A Matrix-Driven Cellular Automata Model for Analyzing Urban Decay and Vitality Indicators at the Neighborhood Scale

Urban decay and urban vitality are widely used concepts in architecture and urban studies to describe the negative and positive characteristics of urban environments. However, they are commonly addressed through qualitative or static approaches, limiting their applicability in neighborhood-scale spatial assessment and design-oriented decision-making processes. This study proposes a matrix-based cellular automata model for analyzing urban decay and urban vitality indicators at the neighborhood scale. Indicators related to urban decay and urban vitality were identified through a comprehensive literature review, and repetitive, overlapping, and context-inappropriate criteria were removed. A data-based decision matrix was then constructed using five criteria: theoretical validity, data accessibility, spatial applicability, model compatibility, and impact level. Indicators were scored on a 1–5 scale, and those with a total suitability score of four or higher were selected as model inputs. The finalized indicator set was incorporated into a cellular automata model with a regular grid structure, defined for a study area of approximately 600 m × 600 m in the Semsi Tebrizi neighborhood of Konya, Turkey, using 15 m × 15 m cells. The model is not intended as a predictive tool but functions as an indicator-based decision-support framework for pre-design spatial analysis and interpretation.