Assessment and prediction of land use and land cover change by using of GIS and remote sensing techniques (Case study: Ahvaz city)

Studying the changes and destruction of resources in previous years, and possibility-evaluation and prediction of these changes in subsequent years, could be a significant step in the planning and efficient use of resources, and controlling and containment of the unprincipled changes in future. This study aims to assessment and predicting changes in land use and land cover in the city of Ahvaz. In doing so, Remote Sensing Data, including Landsat TM satellite images of the years 1997, the ETM+ of 2009 and OLI image of 2021 have been used. After accomplishing the needed preprocessing, satellite images were processed and classified through choosing the appropriate training areas. For the Change Assessment, post-classification comparison method was used, and tables and maps of changes were prepared. General changes in the 24-year period is such that the space of built-up areas, with 6 square kilometers rate of growth per year, have been increased from 100/27 square kilometers to 230/33 square kilometers. The extension of the countryside had been associated with the destruction of Barren lands and agricultural, and the agricultural usage had been increased from 951/52 square kilometer in 1997 to 957/26 in 2021. Modeling has been performed through using CA-Markov models. These results are demonstrating the appropriate ability of CA-Markov model in modeling and predicting changes. Thereafter, the land cover map for 2033 was simulated with CA-Markov model.Studying the changes and destruction of resources in previous years, and possibility-evaluation and prediction of these changes in subsequent years, could be a significant step in the planning and efficient use of resources, and controlling and containment of the unprincipled changes in future. This study aims to assessment and predicting changes in land use and land cover in the city of Ahvaz. In doing so, Remote Sensing Data, including Landsat TM satellite images of the years 1997, the ETM+ of 2009 and OLI image of 2021 have been used. After accomplishing the needed preprocessing, satellite images were processed and classified through choosing the appropriate training areas. For the Change Assessment, post-classification comparison method was used, and tables and maps of changes were prepared. General changes in the 24-year period is such that the space of built-up areas, with 6 square kilometers rate of growth per year, have been increased from 100/27 square kilometers to 230/33 square kilometers. The extension of the countryside had been associated with the destruction of Barren lands and agricultural, and the agricultural usage had been increased from 951/52 square kilometer in 1997 to 957/26 in 2021. Modeling has been performed through using CA-Markov models. These results are demonstrating the appropriate ability of CA-Markov model in modeling and predicting changes. Thereafter, the land cover map for 2033 was simulated with CA-Markov model.