Spatial Modeling of Soil Salinity Using Remote Sensing, GIS, and Field Data
This study has shown the benefit of using satellite images in generating accurate soil salinity maps. Corn and alfalfa crops were selected as indicators of soil salinity. Five images were acquired from Aster, Ikonos, and Landsat to check the correlation between measured soil salinity and remote sensing data. Observed data was used in conjunction with satellite images. Three models were applied to predict soil salinity from remote sensing: the ordinary least squares model (OLS), spatial autoregressive model (SAR), and modified kriging model. This study has demonstrated a more efficient and accurate way of estimating soil salinity from remote sensing data that should help the efforts toward sustainable agriculture.