Background and Objectives: Optimal site selection and nature-based design principles in green space development are among the most effective approaches for mitigating environmental degradation and can also be considered a step toward nature conservation. This study was conducted in three main phases with the aim of optimal site selection for peri-urban green space development using a parametric ecological analysis and a Multi-Criteria Evaluation (MCE) model. Materials and Methods: To achieve the research objectives, required environmental digital maps were first prepared, followed by a floristic assessment of the study area using representative sampling plots. Based on the field survey data of species-specific vegetation canopy cover collected through a systematic random sampling method, Detrended Correspondence Analysis (DCA) was applied, resulting in the identification of three distinct ecological groups. According to the DCA results, these groups exhibit ecological affinity. In the next phase, nine main criteria were selected for optimal park site selection, including slope, aspect, elevation above sea level, soil characteristics, bare land areas, high-density forest stands, low-density forest stands, road distance buffer, and river distance buffer. These criteria were evaluated using the Analytic Hierarchy Process (AHP), and an integrated Multi-Criteria Evaluation (MCE) model was developed. The derived weights were applied to the corresponding digital layers within a GIS environment.
Results: The results indicated that among the nine main criteria, soil-related characteristics had the highest weight, while aspect and elevation had the lowest weights. The most influential environmental parameters contributing to ecological differentiation were soil depth and elevation above sea level. For spatial decision-making, the Weighted Linear Combination (WLC) approach was employed. In the WLC process, the weight of each factor (thematic map), derived through AHP, was multiplied by the standardized numerical priority of each class, and the resulting weighted layers were then summed with other relevant thematic layers. In the final stage, based on the integrated raster map produced from the weighted layers, land-use suitability for peri-urban park development was classified into five priority classes ranging from completely suitable to completely unsuitable. In this study, areas classified as completely suitable and suitable were selected as the optimal locations for peri-urban park development.

Conclusion: This study showed that combination of ecological analysis, assessment models, and multi-criteria decision-making are effective tools for optimal location of suburban green spaces. The special importance of soil and environmental characteristics in determining the best locations for green space development is an important result of this research. The use of these approaches can contribute to sustainable development and environmental protection in different regions and provide scientific and practical solutions for efficient green space management.