International Journal of

Transformation of land use-land cover change occurs due to the numbers and activities of people. Urban growth modeling has attracted authentic attention because it helps to comprehend the mechanisms of land use change and thus helps relevant policies made. This study applied logistic regression to model urban growth in the Ahvaz Metropolitan Area of Khuzestan province in IDRISI Selva software and to discover what are driving forces effective on the urban growth of Ahvaz city, and with what intensity? Historical land use and land cover data of Ahvaz were extracted from the 1991and 2006 Satellite images. The following two groups of factors were found to affect urban growth in different degrees as indicated by odd ratios: (1) Constraints Distance to the Bridge, Rural Areas, Planned town and Industry activities (all with odds ratios<1_or coefficient <0); and (2) Number of urban cells within a 5·5 cell window, Distance to the Hospitals, Main Road, High Road, Rail Line, River, CBD and Secondary centers, agriculture areas in distance more than 5km of Urban area and Vacant area (all with odds ratios>1_or coefficient >0). Relative operating characteristic (ROC) value of 0.906 indicates that the probability map is valid. It was concluded logistic regression modeling is suitable for Understanding and measuring of driving forces effect on urban growth. Second, unlike the Cellular Automata (CA) model, the logistic regression model is not temporally explicit; urban growth trend in Ahvaz isn't in the event of infill development strategy. Also, variables of sprawl based agents indicate more power than to compact base agents.

Rapidly increasing urbanization in the world, especially in developing countries, let to increasing urban extents. Rapid urban growth causes to appearance many problems such as wasting environmental resources, inability of providing necessary services for citizens and unplanned growth. Urban mangers and planners need tools for understanding amount and size of future urban growths to prevent these problems. Urmia as capital city of west Azerbaijan province, in the last decades has considerable growth in both extent and population. This rapid growth caused to lose most high value agricultural resources in its surrounding. It has also caused many problems for urban management. Therefore, how city managers and urban planners can be aware of magnitude and location of Urmia city’s future growth and what is the best growth scenario for Urmia city? This paper uses a quantitative analysis research methodology to prediction and evaluation of growth scenarios for Urmia city. In this paper, SLEUTH model was applied to predict future urban growth of Urmia until 2050. Two different scenarios were employed include: Historical Growth Scenario (HGS) and Environment Protection Scenario (EPS). The result highlight that if the city continues its growth based on HGS scenario, in compare with growth based on EPS scenario, it would occupy more area. In this paper, we concluded that the EPS scenario can be more sufficient than HGS scenario. In addition, SLEUTH urban growth model can be used as a planning support model for urban planners and managers decisions for Urmia city based on scenarios.

This Paper attempts to investigate the patterns of land cover changes and also the process of urban growth in Shiraz Metropolitan Area. Since detailed information of current urban processes is required for future developments and managements of urban areas, this study utilizes remote sensing data and landscape metrics, as useful tools to gather information on urban growth and dynamics, in order to examine the spatial pattern of Shiraz metropolitan area (SMA) from 1986 to 2014. Since, the northwestern areas of SMA are superior in terms of ecological advantages, analysis of types and patterns of SMA growth were separately examined for each sector (NW, NE, SE, and SW). Five landscape metrics were used to analyze compactness and dispersion of urban patches derived from remotely sensed images. The results showed that over the past 28 years, SMA experienced sweeping changes with unexplainable growth during 1996-2006: a great horizontal expansion with 5.89 percent annual growth rate. After facing great urban sprawl, especially on the edge of the main city in the 96-06 period, periphery rural areas beyond the city borders started growing drastically during last decade. While measuring landscape metrics indicates a process of compactness in the growth patterns of NE, SE and SW areas, NW is going to be more dispersed in the coming years.