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Towards a Scenario-based Spatial Dynamic Modeling for Predicting Urban Land Use Change

Planning Tools and Comparative Analysis

Time: Wed 2023-04-12 10.00

Location: F3, Lindstedtsvägen 26 & 28, Stockholm

Video link:

Language: English

Subject area: Land and Water Resources Engineering

Doctoral student: Zipan Cai , Resurser, energi och infrastruktur

Opponent: Professor Stan Geertman, Utrecht University

Supervisor: Professor Vladimir Cvetkovic, Resurser, energi och infrastruktur; Associate Professor Fredrik Gröndahl, Vatten- och miljöteknik; Professor Brian Deal, University of Illinois at Urbana-Champaign

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As global urbanization progresses, cities worldwide are growing in size, which leads to many economic, environmental, and management challenges. Recent advancements in spatial data analysis and algorithmic geography have also led to the development of various urban model-based planning support systems (PSS) for urban planning. These PSSs aim to assist urban decision-makers in understanding urban information and collaborating on planning to address urban development challenges. Advanced urban planning concepts are, however, always multidisciplinary, multi-situational, and continuously evolving. In addition to the development of more advanced urban information and communications technology (ICT) and management, planning concepts that promote urban health and sustainable development are needed to meet residents’ physical, spiritual, and social needs, and promote more sustainable lifestyles. These factors create the need for a more rigorous methodological and theoretical foundation to apply PSS to urban planning at the microscale. 

A scenario-based spatial dynamic modeling approach is proposed in this thesis to address this research gap, allowing for a more precise matching of local policy scenarios and desired development patterns for practical planning support purposes. Several urban development scenarios and their potential impacts are explored by analyzing future urban land use changes. The establishment of this planning support approach effectively integrates spatial analysis, simulation model, policy revision, and participative planning. First, the thesis examines the rules and correlations underlying land unit transformations resulting from human-land interactions in spatial dynamic models by investigating mechanisms driving changes in urban land use. Second, a series of possible urban development simulations are generated through several case studies that employ a variety of representative cities with different urban contexts as model test sites including Nanjing in China, Stockholm in Sweden, and Chicago in the USA to evaluate their validity and practicality. Socioeconomics, ecological systems, and urban amenities are among the research themes that provide a more realistic and practical view of urban development. Last, visualization of the simulation results and quantitative information analyses and transformation is utilized to arrive at recommendations for revising planning policies and promoting sustainable development strategies.

The challenge of adapting successful experiences of urban transformation from one city to another is considerable and cannot be achieved by merely replicating single projects or developments. An important goal was to address this challenge by developing general methods for model-assisted planning and then exploring their applicability and scalability across different contexts and geographical regions. Obtained results confirm that prioritizing industrial and transportation sectors in urban development is the most significant factor contributing to the rapid expansion of cities. This allocation of resources leads to the development of supporting infrastructure and employment opportunities, thereby attracting more people and industries to urban areas. Limiting the expansion of built-up areas and preserving green spaces is a desired measure to protect natural assets and the composition of cities and mitigate the negative environmental consequences of urbanization. Moreover, it is found that there are significant differences in the spatial and temporal needs and dependencies of residents in different areas with respect to natural and social amenities, providing a basis for future land development in residential and commercial areas of a city. Based on these findings, policymakers can more readily test and evaluate “what-if” scenarios using a process-based approach to avoid uncontrolled urban growth. In spite of limitations and uncertainties, the tools presented in this thesis are relevant for urban policymakers to enhance stakeholder interaction and consensus building in the decision-making process. This work has demonstrated the methodological steps for the implementation of these tools, as well as the general potential benefits of dynamic modeling for sustainable city planning and development.