Developing an integrated urban growth prediction model: a scenario-based approach for the conservation of protected areas

Abstract

With the rise in population growth, urbanization boundaries are expanding, leading to increased habitat fragmentation and a decline in genetic diversity among species within protected areas located near urban centers. This study investigates the simulation and prediction of urban sprawl and land use/land cover (LULC) changes in eastern Tehran, as well as the management of their impact on the neighboring Jajrood Protected Area. We developed LULC maps for the years 1986 and 2016 by applying neural network classification to Landsat imagery. To forecast urban growth and LULC changes, we utilized the SLEUTH model. Three different scenarios including Historical Urban Growth (HUG), Managed Urban Growth (MUG), and Environmental Urban Growth (EUG) were defined to predict urban growth through 2046 by by adjusting the calibrated SLEUTH coefficients, including Diffusion, Breed, Spread, Slope Resistance, and Road Gravity. The east of Tehran city is affected by many coefficients such as the slope resistance, road gravity and spread coefficients. Results show the most important coefficients in this research according to HUG, MUG, and EUG scenarios are the road gravity coefficient, the spread coefficient, and the slope coefficient. In the HUG scenario, the predominant land uses will include roads, water bodies, and urban green spaces. Conversely, in the MUG and EUG scenarios, the largest areas will be allocated to agricultural land, forests, and semi-compact pasturelands.