University of Tehran Journal of Natural Environment 2008-7764 74 2 2021 08 23 Evaluation of trend in salt and water changes in the Urmia lake by object-oriented image analysis using satellite imagery Evaluation of trend in salt and water changes in the Urmia lake by object-oriented image analysis using satellite imagery 224 236 83763 10.22059/jne.2021.321811.2206 FA Leila Malekani َAsistant Professor, Department of Civil Engineering, Faculty of Technical and Engineering of Marand, University of Tabriz, Iran Keivan Mohammadzadeh Department of Remote Sensing and GIS, Faculty of Geography and Planning, University of Tabriz, Iran Maryam Maleki Department of Remote Sensing and GIS, Faculty of Geography and Planning, University of Tabriz, Iran Journal Article 2021 04 10 During the past years, under the influence of various factors, the surrounding area of Urmia Lake has been subjected to significant changes followed by emerging saline cores leading to some damaging consequences making this study of importance. Therefore, this study was conducted to investigate the dryness scale resulting in the high levels of saltiness in Urmia Lake. To this purpose, Landsat satellite images were used during different periods of time, 1998 to 2019. The object-oriented approach has been used to process and identify the amount of wet salt mixed with soil and the degree of water receding. Accordingly, the segmentation was accomplished based on scale 15 for Landsat 5/7 images and Scale 150 for Landsat 8 images, having also different types of indices (salinity, brightness, and vegetation) applied to all the images.The results showed that annual changes in the water level of the Lake and wet salt mixed with soil have been considerable. During the years 1998 to 2015, the water bodies' coverage fell up to 32.74 percent shrinking from 5722.83 to 687.718 square kilometers while the wet salt mixed with soil has increased by 30.38 percent. From 2015 onward, due to increased rainfall and preventive measures set to revive the lake, this trend has been reversed resulting in water bodies' coverage increasing by 3502.267 square kilometers and salinity has simultaneously gone at 20.198 percent. The overall accuracy of 0.94 and kappa coefficient of 0.92 were obtained for classification results implying the capability of object-oriented processing in the classification of the surface features using the Landsat imagery. During the past years, under the influence of various factors, the surrounding area of Urmia Lake has been subjected to significant changes followed by emerging saline cores leading to some damaging consequences making this study of importance. Therefore, this study was conducted to investigate the dryness scale resulting in the high levels of saltiness in Urmia Lake. To this purpose, Landsat satellite images were used during different periods of time, 1998 to 2019. The object-oriented approach has been used to process and identify the amount of wet salt mixed with soil and the degree of water receding. Accordingly, the segmentation was accomplished based on scale 15 for Landsat 5/7 images and Scale 150 for Landsat 8 images, having also different types of indices (salinity, brightness, and vegetation) applied to all the images.The results showed that annual changes in the water level of the Lake and wet salt mixed with soil have been considerable. During the years 1998 to 2015, the water bodies' coverage fell up to 32.74 percent shrinking from 5722.83 to 687.718 square kilometers while the wet salt mixed with soil has increased by 30.38 percent. From 2015 onward, due to increased rainfall and preventive measures set to revive the lake, this trend has been reversed resulting in water bodies' coverage increasing by 3502.267 square kilometers and salinity has simultaneously gone at 20.198 percent. The overall accuracy of 0.94 and kappa coefficient of 0.92 were obtained for classification results implying the capability of object-oriented processing in the classification of the surface features using the Landsat imagery. https://jne.ut.ac.ir/article_83763_8ac45c6c63bbd0a4bf0733d0815fe911.pdf