Qizhi Mao

Beijing urban development model: Urban growth analysis and simulation

Abstract Urban growth analysis and simulation have been recently conducted by cellular automata (CA) models based on self-organizing theory which differs from system dynamics models. This paper describes the Beijing urban development model (BUDEM) which adopts the CA approach to support urban planning and policy evaluation. BUDEM, as a spatio-temporal dynamic model for simulating urban growth in the Beijing metropolitan area, is based on the urban growth theory and integrates logistic regression and MonoLoop to obtain the weights for the transition rule with multi-criteria evaluation configuration. Local sensitivity analysis for all the parameters of BUDEM is also carried out to assess the models performances. The model is used to identify urban growth mechanisms in the various historical phases since 1986, to retrieve urban growth policies needed to implement the desired (planned) urban form in 2020, and to simulate urban growth scenarios until 2049 based on the urban form and parameter set in 2020. The model has been proved to be capable of analyzing historical urban growth mechanisms and predicting future urban growth for metropolitan areas in China.

An urban containment planning support system for Beijing

Abstract Urban containment policies, including urban growth boundaries, urban service boundaries and greenbelts, have been extensively discussed worldwide for managing urban growth. This paper focuses on the issues associated with supporting an urban containment plan and its application in China using a planning support system. The background is that the urban containment plan has been enacted as a new component of the urban plan under the City Planning Law of the People’s Republic of China. In China, the accommodating or restrictive features are integrated as control factors (CFs), which include control indicators for land-use type control, urban activity control, building height control, as well as underground development control. This paper proposes an urban containment planning support system (UC-PSS) based on ArcGIS for automatically compiling the Beijing urban containment plan considering 60 control factors with various control indicators. The compiled plan was also applied for reviewing urban master and district detail plans in Beijing supported by the UC-PSS. The effectiveness of UC-PSS was comprehensively evaluated from the perspectives of planning compilation and planning review via interviewing urban containment planners (main users of the UC-PSS) in Beijing.

Retrieving Spatial Policy Parameters from an Alternative Plan Using Constrained Cellular Automata and Regionalized Sensitivity Analysis

In this paper we propose an approach to identify the spatial policy parameters (termed the implementation intensity reflecting planning controls on corresponding spatial constraint) associated with a predefined alternative plan, namely, a predefined-binary urban form. During plan implementation, the alternative plan cannot be fully realized in some cases due to practical urban growth driven by both institutional forces and market incentives, which are comprehensive and complex. Few researchers have investigated spatial policies appropriate for an alternative plan. We aim to propose a novel approach incorporating constrained cellular automata and regionalized sensitivity analysis, a method for global sensitivity analysis to calculate the realization possibility and identify the spatial policy parameters for an alternative plan. This approach is first tested in a virtual space with four predefined urban forms and various point, line, and polygon spatial constraints, with both positive and negative impacts on urban growth. Finally, the approach is also tested in the Beijing Metropolitan Area to identify the required spatial policy parameters for four alternative plans with seven spatial constraints.

BUDEM: An urban growth simulation model using CA for Beijing metropolitan area

It is in great need of identifying the future urban form of Beijing, which faces challenges of rapid growth in urban development projects implemented in Beijing. We develop Beijing Urban Developing Model (BUDEM in short) to support urban planning and corresponding policies evaluation. BUDEM is the spatio-temporal dynamic model for simulating urban growth in Beijing metropolitan area, using cellular automata (CA) and Multi-agent system (MAS) approaches. In this phase, the computer simulation using CA in Beijing metropolitan area is conducted, which attempts to provide a premise of urban activities including different kinds of urban development projects for industrial plants, shopping facilities, houses. In the paper, concept model of BUDEM is introduced, which is established basing on prevalent urban growth theories. The method integrating logistic regression and MonoLoop is used to retrieve weights in the transition rule by MCE. After model sensibility analysis, we apply BUDEM into three aspects of urban planning practices: (1) Identifying urban growth mechanism in various historical phases since 1986; (2) Identifying urban growth policies needed to implement desired urban form (BEIJING2020), namely planned urban form; (3) Simulating urban growth scenarios of 2049 (BEIJING2049) basing on the urban form and parameter set of BEIJING2020.

