Assessment of Remotely Sensed Indices to Estimate Soil Salinity


1 Assist. Prof., Faculty of Agriculture and Natural Resources, Mahabad Branch, Islamic Azad University, Mahabad, Iran

2 MSc of Agroecology, Mahabad Branch, Islamic Azad University, Mahabad, Iran


Soil Salinization is one of the oldest environmental problems and one of the main
paths to desertification. Access to information in the shortest time and at low cost is
the major factor influencing decision making. The satellite imagery provides
information data on salinity and also offers large amount of data that can be analyzed
and processed to understand several indices based on the type of the sensor used. In
this research, the capability of different indices derived from IRS-P6 data was
evaluated to identify saline soils in Mahabad County. The quality of the satellite
images was first evaluated and no noticeable radiometric and geometric distortion was
detected. The Ortho-rectification of the image was performed using the satellite
ephemeris data, digital elevation model, and ground control points. The RMS error
was less than a pixel. In this study, the correlation between the bands and used indices,
including Salinity1, Salinity2, Salinity3, PCA1 (B2, B3), PCA1 (B4, B5), PCA1 (B1,
B2, B3, B4, B5), Fusion (Pan and B2), Fusion (Pan and B3) and Fusion (Pan and B4)
with EC were investigated. The highest correlation was related to the Fusion (Pan and
B2) with a coefficient 0.76 and the lowest correlation was related to B4 with a
coefficient 0.2. The results showed that the indices have a high ability for modeling,
mapping and estimating the soil salinity.