Analysis of the Relationship between Landuse Changes and Landuse Metrics: the Case Study of Godarchai Watershed

The main aim of the current research was to investigate the existing and future status of land use in the Gadarchai Watershed, one of the sub-basins of the Lake Urmia watershed in West Azerbaijan province. First, Sentinel-2 images were obtained from the European Union's Copernicus website from 2016 to 2022. Then, preprocessing methods were wisely applied in various software environments, and corresponding imagery was sent to the eCognition software environment. Next, a Markov-Chain model (in the TreeSet software setting) was used to predict land-use changes in future years. Finally, the land-cover metrics were calculated using the Fragstats software (version 8.2) at two levels of landscape and classes. The results show that by 2028, agricultural land-use will be 13.89%, dry farming will be 1.14%, residential areas will be 0.33%, and salty flats of Lake Urmia 26%. Also, the salty-soil class will likewise decrease by 10.26%, and grasslands will decrease by 5.35%. According to the results of the land-cover metrics, the highest Edge Density (ED) in 2016, 2022, and 2028 is related to grasslands with values of 36.06, 33.58, and 26.72, respectively, and the lowest value was related to salt edges of the lake 0.01, 0.14, and 0.45. Other examined metrics showed that grassland use had the highest value in most indicators. At the landscape level, the results of the land-cover metrics showed an increasing trend in metrics related to patch cohesion. The final results highlight the preservation of watershed stability against changes. Accordingly, research findings can be employed in the sustainable forthcoming regional planning