Application of Remote Sensing and GIS Techniques for Simulating Urban Development (Case Study: The City of Mahabad

The investigation of land cover and land use changes has been important since ancient eras and these changes mainly occur in two ways: the first types of these changes take place by the means of natural factors such as erosion, tectonic forces and floods and the second types take place by human factors. In recent years in many parts of the world, human oriented activities were the most effective factors in changing land use, land cover and urban development. Nowadays population growth,on one hand and limites resources,on the other hand, result in changing of the application of lands. Land use changes in agricultural areas neighboring the cities is an important factor which has a vital role in supplying food and maintaining food security as well as earning money for urban population which have rapid growth. Vicinity of agricultural and horticultural areas with cities of Iran as ecological reserves, has increased the necessity of conducting this study. The present study aims to minimize the extent of use changes and lessen challenge of ecological destruction via development scenarios.
In this study logistic regression model has been used, which is a special kind of multiple regressions and in which the dependent variable is discrete. Contrary to other linear models, the least square method was used in logistic regression. Maximum probability method was used for estimation of characteristics and factors of each independentvariable. Therefore,the logistic regression equation is as follows: { }{ }{ }….{ }
Different data and softwares were used toward implementing the regression model. The soft wares used are:Ecognition¡Idrisiselva and Arc GIS. Images were received through satellite Landsat 5 in 1986 and Landsat 8 in 2014 from USGS site (United State Geological Site). Regarding the location of Mahabad which is situated in pass 168 and rows 34 and 35, we received two frames each year. Pre-process operations including image mosaic, subset and radiometric correction were implemented on images before classification operation by Flaash method in ENVI environment. For increasing accuracy of multi-spectral images of Landsat 8 bands which have low local resolution and high spectral resolution fusion operations were implemented combined with 15 meters panchromatic band. Classification was conducted through the Fuzzy method in the Ecognition environment. Then, classified images were transformed into ASCII format in Arc GIS environment for entering the software environment of Idrisiselva, and their format were changed into RST format in IDRISI environment software for preparing variables. Logistic regression command was used for modeling in the software Idrisi environment. To do this, we entered the amount of change in urban development from 1986 to 2014 into the model environment as a dependent variable and other involved factors in urban development as independent variables, respectively. We used Fuzzy method for scenario building and zoning of developed areas, in which developed areas were categorized into four classes: very proper, proper, improper and very improper.
The investigation of land use changes from 1986 to 2014 determined that land uses decreased with urban development every year. Land use changes are as follow: building lands increased from 989.86 ha to 2000.02 ha. Water resources (dikes and rivers) had decreasing trend from 841.85 ha to 564.16ha. Irrigated arable lands decreased from 2889.17 ha to 1195.378 ha in 1986, and also rocky lands decreased from 10045.42 ha to 7572.78 ha. In this study, investigation of urban development from 1986 to 2041 shows that land use change will be increased in proportion with population growth.
Results of the study showed that in the city of Mahabad, land use changes doubled with the twofold growth of the population in the mentioned period. Development in the third period was lower than twofold. Generally, changing land use could be predicted for future years through using different models of forecasting and through using geographical information system techniques and remote sensing as well, and allowing controlling and management of urban development trends, considering ecological and risk factors, and prohibit from entering residential areas into risky areas. These bestow help and information to urban managers to solve the problems. By introducing solutions urban development can be managed and controlled in a desired way. Considering urban development and reducing arable lands by making urban belt prohibits urban development in agricultural lands and prohibits approaching to natural risks areas, stabilizes land use in a programmed form and prevents hasty urban development. On the other hand, for identifying areas prone to urban development, and for preventing unlawful building by making barrier in the way of rushed urban development,we should establish an exact plan from an economic point of view.