Urban Microsimulation for Spatial Plan

This dissertation aims to introduce microsimulation into spatial plans to support urban planning compilation and evaluation. The spatial plan as an effective measure for managing urban growth attracts extensive attentions from aspects of geographical information system (GIS), remote sensing (RS), as well as land use & transportation integrated models. Urban systems as a type of complex adaptive system, however, are composed by numerous parcels in the physical space and urban residents in the social space. The bottom-up microsimulation approaches, such as cellular automata (CA) and multi-agent system (MAS), have their opportunities in analyzing and simulating spatial plans. This dissertation will apply GIS, CA, and MAS based microsimulation techniques to develop microsimulation models for supporting urban spatial plan compilation and evaluation as follows.

 

Firstly, we proposed a data synthesis approach for urban microsimulation models. We disaggregate individual micro data using aggregate data, small-scale surveys and empirical researches to feed microsimulation models to tackle the current data sparse condition in China.

 

Secondly, we developed two microsimulation models for supporting spatial plan compilation. The first model, BUDEM, is developed based on CA incorporating four types of constraints to simulate future urban growth. The simulation results can be adopted as spatial plan alternatives as well as urban growth boundaries (UGB). The second model, FEE-MAS, is for calculating commuting energy consumption and environment impact for urban form in the inner city level. The quantitative relationships among them can then be identified accordingly using a global sensitivity analysis approach, thus supporting the compilation and evaluation of spatial plan.

 

Thirdly, we conducted two researches for evaluating spatial plan alternatives using the BUDEM model. One, spatial plan can be evaluated as possible or impossible in terms of the availability of urban policies, which is the reversed process of conventional urban growth scenario analysis. Two, spatial plan implementation effectiveness is spatiotemporally evaluated for five master plans in Beijing.

 

In sum, several key solutions are proposed in this thesis for introducing microsimulation into spatial plan with empirical researches in the hypothetical space and Beijing, respectively. The approaches included in this dissertation range from GIS, RS, CA, MAS, spatial analysis, and artificial intelligence, and the spatial plans cover both master plans and detail plans. Therefore, this dissertation is promising for promoting planning support techniques for spatial plans in China. 

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Dissertation_LONG_20110518.pdf
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BUDEM2

Most existing carbon emission models operate at the inter-city level or are inventory-based; few operate at the inner-city scale.  Beijing has witnessed booming urban growth in the last three decades and this is expected to continue into the future.  Against this background, we have developed a family of Beijing Urban Spatial Development Models (BUDEMs) for modelling spatial dynamics and evaluating carbon emission (CO2).  Models were developed for the macro, meso and micro level respectively. This paper describes how the three Beijing models were established, calibrated and applied to carbon emission evaluation from a perspective of spatial organization. The macro model was based on constrained cellular automata and logistic regression to analyse past growth patterns and long-term future urban growth scenarios. The meso model was an integrated land-use and transportation model, with traffic analysis zones as its basic unit. This aimed to evaluate medium term carbon emission resulting from various policy scenarios. The micro BUDEM was developed in the parcel/block scale based on 100% micro data including households, residents, firms as well as human mobility and parcels. It was used to evaluate short-term carbon emission. The models that we developed have been applied in planning practices in Beijing and could offer city planners a more carbon-efficient urban form in future based on the CO2 evaluation results of a planning alternative.    

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Slices on macro-, meso-, and micro- BUDEMs
BUDEM_MMM.pdf
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New! A brief introduction on BUDEM2 at the BCL Wechat website


Applied Urban Modeling with Big Data

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Opportunities and challenges for applied urban modeling in the era of big data
In Chinese
大数据时代的城市模型研究及其机遇.pdf
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My experience with urban modeling
In Chinese
北京这六十年.pdf
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In Chinese (our interview with Prof Michael Batty)
刘伦和龙瀛 2014 北京规划建设_M.Batty访谈.pdf
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A review on applied urban modeling in Chinese
刘伦等 2014 城市规划_城市模型综述.pdf
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A review on applied urban modeling in English
Liu et al 2016 CCPR_UrbanModelReview.pdf
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Beijing Transportation and Land Use Integrated Model (BLUTI)

Since an interactive relation exists in transportation and land use, the planning and evaluation of major policies, measures and infrastructures having a long-lasting influence shall focus on the research of the advantages, disadvantages and influence degrees of transportation and land use. Meanwhile, land-use and transportation integrated model is required to complete the research and analysis of urban real estate market, evaluation of planned land-use structure and layout, and the assessment of the effectiveness of planning scheme of urban transportation system. Based on the abovementioned demand, this paper takes Beijing as an example.

 

Beijing land-use model is established and calibrated on the basis of the transportation model of Beijing. As a result, the construction of transportation and land-use integrated model has been realized. Also, typical model application analysis has been carried out in order to evaluate the harmonious of urban land-use planning and transportation system planning.

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WP14.pdf
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BUDEM

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 model's 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.

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Python code for BUDEM
Simplified version
RST_CA.zip
Compressed Archive in ZIP Format 2.2 MB
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Video demo for CA in a virtual city
VirtualSpace6.avi
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Paper in TST
In English: http://www.sciencedirect.com/science/article/pii/S100702140970149X#!
Long et al 2009 TST_BUDEM.pdf
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Paper in CHENGSHI GUIHUA XUEKAN
In Chinese
城市规划学刊_综合约束CA城市模型.pdf
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Paper in CCPR
Long and Mao 2010 CCPR_CCCA.pdf
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BUDEM-JJJ

The Beijing urban development model based on prevalent urban growth theory and constrained cellular automatic, has been developed in 2008 for analyzing and simulating urban expansion in space for the Beijing Metropolitan Area (BMA). It is proved that the model, using point, line and polygon factors as constraints of urban expansion, is capable of analyzing historical urban expansion mechanisms and predicting future urban expansion for metropolitan areas in China. The model BUDEM_GBA (Greater Beijing Area, namely GBA), as the regional version of BUDEM, is used to identify urban expansion mechanisms in two historical phases from 2000 to 2005 and from 2005 to 2010, to retrieve urban expansion policies needed to implement the desired (planned) urban form in 2020, and to simulate urban expansion scenarios for 2049 based on the urban form and parameter set in 2020. 

