Abstract
Nowadays, cities are expanding and developing with a rapid growth, so that the urban development process is currently one of the most important issues facing researchers in urban issues. In addition to the growth of the cities, how land use changes in macro level is also considered. Studying the changes and degradation of the resources in the past few years, as well as feasibility study and predicting these changes in the future years may play a significant role in planning and optimal use of resources and harnessing the non-normative changes in the future. There are diverse approaches for modeling the land use and cover changes among which may point to the Markov chain model. In this study, the changes in land use and land cover in Kermanshah City, Iran during 19 years has been studied using multi-temporal Landsat satellite images in 1987, 2000 and 2006, side information and Markov Chain Model. Results shows the decreasing trend in range land, forest, garden and green space area and in the other hand, an increased in residential land, agriculture and water suggesting the general trend of degradation in the study area through the growth in the residential land and agriculture rather than other land uses. Finally, the state of land use classes of next 19 years (2025) was anticipated using Markov Model. Results obtained from changes prediction matrix based on the maps of years 1987 and 2006 it is likely that 82% of residential land, 58.51% of agriculture, 34.47% of water, 8.94% of green space, 30.78% of gardens, 23.93% of waste land and 16.76% of range lands will remain unchanged from 2006 to 2025, among which residential lands and green space have the most and the least sustainability, respectively.
Highlights
Urban growth rate is most important feature of human settlement transformation in developing countries; the need to better management by people, communities and governments is vital for this growth
Studying the changes and degradation of the resources in the past few years, as well as feasibility study and predicting these changes in the years can play a significant role in harnessing and controlling the Methods: In this study, the land use changes matrix and Markov Chain Model has been used for land cover change prediction
Number of the through the Multilayer Perceptron Neural Network categories was determined according to the images and Classification Method and predicting the trend of land maps, the state of the study area and categories required use changes using Markov Chain Model in Kermanshah for land cover mapping and 7 classes were considered as follows: residential land, agriculture, water, green space, garden, forest and range land
Summary
Urban growth rate is most important feature of human settlement transformation in developing countries; the need to better management by people, communities and governments is vital for this growth. In these countries, cities usually attract twothird of increased the total population and more than half of the urban population and natural increase and rural to urban migration (McGill, 1988). Knowledge of the types of land cover and human activities in different parts of land as basic information for various planning is of significant importance. The results of the spatial analysis show that the extent of urban area has increased exponentially for the past 83 years and this urban expansion is correlated with the
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