This research deals with the identification and mapping of salt affected soils inrnMiddle Awash. The analysis was made based on remote sensing data of LandsatrnETM+ image, Electrical conductivity (EC) of soil sample taken in the same year whenrnthe image was captured and some other ancillary data. Remote sensing techniquesrnemployed were visual interpretation, digital image processing and indices likernNormalized Difference Salinity Index (NDSI) and Normalized Difference VegetationrnIndex (NDVI).rnAn attempt has been made to identify salt affected area by visual interpretation usingrnboth TCC and FCC. From the unsupervised and supervised classification1930ha andrn887.3ha areas have been mapped as highly saline. The result obtained fromrnunsupervised classification is larger in area extent. However the result obtained fromrnNDSI was not only in area wise but also the level of salinity as highly saline,rnmoderately and slightly saline, determined based on the reflectance value. Out of therntotal area 10% are mapped as highly saline. Attempt has been made to indirectlyrnidentify salt affected area using NDVI and the result showed similar area distributionrnof salt affected area.rnA regression analysis between EC values of small areas confined only in Melka Sadirnarea and the corresponding reflectance value in the NDSI image offer a polynomialrnrelation of order two. The model obtained used to derive a salinity map and 16 andrn0.9 dS/m of maximum and minimum EC level respectively was estimated. The spatialrndistribution of salt affected area derived from NDSI and model has shown similarrnpattern but different area extent.rnOverlay analysis of salt affected area and soil, canal, drainage and water table hasrnbeen made to assess the spatial distribution as well as the relationship with thisrnfeatures and the result revealed the spatial distribution not highly influenced by thernfeatures being considered.rnKey word: NDSI, EC, Soil salinity