基于多智能体的就业与居住空间演化多情景模拟——快速工业化区域研究

就业与居住空间关系是城市规划与管理研究的热点问题。已有研究主要基于传统宏观模型对就业—居住空间结构进行现状分析或对城市理论进行实证研究,在微观尺度的机制探讨与过程模拟方面较为缺乏。本文基于多智能体自下而上的建模思想,提出基于就业市场的人口居住区位选择模型(Labor Market Based Model of Residential Location-LMBMRL)。以典型的快速工业化地区—东莞市主城区为实验区,通过多情景模拟对就业与居住空间的互动关系进行机制探讨与过程分析。模拟结果充分反映了就业选择对人口居住区位决策的影响,定量评估了住房与交通对职住空间均衡性与职住分离的影响规律。当住房成本提高时,城市职住均衡性降低;当交通可达性提高时,城市空间结构可能出现较为显著的职住分离现象。最后通过多情景模拟揭示不同行业劳动人口群体的就业—居住空间特征与组织模式。研究结果有助于深刻理解城市就业—居住空间互动关系及其内部因果,能够为城市规划与管理提供决策参考。     

Defining agents' behaviour based on urban economic theory to simulate complex urban residential dynamics

In recent years, agent-based models (ABMs) have become a prevalent approach for modelling complex urban systems. As a class of bottom-up method, ABMs are capable of simulating the decision-making as well as the multiple interactions of autonomous agents and between agents and the environment. The definition of agents' behaviour is a vital issue in implementing ABMs to simulate urban dynamics. Urban economic theory has provided effective ways to cope with this problem. This theory argues that the formation of urban spatial structure is an endogenous process resulting from the interactions among individual actors that are spatially distributed. However, this theory is used to explain urban phenomena regardless of spatial heterogeneity in most cases. This study combines GIS, ABM and urban economic models to simulate complex urban residential dynamics. The time-extended model is incorporated into an ABM so as to define agents' behaviour on a solid theoretical basis. A spatial variable is defined to address the neighbourhood effect by considering spatial heterogeneity. The proposed model is first verified by the simulation of three scenarios using hypothetical data: (1) single dominated preference; (2) varying preferences on the basis of income level; and (3) spatially heterogeneous environment. Then the model is implemented by simulating the residential dynamics in Guangzhou, China.     

基于垄断竞争的大都市商业空间结构动态模拟

本文构建了一个基于垄断竞争、规模经济、交通成本、消费者多样化偏好以及商品和服务差异化的大都市两区域商业空间结构模型。提出了经济学演绎模型与基于agent 的计算实验相结合的研究路径,通过对商家、消费者等大量微观自主体(agent) 的相互作用来“动态地”观察和讨论大都市新、老城区宏观商业空间结构的微观基础、影响因素和演化过程。研究结果表明,①在商品和服务替代性、购物交通成本设定的情形下,新、老城区商业固定成本投入差距越大,则商业空间分布越不均衡,越易形成核心-边缘结构。② 由于居民的消费存在多样化偏好,因此强化区域间的差异性有助于改变商业的市场份额。③ 商业往往集聚在具有区位优势、人口规模优势以及固定成本优势的地区,而且交通条件的改善将加速商业的空间集聚。研究认为,空间经济学演绎模型与推导→基于agent 的地理计算→实证分析与计量检验是一个值得探索的技术路线。     

城市养老设施配置的微观模拟与规划政策分析——以北京市为例

养老设施规划配置的关键应着眼于老年群体对养老服务的差异化需求及其动态变化特征。本文提出了基于多主体模拟的理论框架,并通过对前期研究的梳理,归纳出养老机构配置问题中需要考虑的老年人、养老机构等主体的时间变异和空间差异特征、其行为规则以及他们与环境之间的相互作用规律。在此基础上,以北京市为例构建了多主体微观模拟模型,对2010-2030年间养老机构需求与供给态势进行了预测,并讨论了养老设施布局的评估指标,通过设施利用率、百人床位数和空间匹配度等指标,对北京市养老服务设施的规划政策进行了评估。研究表明,多智能体模拟技术对把握人口动向及养老服务需求的不确定性和动态变化特征而言是一个十分有效的研究工具,能够很好地体现各种要素的空间属性。对于北京市的“9064”养老服务规划和养老设施专项规划的分析表明,如果仅仅对养老模式的分担比例和百人床位数进行控制,而忽视对空间布局的管控,养老机构床位空置率有可能出现继续上升的趋势,为此,必须制定城市中心区养老机构的比例,同时对养老机构的定价、选址和服务质量采取必要的管控措施。     

