Modeling the impacts of Urmia lake drought on soil salinity of agricultural lands in the eastern area of fuzzy object based image analysis approach

Object based image analysis (OBIA) techniques are known as new methods in the domain of remote sensing image processing methods which are having significant potentialities for a variety of applications in pedology sciences. In this regard OBIA known as approach which integrate spectral and spatial pattern of satellite images for obtaining more accurate results. This approach has developed against of pixel based methods which are facing serious challenges due to the similarity index in spectral properties. The main objective of this study is to analyze soil salinity and apply an integrated approach of Fuzzy-object based for monitoring changes in soil characterize in the eastern area of Uremia Lake which has been under an environmental impact of lake drought. For this goal, Landsat 7 satellite images (ETM) of 2000 and Landsat 8 (OLI) satellite image, for 2015 was prepared. In doing so, first pre-processing steps on satellite images were established. Accordingly, soil salinity trends of agricultural croplands in eastern area were evaluated using fuzzy object based image analysis approach. For this goal, we employed the object based features including: NDVI, spectral indices, brightness and NDSI. The results of this research indicated that, significant progress in increasing salinity areas while the soil salinity rate measured up about 21.54 % (833/18 Km2). According to the results, the salty barren lands with positive slope 19.7 % represent a positive growth rate while it has increased from 15.3 % to 35.05 %. Results indicated the critical environmental situation for the agriculture croplands located in the Eastern area of Uremia Lake which requires the attention of decision makers and authorizations in the East Azerbaijan province.