Monitoring of Land-use Changes and Predicting the Time - Location in Hamedan City

Land-use changes in developing countries have negative environmental and ecological consequences for the environment. Therefore, access to the updated information in land-use changes is necessary for the analysis of different needs of human settlements and adopting appropriate policies to ensure the future. Past studies and prediction of land-use in the future have a fundamental role in decision making and policymaking of land-use planners. The purpose of this study was to study land- use and its changes over the years 2001 - 2013 and to identify the land-use changes in Hamedan city and to simulate and future land- use and its changes by Ca - Markov model in 2010.Ingredients: After obtaining satellite images of TM, ETM, and OLI, preprocessing steps including radiometric and geometric corrections were performed on images. Then, using the support vector machine (SVM) algorithm. We used a support vector machine (SVM) to classify satellite images and divide the land- uses into four classes of residential and non - residential, barren lands and poor rangeland, garden lands, and irrigated farming, mountainous, and grassland. After land-use change detection and changes to predict the trend of these changes by the Markov chain model due to the high capability in detecting spatial - spatial component changes, for 2010.

The results of the present study indicate that over time, the growth and development of urbanization in this metropolis cause to expand the physical texture of the city in this region. Therefore, at the beginning of the study, the residential and non - residential land use area in this metropolis, if at the end of the period, the total area of the region has arrived. The study of land-use changes showed that from 1390 to 1392, residential and non - residential land uses were added to residential and non - residential land uses and the increase of the next land-use area was related to arid lands and pastures. Land- use and irrigated farming, along with mountain use, were among the number of land uses that had been decreased in 2010 compared to the previous year. This trend continues with time in a way that the area of residential and non - residential construction and bare lands continues to increase its area in 1390 and is added to the area of land uses. Finally, over the past year, it can be said that over the past year, the land- use of residential and non - residential areas and land use has decreased. This conversion has negative consequences in the future of the region to reduce the negative consequences of these changes in the future.

In this study, the automated cell model and Markov chain have a high ability to predict land-use changes in the future. It is also necessary to increase the land-use area for residential and non - residential and bare land uses and other uses such as garden lands, irrigated farming, mountain, and grassland are decreasing areas in the region. Therefore, planners should always consider this growth and expansion in the future to better plan their programs.