Study on the synergy between intra-urban resident’s migration and job change in Beijing

People’s decisions of residential mobility in housing market and decisions of job change in labor market play an essential role in the formation and dynamics of urban spatial structure. This paper investigates the relationship between residential relocation and job change and its heterogeneity using a large-scale survey of residential living satisfaction and preferences in Beijing. Several conclusions are drawn as follows: 1) People’s decisions of residential mobility are significantly positively correlated with their decisions of job change, indicating that these two-dimensional decisions are in fact a correlated decision process rather than two independent decision processes. 2) There is heterogeneity in the correlated decisions of residential mobility and job change. More specifically, the interrelationship between the decisions of residential mobility and job change among people without Beijing hukou, renters and single-worker households is more intensive than people with Beijing hukou, homeowners and multi-worker households. In addition, there is heterogeneity in the determinants of residential relocation and job change between groups with different types of housing tenure, household registration status and family employment structure. 3) For renters, commuting time can significantly increase the probability of residential relocation, which indicates that residents of different socioeconomic attributes have very different responses to commuting time costs.     

An agent-based micro-simulation framework for modelling of dynamic activity–travel rescheduling decisions

The simultaneous implementation of daily activity–travel schedules of individuals in a given spatial environment generally gives rise to time- and location-varying congestion levels, which affect the conditions for subsequent activity and travel choices. Although such dynamics are commonly recognized, current activity-based models typically ignore the adaptive behaviour of individuals. In this article, we propose an agent-based simulation system that allows one to simulate, in addition to activity-scheduling behaviour, also the execution of schedules in space and time. Congestion levels at specific times and places emerge in the system and may lead to discrepancies between scheduled and actual activity and travel times. Agents respond to such unforeseen events by reconsidering an existing schedule (within-day re-planning) and by adapting their expectations about traffic conditions for subsequent days (learning). The system is illustrated using the activity–travel diary data collected in the Eindhoven region, the Netherlands, to better understand the choice of urban parks in the study area. We discuss the merits of the system for transport and spatial planning and identify avenues for future research.     

北京市居民居住—就业选择的协同性研究

居民在住房市场上的迁居决策和劳动力市场上的工作迁移决策,是城市空间结构塑造和演化的重要微观因素。本文以2009 年北京市城市居住环境评价和偏好选择抽样调查问卷为基础,探讨了居民居住迁移和工作迁移决策的协同性及其异质性,结果发现：居民居住迁移决策和工作迁移决策是一个存在正向相互联系的协同决策过程,而非两个独立的决策过程;居住迁移和工作迁移决策的正向反馈强度随着微观主体住房产权、户籍和家庭就业结构等状况的不同而具有异质性,非北京市户籍、租房户和单职工家庭居民的居住迁移和工作迁移的正向相关关系要显著大于有北京市户籍、购房户和多职工家庭居民,并且不同社会经济属性的居民其居住迁移决策和工作迁移决策的影响因素也具有异质性。     

基于指数分析法的乌鲁木齐市居住格局研究

乌鲁木齐作为新疆的首府城市,是中国西部地区重要的经济中心,在我国城市体系格局中发挥着重要的作用,通过研究乌鲁木齐市人口居住格局对乌鲁木齐城市空间规划提供指导。以乌鲁木齐市为研究区域,利用城市空间的扩展印证居住空间格局变化宏观特征,将“居住格局”作为切入点,利用莫兰指数并借助ArcGIS技术分析该区域不同属性人口的居住格局。结果显示：乌鲁木齐市城市居民用地主要沿西北方向的新市区延伸、西山方向扩展、沿东山方向扩展,并沿着老城区的外缘扩展;不同年龄人口中学龄人口和老年人口的聚集现象较为明显,劳动人口的聚集现象并不显著,不同受教育程度人口中小学及初中人口和大专以上人口比重指标Moran’s I值较高,文盲人口比重指标oran’s I值相对较低,高中人口在空间上呈现负相关;2000—2016年所有区域学龄人口、老年人口空间分异指数都有所上升,劳动人口分异指数在沙依巴克区和水磨沟区有所下降,说明老龄化现象越来越明显,1990—2000年文盲人口在头屯河区处于相对分异状态,2000—2010年在新市区分异水平较高,1990—2010年小学及初中人口、高中人口以及大专以上人口分异现象逐渐减少,混居程度加深,居住分异现象减少。     

