Dynamic Simulation of Urban Expansion Based on Cellular Automata and Logistic Regression Model: Case Study of the Hyrcanian Region of Iran

Abstract

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.

Modeling the Impact of Urbanization on Land-Use Change in Bahir Dar City, Ethiopia: An Integrated Cellular Automata–Markov Chain Approach

“…The neighborhood cells are the adjacent pixels: the cells that are the immediate neighboring cells of a particular cell in the grid. Finally, the transition rules spell out the transformation of cells into another state due to the change in neighborhood cells' status [2,22,48].…”

“…The application of the CA model shows the role of physical and environmental factors that restrict the urbanization process, assuming that the neighborhood cells also influence the state of a cell [22,46,49]. Therefore, the state of the specific plot of land on the ground (e.g., a water body such as a lake) is determined by some predefined transition rules (e.g., water bodies cannot be converted into the built-up area) as well as the state of the neighborhood cells [50].…”

“…One salient area of research has been modeling the nature and the geographies of the massive conversion of "other" land-use types into built-up areas because of rapid urban expansion [17,18]. For example, previous studies have revealed that the built-up area expansion has predominantly been occurring by means of the conversion of agricultural land [19][20][21], forest [22], and open lands [23,24], depending on the context. These rapid and often uncontrolled and unplanned land use conversions have become a key challenge as they impact livelihoods in both the earlier communities and the newly emerging sprawl communities alike, and therefore ultimately the sustainability of the urban expansion at large [13,18,25].…”

A Change Vector Analysis Method to Monitor Drought Using Landsat Data

“…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 spatiotemporal representation in distinct urban development formats (Jafari 2016).…”

Is Big Good or Bad?: Testing the Performance of Urban Growth Cellular Automata Simulation at Different Spatial Extents

“…In CA models, past land use changes are used to project future changes and provide guidance for land use management in urbanization [9]. To enhance the performance of CA, researchers have conducted vast research to calibrate and optimize the models [10][11][12].…”