Classification and Assessment of the land use changes using Landsat satellite imagery (Case Study: Rey Plain)

Subject Areas : environmental management

pegah mohammadpour ¹ ( PH. D Student Department of Environmental Management, Department of Natural Resources and Environment, Science and Research Branch, Islamic Azad University, Tehran, Iran. )
reza Arjmandi ² ( Associate Professor, Department of Environmental Management, Department of Natural Resources and Environment, Science and Research Branch, Islamic Azad University, Tehran, Iran .*(Corresponding Author) )
Amir Hesam Hasani ³ ( Professor of Environmental Engineering, Department of Natural Resources and Environment, Science and Research Branch, Islamic Azad University, Tehran, Iran. )
Jamal Ghoddousi ⁴ ( Associate Professor, Faculty Member of Soil and Watershed Management Institute. Tehran, Iran. )

Received: 2022-04-17 Accepted : 2022-06-29 Published : 2022-09-23

Keywords: Rey Plain, maximum likelihood algorithm, Remote sensing, Supervised Classification, land use,

Abstract :

Background and Purpose :Land use change due to human activities is one of the important issues in regional and development planning. Lack of attention to land use changes in recent decades has created many environmental problems such as pollution of water resources, soil, etc. Therefore, the study and analysis of land use at different scales with the aim of sustainable development in the proper management of the environment and natural resources is essential. Remote sensing and GIS provide the necessary and sufficient facilities for extracting and updating land use maps and determining its amount. This study aims to investigate changes in land use conversion using remote sensing technology and satellite images for four periods It has been done for 3 years, from 2008 to 2020 in Rey plain. Material and Methodology: TM and OLI satellite images of Landsat 5 and 8 satellites were used to prepare land use maps for the studied years. Then the satellite images were monitored by classification method and were classified using the maximum neighborhood probability algorithm with an overall accuracy of 87.39 to 95.78% and a kappa coefficient of 85 to 93% in four user classes.. In the next step, land use maps were compared. Results: Based on the analysis, it was found that in the period under study, 26.07 square kilometers of Barren lands in this area has changed to agricultural, industrial and residential lands. As a result, the area of Barren lands has decreased and other uses have increased during the studied years. , So that the area of land with agricultural, industrial and residential use has increased by 14.66 square kilometers, 9.77 square kilometers, 1.64 square kilometers, respectively. Discussion and Conclusion: The results of the research show that the most important factor in land use change in the region is human activities that have caused many changes in land use. Analysis of the area of these uses showed that the level of agricultural land has increased significantly, mainly this increase. The result is the conversion of agricultural land use. Finally, the results of this study indicate that the combination of remote sensing techniques and GIS in the implementation of models for assessing spatial-temporal changes in land use, in order to know the type and percentage of land use and the extent of their changes, is very effective. The title of a management parameter can help planners of different executive departments in monitoring and managing the environment.  

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