: 1.58  Citations  h5-index & Ranking

Soil Salinity Detection in Semi-Arid Region Using Spectral Unmixing, Remote Sensing and Ground Truth Measurements

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DOI: 10.4236/jgis.2020.124023    195 Downloads   535 Views  


Soil salinity is one of the serious environmental problems ravaging the soils of arid and semi-arid region, thereby affecting crop productivity, livestock, increase level of poverty and land degradation. Hyperspectral remote sensing is one of the important techniques to monitor, analyze and estimate the extent and severity of soil salt at regional to local scale. In this study we develop a model for the detection of salt-affected soils in arid and semi-arid regions and in our case it’s Ghannouch, Gabes. We used fourteen spectral indices and six spectral bands extracted from the Hyperion data. Linear Spectral Unmixing technique (LSU) was used in this study to improve the correlation between electrical conductivity and spectral indices and then improve the prediction of soil salinity as well as the reliability of the model. To build the model a multiple linear regression analysis was applied using the best correlated indices. The standard error of the estimate is about 1.57 mS/cm. The results of this study show that hyperion data is accurate and suitable for differentiating between categories of salt affected soils. The generated model can be used for management strategies in the future.

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Bouaziz, M. , Hihi, S. , Chtourou, M. and Osunmadewa, B. (2020) Soil Salinity Detection in Semi-Arid Region Using Spectral Unmixing, Remote Sensing and Ground Truth Measurements. Journal of Geographic Information System, 12, 372-386. doi: 10.4236/jgis.2020.124023.

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