Abstract for: Mapping System Dynamics in Spatial Decision Systems: A Bibliometric and Content Analysis of SD–GIS Integration for Sustainable and Resilient Planning
System Dynamics (SD) effectively models complex temporal behaviors but lacks spatial representation, while GIS captures spatial patterns without dynamic feedback. Their integration, known as Spatial System Dynamics (SSD), addresses these limitations. However, despite rapid development toward decision-support systems, the field remains fragmented, with challenges in interoperability, transparency, and integration with emerging paradigms such as digital twins and human-centered systems. This study employs a mixed-methods approach combining bibliometric and qualitative content analysis to examine SD–GIS research. A corpus of 38 peer-reviewed studies (2001–2025) was analyzed to identify temporal trends, geographic distribution, and keyword patterns, alongside methodological classifications, application domains, and emerging research gaps, providing a comprehensive understanding of the field’s evolution. The results reveal a clear evolution of SD–GIS research across three phases: early conceptual development, methodological expansion, and recent maturation into decision-support systems. Publications are concentrated in Asia, while keyword trends show a shift toward sustainability and policy applications. Content analysis highlights advances in hybrid modeling and scenario-based systems, reflecting a transition from theoretical models to applied, policy-oriented tools. The findings indicate that SD–GIS research is transitioning toward integrated, application-driven systems but remains limited by fragmented methodologies and insufficient interoperability. Key challenges include the lack of semantic integration, limited explainability, and weak linkage to real-time data environments. Addressing these issues is essential for advancing SD–GIS toward digital twin applications and human-centered decision-support systems in complex planning contexts. used for paraphrasing