| Estimation and inversion modeling of salinity of cotton field soil using remote sensing in the Delta Oasis of Weigan and Kuqa Rivers |
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| DOI：10.7606/j.issn.1000-7601.2018.06.37 |
| Key Words: cotton field soil salinity enhanced normalized vegetation index remote sensing inversion the Delta Oasis of Weigan and Kuqa Rivers |
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| Abstract: |
| Based on data from the field sampling and the enhanced vegetation index from Landsat 8 remote sensing images, we tried to construct the salinity inversion estimation model of cotton field soil in the Delta Oasis of Weigan and Kuqa Rivers. Also, the model was used to predict the spatial distribution pattern of soil salinity in the region. The results showed that: (1) By using soil measured salinity and Enhanced Normalized Difference Vegetation Index (ENDVI), a linear model, y=-56.494x+22.687, was constructed with a R2 of 0.886 and RMSE of 0.907. (2) The predicted salinity by the inversion model based on the remote sensing data varied from 9.33 to 26.99 g·kg-1 with an average value of 17.42 g·kg-1 and a standard deviation of 2.30 g·kg-1. Compared the data from the selected 82 sampling points with the predicted results, the predicted results of soil salinity were consistent with the measured results. (3) A spatial distribution map of soil salinity of cotton field in the study area was developed by using the method of geo-statistical analysis. The analysis demonstrated that soil salinity was rising gradually from the interior to the periphery of the oasis. |
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