Monitoring and Prediction of Land Use/Cover Changes in Shadegan International Wetland, Iran

Quantifying land use/land cover changes is essential to monitor and assess the ecological consequences of human disturbances. Ecological condition and water quality of wetlands are highly related to the landscape characteristics, including land use/land cover (LULC) types and their fractions in the upland and the surrounding landscape. The changing characteristics of LULC in Shadegan International Wetland, Khouzestan Province, Iran, were detected in this study by using the Landsat Satellite images of the years 2001, 2014, and 2017, which were classified using the Artificial Neural Network algorithm. Then by using Land Change Modeler (LCM) in the TerrSet IDRISI software, the future of LULC changes was simulated using six independent variables and the Markov chain method. The results of this study showed that from 2001 to 2017, about 48200 ha of the wetland water was increased and around 50000 ha of saline soils and vegetation area was decreased. However, since this water increase in the wetland was due to the entry of drainage and wastewater, particularly from sugarcane cultivation around the wetland, this increase could significantly alter the hydrology, the water quality of wetland and also, the plant species composition, as compared to historical conditions; mapping these changes requires further investigations and fine scale monitoring studies.