V-BUDEM

BUDEM (Beijing Urban Development Model) is a spatio-temporal dynamic urban model for supporting city planning and corresponding policies evaluation in the Beijing metropolitan area, using a raster-based CA method. The first phase of BUDEM was used to simulate urban growth, including identifying urban growth mechanisms in the various historical phases, retrieving urban policies needed to implement the planned urban form, and predicting urban growth scenarios, which has been proved to be useful to support the compilation of Beijing’s urban master plan. In this paper, based on the former work, we develop a vector-based Beijing Urban Development Model (V-BUDEM), using the method of vector-based CA.In this model, the parcel is treated as the cell, and would be transited into developed or undeveloped as a whole unit during the simulation process. The neighborhood is defined as all parcels surrounding the cell within a certain distance. After describing the conceptual model of V-BUDEM, we used it to simulate urban growth of Xiji Town, one small town in Beijing, and compared the result with that from BUDEM. As the results shown, V-BUDEM is a model aiming to the application of urban planning, and emphasizes the importance of comprehensive constraints, such as policies of basic farmland protection and forbidden built-up areas. The semi-automatic parcel division method, used in this paper, is a new solution to divide parcels, and can determine the basic simulation spatial units for V-BUDEM, and is easy to implement and speed-up the model run. The vector-based CA method is a useful means to simulate urban growth, and V-BUDEM can simulate urban growth in a way, which is more close to real situation. 


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

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Slices presented at SPSD 2013
V-BUDEM_SPSD.pptx
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Long and Shen 2015 Springer_BeijingMonog
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Applying BUDEM in Pei Xian

Lun Liu in University of Cambridge applied our BUDEM model for simulating urban development in Pei Xian. 

 

Planning Policy Scenario Analysis based on BUDEM: A Case Study of Peixian County during Industrial Transition

CA (cellular automata) models have achieved much progress in urban simulation since the 1980s. However, most relevant researches are from the field of geography and thence are not ready for application in urban planning, especially as a support tool for planning policymaking. Therefore, this research explores this application of CA by proposing Peixian Urban Spatial Development Model as a planning support tool for a mining city Peixian in East China. The model is based on Beijing Urban Spatial Development Model (BUDEM) developed by Long (2008) and is focused on the specific influencing factors of Peixian’s urban growth. Three policy scenarios will be simulated and analyzed, that’s industrial development policy scenario, urban development policy scenario and environmental protection policy scenario, from which policy recommendations can be drawn to promote the implementation of Peixian master plan during its industrial transition. In the last part, the role of CA models in planning practice is discussed.


Residential and industrial location choice models using UrbanSim

This research is based on the UrbanSim system, a platform features modelling micro individual behavior in the city system. With the spatial resolution of 1911 segments (traffic analysis zone) of Beijing (1067 segments within inner-city), the research focuses on characteristics of residential and industrial location choice behavior within the inner city, based on residential and enterprise location choice theory in urban economics and discrete choice model. A series of technology of residential and industrial land allocation is developed from the view of demand side.

 

An analysis of the mechanism for how the location factors, namely traffic and employment accessibility, public services, municipal facilities and living facilities, exert influence on household residential location choice behavior and its strength is made through residential location choice module. Through the analysis, the research accurately measures residents’ preference heterogeneity. 


Model estimation results show that: in groups classified by income, the low-income families prefer public service facilities, while other families are more concerned about living green spaces and leisure facilities. According to the rent-or-buy correlation group results, self-owned housing families prefer educational and medical quality resources whereas rental households are more concerned about traffic and employment accessibility.

 

Modern service enterprises and retails, the industry of market-oriented location choice, are taken as the object of the study. The research conducts modify settings in UrbanSim to meet the actual situation in Beijing, and the location choice models of modern service enterprises and retails are separately calibrated. The empirical analysis of this research shows that: zones with intensive agglomeration economy, better transportation accessibility, low land rent and favorable government regulations are more attractive to modern service enterprises. Specifically, the modern service enterprises focus more on intensive agglomeration economy and better transportation accessibility. In addition, zones with low land rent, large and rich resident population, and convenient transportation will attract both retail firms.

 

Based on the residential and industry location choice model, the research further explores the practical application of the land allocation technology from the view of demand side. Firstly, the research use the cumulative probability distribution function and the GIS graphic expression, and demonstrates the differences between land use preference and the actual land supply. We can see the spatial distribution of "the gap between supply and demand".

 

Secondly, according to the different preference of residents and firms in each zone, the study puts forward a land allocation method highlighting demand strength between the two types, supporting spatial configuration of mixed-use related decisions.


Furthermore, by analyzing the target group’s preference for affordable housing, we propose a affordable housing site suitability index calculation method, taking comprehensive consideration of the low-income rental households living amenity and opportunity cost of land grant. This method can help the city government achieve a better balance between enhancing the quality of life of public rental housing families and avoiding excessive loss of land revenue. The actual evaluation of the public rental housing site alternatives in Beijing is made.

Self-owned housing families’ preference

Rental housing families’ preference


Modern service enterprises’ preference

Retail firms’ preference


GAP of Residential

GAP of Commercial


Comparison preference between residential and industrial location choice

Affordable housing site suitability index spatial distribution