Geospatial Analysis to Support Urban Planning in Beijing

Based on their extensive studies on using planning support systems in Beijing planning practices and research, Dr Ying Long and Prof Shen have published a monograph in Springer. The details are as follows. The book is available online now (CLICK HERE). 

This book describes a comprehensive framework of novel simulation approaches, conventional urban models, and related data mining techniques that will help develop planning support systems in Beijing as well as other mega-metropolitan areas. It investigates the relationships between human behaviors and spatial patterns in order to simulate activities in an urban space, visualize planning alternatives, and support decision making.

 

The book first explains urban space using geometric patterns, such as points, networks, and polygons, that help identify patterns of household and individual human behavior. Next, it details how novel simulation methodologies, such as cellular automaton and multi-agent systems, and conventional urban modeling, such as spatial interaction models, can be used to identify an optimal or a simulated solution for a better urban form.

 

The book develops a comprehensive land use and transportation integrated model used to explore the spatial patterns of mutual interaction between human mobility and urban space. This model can help forecast the distribution of different types of households, rent prices, and land prices, as well as the distribution of routes and traffic volume based on an appraisal of labor demand and supply.

 

This book shows how geospatial analysis can be a useful tool for planners and decision makers to help in ascertaining patterns of activities and support urban planning. Offering both novel and conventional approaches to urban modeling, it will appeal to researchers, students, and policy makers looking for the optimal way to plan the development of a mega-metropolitan area.


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A detailed outline of the monograph
Long and Shen 2015 Springer_BeijingMonog
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Planner Agents

Land use patterns, or land use layout, is one of the key issues in the compilation of an urban master plan. Government, planners and residents, all with various requirements and preferences, are the agents participating in this process in China. Among them, planners play a role in negotiating with related agents and then establishing land use patterns. In this paper, we propose the Planner Agent theory to support land use pattern scenario analysis (LUPSA), based on existing Planning Support System (PSS) research. Planner Agents are divided into three types: Non-spatial Planner Agent (NPA), Spatial Planner Agent (SPA) and Chief Planner Agent (CPA). The NPA is responsible for formulating special plans (such as transport, municipal public facilities or nature reserve plans) that correspond to available data (such as road network, public facilities and nature reserve patterns) from LUPSA. The SPA is responsible for establishing and evaluating land use patterns. The SPA considers constraints of local development conditions, communicates and coordinates with the NPA to confirm special plans formulated by the NPA that can support implementation of the established land use pattern. The CPA is responsible for determining the final land use pattern after a public participation process involving local residents. This theory was initially tested in a hypothetical city, followed by an experiment in Beijing. Results show that the proposed Planner Agent theory is suitable for LUPSA, and is more efficient and scientific than traditional planning methods. 

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Slices presented in CUPUM 2013
PA_CUPUM_v5_Long.pptx.pdf
Adobe Acrobat Document 2.7 MB
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Long and Zhang 2015 EPB_PA.pdf
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A framework of planning support systems

Planning support systems (PSSs) have attracted extensive attention from scholars and decision makers for decades. Most of the existing research on PSSs is related to system design, implementation, application as well as evaluation of a standalone system in one area, e.g. What if?, CommunityViz and INDEX. There is no existing research on an entire framework of PSSs for various types of plans. In this paper, we propose a PSS framework for various types of plans in China, e.g. master plan, detailed plan, municipal infrastructure plan and transport plan. Based on an extensive literature review and multiple rounds of planner and decision maker surveys, the framework focuses on two aspects. On one hand, we itemize plan contents (termed as “plan elements”) into various steps for each type of plan, e.g. population forecasting and establishing urban growth boundaries in a master plan. On the other hand, we list related PSSs for each plan element. In our research, PSSs embody three forms, which are existing PSS software (e.g. What if? and INDEX), planning support models to be developed or already developed as well as quantitative methods (e.g. scenario analysis, systems analysis, and logistic regression). The two dimensional framework provides a full picture of PSS applications in various types of plans. The framework has been applied in the Beijing Institute of City Planning (BICP) for several months, and has attracted hundreds of application requests from planners. 


This paper appears in the Springer book "Geospatial Analysis for Supporting Urban Planning in Beijing" as a chapter.

Slides in CUPUM 2013: BCL Slides 15

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Long and Shen 2015 Springer_BeijingMonog
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In Chinese
龙瀛等 2016 国际城市规划_PSS.pdf
Adobe Acrobat Document 3.8 MB
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The whole framework of the work
Appendix 1.pdf
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The whole framework of the work (in Chinese)
附件1 框架体系.pdf
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PSSs for spatial plans

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龙瀛 2011 博士学位论文_面向空间规划的微观模拟.pdf
Adobe Acrobat Document 26.2 MB
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Slices on our research profile over PSSs
In Chinese
规划支持系统在城市规划中的应用探索.pdf
Adobe Acrobat Document 7.6 MB

PSSs for water and wastewater

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Paper on water conservation planning
In Chinese
给水排水_基于终端分析的北京市节约用水规划研究(上).pdf
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Paper on water conservation planning
In Chinese
给水排水_基于终端分析的北京市节约用水规划研究(下).pdf
Adobe Acrobat Document 393.6 KB
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Paper in a Springer book
An agent-based approach to support decision-making of total amount control for household water consumption
Ma et al 2012 Springer Water.pdf
Adobe Acrobat Document 1.0 MB

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Paper on water resource management
In Chinese
清华大学学报_基于Geodatabase的城市水资源管理系统.pdf
Adobe Acrobat Document 449.4 KB
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Paper on urban wastewater system planning
In Chinese
水科学进展_Geodatabase与城市排水系统规划集成的研究.pdf
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Urban containment planning

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.

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Paper in CHENGSHIGUIHUA
In Chinese
城市规划_北京市限建区规划.pdf
Adobe Acrobat Document 1.9 MB
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Paper in CHENGSHIGUIHUA
In Chinese
城市规划_城市增长控制规划支持系统.pdf
Adobe Acrobat Document 2.8 MB
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Paper in CEUS
Long et al 2011 CEUS_UAZ.pdf
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规划支持系统原理与应用 2007

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The Profile of the Book
龙瀛 2007 化学工业出版社专著_规划支持系统原理与应用.pdf
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My book published in 2007
The Full Book In Chinese (The book is already out of stock, so I share the full text here)
BOOK:规划支持系统原理与应用.pdf
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龙瀛和毛其智 2010 清华大学学报_PSS.pdf
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