Estimating soil salinity using satellite remote sensing data and real-time field sampling

This paper presents a new algorithm for estimating the salinity level of soil by using satellite remote sensing data. The study includes a real-time field work performed during the overpass of Landsat-5 satellite on 20/06/2006 over Salt Lake, Turkey. Electrical conductivity (EC) is used as indicator of salinity for developing algorithm by using multiple regression technique. In the image processing step, geometric and radiometric correction procedures are conducted to make satellite remote sensing data comparable with the spectral ground measurements carried out using field spectroradiometer supported by hand-held GPS. Results show that real-time ground and satellite remote sensing data are in good agreement with correlation coefficient values of between 0.92 and 0.97. The developed algorithm gives acceptable and meaningful results with a determination coefficient value of 0.95. Finally, the model is tested at a number of individual sample points, and the test results indicate the validation of the developed model with a R-2 value of 0.75.