One of the main environmental problems which affect extensively the areas in the world is soil salinity. Traditional data collection methods are neither enough for considering this important environmental problem nor accurate for soil studies. Remote sensing data could overcome most of these problems. Although satellite images are commonly used for these studies, however there are still needs to find the best calibration between the data and real situations in each specified area. Landsat satellite (TM & ETM+) images have been analyzed to study soil pollution (Exacerbation of salinity in the soil without the use of abandoned agricultural for a long time) at west of Baghdad city of Iraqi country for the years 1990, 2001 & 2007. All of the three scenes consist six bands (without the thermal band), changes are determined by applying supervised classification (Maximum Likelihood) technique. Then using Raster to Vector (R to V) Transform technique. ArcGIS 9.1 program is used to apply the supervised classification and the R to V transforms techniques in order to determine the results.
University of Baghdad
Digital Repository