MONITORING AND EVALUATION OF SOIL SALINITY IN TERM OF SPECTRAL RESPONSE USING LANDSAT IMAGES AND GIS IN MESOPOTAMIAN PLAIN/ IRAQ

Abstract

Soil Salinity is one of the most important considerations for monitoring soil degradation and continued desertification that threat some regions in Iraq. Remote sensing techniques and GIS operations have been used for multidate image processing to detect and monitor the history changes of soil in the western part of Mesopotamian plain. The aim of this research is to assign the appropriate and effective image processing techniques to be implemented for monitoring, and then to evaluate soil salinity in the term of the corresponding spectral response in the best spectral band. Landsat MSS, TM, and ETM images for the periods 1972, 1990, and 2000 respectively have been selected, as well as ancillary data of the available salinity field measurements have been used. ERDAS (8.5), ENVI (3.6), and ArcGIS (9.2) softwares have been used for the purpose of digital processing, creation of information layers, integration, and statistical correlation. It is concluded that created image brightness and salinity indices indicate the increasing of salt affected soil during the mentioned period of images. And these image indices have the highest correlation coefficient with Mid-IR band. A predictive equation is established to estimate soil salinity in the term of spectral response of Landsat images; the effective relationship is specified at the value above 28 ds/m of Electrical Conductivity (EC), and the obtained correlation coefficient 87 % reaches to 95% when EC values of soil increase to more than 70 dS/m.