Urban Form, Transportation Energy Consumption, and Environment Impact Integrated Simulation: A Multi-agent Model

More energy is being consumed as urbanization spreads. Extensive research has found that a dominant share of urban energy consumption belongs to transportation energy, which has a strong relationship with urban form in the intracity level. However, little attention has been paid to the relationship between urban form, transportation energy consumption, and its environmental impact in the inner-city level. This chapter aims to investigate the impact of urban form, namely, the land-use pattern, distribution of development density, and the number and distribution of job centers on the residential commuting energy consumption (RCEC). We developed a multi-agent model for the urban form, transportation energy consumption, and environmental impact integrated simulation (FEE-MAS). Numerous distinguishable urban forms were generated using the Monte Carlo approach in the hypothetical city. On the one hand, the RCEC for each urban form was calculated using the proposed FEE-MAS; on the other hand, we selected 14 indicators (e.g., Shape Index, Shannon’s Diversity Index, and Euclidean Nearest Neighbor Distance) to evaluate each generated urban form using the tool FRAGSTATS, which is loosely coupled with the FEE-MAS model. Afterward, the quantitative relationship between the urban form and RCEC was identified using the calculated 14 indicators and RCEC of all generated urban forms. Several conclusions were drawn from simulations conducted in the hypothetical city: (1) the RCEC may vary three times for the same space with various urban forms; (2) among the 14 indicators for evaluating urban form, the patch number of job parcels is the most significant variable for the RCEC; (3) the RCECs of all urban forms generated obey a normal distribution; and (4) the shape of an urban form also exerts an influence on the RCEC. In addition, we evaluated several typical urban forms—e.g., compact/sprawl, single center/multicenters, traffic-oriented development, and greenbelt—in terms of the RCEC indicator using our proposed model to quantify those conventional planning theories. We found that not all simulation results obey widely recognized existing theories. The FEE-MAS model can also be used for evaluating plan alternatives in terms of transportation energy consumption and environmental impact in planning practice.

An Urban Growth Control Planning Support System for the Beijing Metropolitan Area

This chapter is a case study of a planning support system (PSS) for urban growth control, in which the Beijing Metropolitan Area is used as an example to demonstrate the implementation of the planning support system. Generally, encroachment on open space and natural resources caused by urban sprawl has drawn worldwide attention and posed enormous challenges to sustainable human development. The possible negative impacts of urban sprawl include increased land consumption, infrastructure construction costs, commuting distance, traffic congestion, energy consumption, and air pollution (Burchell 1998; Anas and Rhee 2006). However, little attention has been paid to urban growth control planning (UGCP), considering various control factors and their indicators, or the possible application of PSS to these problems.

A Challenge to Configure Form Scenarios for Urban Growth Simulations Reflecting the Institutional Implications of Land-Use Policy

In planning practice, planners and policy makers frequently investigate urban forms, particularly urban growth boundaries (UGBs), using scenario analyses (SA) by regarding development policies as scenario conditions in urban simulations (i.e., Klosterman 1999; Landis 1994, 1995). Couclelis (2005), however, argued that routine land-use modeling has done little in the way of future-oriented research such as investigations of desirable or feared future conditions. This chapter uses planning alternatives, specifically UGBs, as scenarios to identify necessary spatial policies for planners. This is the inverse procedure of traditional urban growth SA. We propose the concept of “form scenario analysis” (FSA), which we employ to investigate relationships between planning alternatives and corresponding spatial policies. This chapter explains an FSA approach using constrained cellular automata (CA), a tool for matching planning alternatives with necessary spatial policies. We look in particular at form scenarios in order to present the institutional implications of different spatial land-use policy options. This novel exploration of FSA can identify necessary policies as well as policy variations required for different planning alternatives. This differs from traditional applications of constrained CA.