Urban sprawl has become a remarkable feature in urban development, especially in developing countries, in the last decades. To face this phenomenon, it is required to first forecast auto-spreading orientation rural areas over time in order to avoid shapeless urban growth. Although GIS/RS and CA-Markov models are applied to study urban growth patterns the world over, very few studies have applied these methods to examine the urban growth of Iran. A major land use change is detected here from 1989 to 2013. In this study the future sprawl of this province is forecasted for target years of 2025 and 2037 through a simulation. The results predict an alarming increase in urban development for the target years of 2025 and 2037, with an expansion is predicted to develop of 11510 and 18320 ha, respectively. In sum, this model is an efficient tool for the support of urban planning decisions and facilitates the process of sustainable urban development providing decisionmakers.
Abstract:The hypothesis addressed in this article is to determine the extent of selected land use categories with respect to their effect on urban expansion. A model that combines a logistic regression model, Markov chain, together with cellular automata based modeling, is introduced here to simulate future urban growth and development in the Gilan Province, Iran. The model is calibrated based on data beginning in 1989 and ending in 2013 and is applied in making predictions for the years 2025 and 2037, across 12 urban development criteria. The relative operating characteristic (ROC) is validated with a very high rate of urban development. The analyzed results indicate that the area of urban land has increased by more than 1.7% that is, from 36,012.5 ha in 1989 to 59,754.8 ha in 2013 and the area of the Caspian Hyrcanian forestland has reduced by 31,628 ha. The simulation results, with respect to prediction, indicate an alarming increase in the rate of urban development in the province by 2025 and 2037 that is, 0.82% and 1.3%, respectively. The development pattern is expected to be uneven and scattered, without following any particular direction. The development will occur close to the existing or newly-formed urban infrastructure and around major roads and commercial areas. If not controlled, this development trend will lead to the loss of 25,101 ha of Hyrcanian forest and, if continued, 21,774 ha of barren and open lands are expected to be destroyed by the year 2037. These results demonstrate the capacity of the integrated model in establishing comparisons with urban plans and their utility to explain both the volume and constraints of urban growth. It is beneficial to apply the integrated approach in urban dynamic assessment through land use modeling with respect to spatio-temporal representation in distinct urban development formats.
2015): Assessment of a spatial multi-criteria evaluation to site selection underground dam in the Alborz Province, Iran, Geocarto International,
AbstractThe most part of Iran County is located in an arid and semi-arid region, thus in most parts of a region; groundwater is the only water resource. This research presents a method based on a spatial multi-criteria evaluation (SMCE) due to design possible sites for an underground dam, and ranks them according to their suitability. The mentioned method was tested for the sitting of an underground dam in the Alborz Province, Iran. At first, screening algorithm was done using exclusionary criteria, and thirty one potential areas were recognized in the study area. In the next step, the suitable gorge or valley was recognized using the combination of basic maps and extensive field surveys (long axis of tank level) in each potential area. Subsequently, it was used of the analytical hierarchy process (AHP) as a powerful tool for decision making in spatial multi-criteria evaluation in order to evaluate different criteria for underground dam sites. SMCE techniques were then applied to combine the criteria, and obtain a suitability map in the study area. These sites were then compared and ranked according to their main criteria such as water, storage, axis, and socio-economic. All these criteria were assessed through GIS modeling. This method shows passable results and could use for site selection underground dam in other regions of Iran County. Downloaded by [University of Otago] at 10:55 23 July 2015 2
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