Investigating Changes in the Cover Classes of Shadegan Wetland during 3 Decades (1988-2017)

Shadegan International Wetland is one of the most important environmental assets of the country due to its very high biodiversity and diverse functions. Awareness of wetland changes is one of the basic needs in the proper management and exploitation of this valuable ecosystem. In this regard, remote sensing methods are a useful tool to study and detect changes in wetlands. Therefore, in this study, with the aim of investigating the trend and revealing the changes in Shadegan wetland, Landsat TM, ETM + and OLI satellite images of 1988-1998-2007 and 2017 were used. Three stages of preprocessing, processing and post-processing were performed on the images, Supervised vector classification (SVM) was used and the images were classified into three classes of water, vegetation and without cover or soil. Classification accuracy for images was calculated using two indicators, overall accuracy and kappa. In order to reveal these classes, changes in 9 classes were analyzed. To show the changes, the graph revealing the changes of uses in three time periods was used. The results showed that in the period 1988 to 1998, water area increased by 1.5% in 1998 and vegetation increased by 5% and soil or uncovered area decreased by approximately 7%. Between 1998 and 2007, water area increased by 4% and vegetation decreased by 20%, and soil or uncovered area increased by approximately 15%. In 2017, there was a 7% decrease in water, a 36% decrease in vegetation, and a 30% increase in soil or uncovered area. This study demonstrates the need for immediate attention to the conservation of wetland residual resources for sustainable use for the next generation.