Assessing and Monitoring of land Use Changes in the Zard River Drainage Basin Using Remote Sensing and Markov Chain Model

r optimal land use, it is necessary to be aware of land use changes and the type of land use; this is possible by assessing and predicting land use changes. The purpose of this study is to investigate the trend of land use change over a period of 18 years (2000-2000) and predict it using the Markov chain model for 2025, 2050 in the Yellow River Basin of Baghmalek city in Khuzestan province. To achieve this goal, first corrections (geometric, radiometric and atmospheric) and necessary processing were performed on Landsat satellite images of 2000, 2006, 2012, 2018; Then, land use maps for four time periods were classified into five classes: green space and gardens, barren lands, agricultural lands, water levels (sedgereh) and man-made residential areas. These changes were addressed using the Markov chain model for 2025, 2050. After making the necessary corrections on the Landsat images, the land use estimate showed that the highest percentage of the study area is barren lands and arable lands. The overall accuracy and kappa coefficient for 2000, 2006 and 2018 are above 0.80 and 0.92. .. The results of revealing the changes between the period 2000 to 2018 showed that barren lands with a rate of 823.51, green space and gardens with a decrease of 157.85 hectares. In contrast to the built-up areas of 439.59 hectares, 1356.56 hectares of arable lands and 404.94 hectares of water levels have been facing an increasing trend. Also, the results of the forecast using the CA-Markov model of land changes in the region for 2025 and 2050 showed that if the speed of land use change is the same as in previous years, in 2025 the use of built-up areas will be 1089.54, hectares of arable land. To 1154/52 hectares and surface water use will increase to 666/54; Landscaping and orchards will be reduced to 42/2012, barren land land use to 59,85279 hectares and in 2050 landscaping and orchards land use to be reduced to 192.62 hectares, barren land land use to be reduced to 8438.69 hectares, arable land land use Increase to 1243.73 hectares and surface water use increase to 8959.59 hectares of built-up areas to 1671/98 hectares. By examining land use change, valuable information can be obtained about man-made changes and natural factors. On the other hand, the prediction map derived from the Markov chain model is very important to provide an overview for better management of natural resources.