| چکیده انگلیسی مقاله |
Introduction: In recent years, land use changes, especially in urban areas, have been recognized as one of the major challenges in the field of urban planning, natural resource management, and sustainable development. With the increase in population, expansion of construction, and the growing demand for urban land, the need for accurate monitoring and analysis of land use changes is felt more than ever before in order to optimally manage resources and formulate efficient urban development policies. In this regard, the present study aimed to investigate the trend of land use changes in Herat city during the years 2015 to 2022. For this purpose, Landsat 8 satellite images from the OLI sensor were used, which, due to their suitable spectral and spatial characteristics, have a high capability in analyzing land use changes.
Materials and Methods: First, the satellite images collected for the two mentioned years were subjected to the necessary pre-processing, including radiometric correction, geometric correction, and atmospheric correction, in order to increase the accuracy of subsequent analyses. After preprocessing, four land use classes including soil, vegetation, residential areas, and water areas were identified in the study area. In order to classify these images and extract information related to land use changes, two widely used classification algorithms including Maximum Likelihood Classification and Artificial Neural Network were used, and the accuracy of the results of these two methods was evaluated and compared.
Results and Discussion: The results of the analyses showed that the Maximum Likelihood method performed better in classifying satellite images than the Artificial Neural Network method. The values of the Kappa coefficient and overall accuracy used to evaluate the classification accuracy were 0.75 and 85 percent for 2015 and 0.96 and 97 percent for 2022. These values indicate the high accuracy and reliability of the Maximum Likelihood method in separating different land use classes in the study area. Analysis of the classification results in the period 2015 to 2022 indicates significant changes in the spatial structure of land use in Herat city. According to the results, during this period, the land area has decreased by 4.0 square kilometers. Also, the water area has decreased by 1.62 square kilometers. On the other hand, the land area related to residential areas has increased by 1.39 square kilometers and the vegetation area has increased by 4.59 square kilometers.
Conclusion: These changes indicate the trend of urban development in Herat city during this period and indicate an increase in human interventions in land use, especially in the form of the development of residential areas and the increase in green space or vegetation. In summary, the findings of this study indicate that urban development in Herat city has caused a decrease in natural lands such as land and water resources, and on the contrary, uses with human interventions such as residential areas and vegetation have increased. Given the decrease in water resources and natural lands, it is essential that future planning of the city focuses on sustainable development, protection of natural resources, and especially effective management of water resources. This management can be achieved through precise policies, imposing restrictions on excessive urban development, and raising public awareness of the importance of natural resources. This research, using remote sensing data and scientific analysis of land use changes, has provided valuable information for decision-makers and urban planners. The results of this study can be used as a basis for developing scientific solutions in the field of urban land management, natural resource conservation, and sustainable development in Herat city. Therefore, the use of modern technologies in monitoring and evaluating land use changes should be considered as one of the basic requirements in the decision-making process and urban policies, and it is suggested that urban development should proceed with better management of water resources. |