Measuring the effect of an ongoing urbanization process on biodiversity conservation suitability index: integrating scenario-based urban growth modelling with Conservation Assessment and Prioritization System (CAPS)

The present study adopts an integrative modelling methodology, which combines the strengths of the SLEUTH model and the Conservation Assessment and Prioritization System (CAPS) method. By developing a scenario-based geographic information system simulation environment for Hashtpar City, Iran, the manageability of the landscape under each urban growth scenario is analysed. In addition, the CAPS approach was used for biodiversity conservation suitability mapping. The SLEUTH model was implemented to generate predictive urban layers of the years 2020, 2030, 2040 and 2050 for each scenario (dynamic factors for conservation suitability mapping). Accordingly, conservation suitability surface of the area is updated for each time point and under each urban development storyline. Two-way analysis of variance and Duncan’s new multiple range tests were employed to compare the functionality of the three scenarios. Based on results, the managed urban growth scenario depicted better results for manageability of the landscape and less negative impact on conservation suitability values.     

Measuring the relationships between landscape aesthetics suitability and spatial patterns of urbanized lands: an informed modelling framework for developing urban growth scenarios

This study develops an informed modelling approach that follows a bottom-up planning strategy to define plausible urban growth scenarios. In this case, landscape aesthetics suitability of the area was first generated using multi-criteria evaluation method. Then, a buffer zone of 1 km was considered to extract the average values of aesthetics suitability scores surrounding urban patches with medium physical size (10–30 hectares). The averaged values were considered as the dependent variable. In the next step, landscape metrics of these urban patches, as explanatory variables, were also computed to measure compositional and configuration-based attributes of urban clusters. Bivariate associations (Pearson correlation analysis) and statistical relationships (linear regression algorithm) between landscape metrics and their associated aesthetics values were measured and modelled. According to the results, both composition and configuration values are significantly correlated to the dependent variable in which configuration-based attributes depicted a stronger explanatory power.     

Study on forecast scenarios for simulation of future urban growth in Shenyang City based on SLEUTH model

The SLEUTH urban growth model was used to simulate future urban growth patterns and to explore potential environ-mental impacts of urban development under different conditions of development in Shenyang City, China. The SLEUTH model was calibrated with historical data (1988-2004) extracted from a time series of TM satellite images, and the future growth was pro-jected out to 2030 assuming three different policy scenarios: (1) current trends scenario (Scenario CT), (2) regional policy and ur-ban planning sce...     

Improving the capability of an integrated CA-Markov model to simulate spatio-temporal urban growth trends using an Analytical Hierarchy Process and Frequency Ratio

The creation of an accurate simulation of future urban growth is considered one of the most important challenges in urban studies that involve spatial modeling. The purpose of this study is to improve the simulation capability of an integrated CA-Markov Chain (CA-MC) model using CA-MC based on the Analytical Hierarchy Process (AHP) and CA-MC based on Frequency Ratio (FR), both applied in Seremban, Malaysia, as well as to compare the performance and accuracy between the traditional and hybrid models. Various physical, socio-economic, utilities, and environmental criteria were used as predictors, including elevation, slope, soil texture, population density, distance to commercial area, distance to educational area, distance to residential area, distance to industrial area, distance to roads, distance to highway, distance to railway, distance to power line, distance to stream, and land cover. For calibration, three models were applied to simulate urban growth trends in 2010; the actual data of 2010 were used for model validation utilizing the Relative Operating Characteristic (ROC) and Kappa coefficient methods Consequently, future urban growth maps of 2020 and 2030 were created. The validation findings confirm that the integration of the CA-MC model with the FR model and employing the significant driving force of urban growth in the simulation process have resulted in the improved simulation capability of the CA-MC model. This study has provided a novel approach for improving the CA-MC model based on FR, which will provide powerful support to planners and decision-makers in the development of future sustainable urban planning.