Land use and transport integration across scales: A review of evolving models and strategies for scaling up - Dong Xiao; Liton Kamruzzaman; Hai L. Vu (Transportation Research Interdisciplinary Perspectives, 2025)
Land Use and Transport Integration (LUTI) models are critical tools for understanding the complex interactions between land use dynamics and transport systems. While extensively applied at local and metropolitan levels, their implementation at broader spatial scales remains limited and fragmented. This systematic review examines 115 peer-reviewed studies to trace the evolution of LUTI models across spatial levels—from cities to national contexts. Using bibliometric, content, and thematic analyses, the study identifies key modelling approaches, integration mechanisms, and application domains. Findings reveal a progression from aggregate spatial interaction models to disaggregate agent-based and microsimulation frameworks, with accessibility-activity feedback loops serving as the core integration mechanism. Despite methodological advancements, the review highlights persistent challenges in scaling up LUTI models, including data harmonization, computational complexity, and inter-jurisdictional policy coordination. Building on insights from large-scale implementations, the paper proposes a conceptual framework to guide future model development, focusing on data organization, hybrid model architectures, and long-term strategic functionality. By synthesizing evolving practices and identifying pathways to overcome scaling barriers, this review contributes to both academic research and professional practice. For researchers, the study offers a refined spatial scale typology and a structured framework for large-scale LUTI model development. For practitioners, it presents actionable strategies to address real-world implementation challenges, including data harmonization, model usability, and inter-jurisdictional coordination. These insights support the broader application of LUTI models in regional and national strategic planning.