基于多智能体的居住区位空间选择模型

多智能体系统(Multi-Agent system, MAS) 是一种进行复杂系统分析与模拟的强有力工具,尤其在社会科学领域得到了广泛的应用。本文提出了基于多智能体的居住区位选择模型(Agent-Based Model of Residential Location-ABMRL),将多智能体建模的方法应用于居民居住区位决策行为和地价动态变化的研究中,旨在探索与模拟居民在居住选择过程中的复杂空间决策行为,以及居民之间、居民与地理环境的相互作用而导致城市居住空间分异的演化过程。ABMRL模型由表征各类居民的多智能体层和表征地理环境的元胞自动层组成,对应人地关系中的两个基本要素--人类与自然环境。该模型认为居民迁居的动力源于内部的经济社会压力和外部的居住环境刺激。利用ABMRL模型模拟和验证了居住空间分异、圈层城市空间结构、城市绅士化等经典城市理论,并以广州市海珠区为实验区,模拟了该区域居民居住空间分异的演化过程和地价的动态变化。     

基于人口变化的东莞城镇增长与收缩特征和机制研究

基于人口变化的视角,考察东莞城镇人口增长与收缩所出现的结构性变化,分析金融危机前后东莞城镇人口在规模数量、年龄结构、性别结构、学历结构,以及不同类型增长城镇与收缩城镇的产业经济和空间格局特征,并建立面板回归模型探讨影响城镇人口增长与收缩的因素和机制。研究表明,东莞总人口规模趋于波动增长的同时,人口结构呈现出外来人口市民化加快、男女性别失衡加剧、人口年轻化与高学历化的转变;增长类型城镇产业结构以先进制造业和现代服务业为主,而收缩类型城镇则面临传统加工制造业的转型升级问题;空间上呈现“北增长-南收缩”的格局,形成了中部增长、西北部和东南部收缩的城镇集中片区;而宏观经济波动、产业转型升级、科技创新投入、地方发展方式影响着东莞城镇人口的增长与收缩。     

转型时期广州居民职住流动及其空间结构变化——基于3个年份的调查分析

中国城市处于由国家/集体分配体制为基础的计划经济向以市场调控为基础的市场经济转型的特殊时期,城市居民职住空间大规模重构。本文基于2001年、2005年和2010年家庭调查问卷,分析城市居民职住流动及其空间变化,总结城市居民职住流动对广州市社会空间重构的影响。改革开放以来广州市城市居民职住流动率大规模增加,且圈层差异明显,越往外围,职住流动率越高。城市居民的职住就近流动的特征明显,偏好于工作地附近就近选择居住地或在居住地附近就近选择工作地。地方政府应通过城市规划、就业制度改革和住房制度改革等手段来加强宏观调控,合理引导不同社会群体的职住区位选择,以减少居住空间分异和职住空间的过度分离。     

基于动态约束的元胞自动机与复杂城市系统的模拟

为获得复杂城市系统更理想的模拟效果,提出时空动态约束的城市元胞自动机(CA)模型。用不同区域、不同时间新增加的城市用地总量作为CA模型的约束条件,形成时空动态约束的CA模型,并利用该模型模拟1988—2010年东莞市和深圳市城市扩张过程。结果表明,利用CA模型模拟的1993年城市用地总精度比静态CA模型提高了5.86%,而且模型中的动态约束条件可以反映城市发展的时空差异性。     

城市流动人口居住自选择中的空间权衡分析——以成都市为例

基于成都市主城区各街道的流动人口数据,分析2010-2015年流动人口规模的空间分布格局及居住空间分异程度,并从流动人口行为决策的视角选取影响变量,分析其对居住自选择的影响程度及其空间差异,据此揭示居住自选择中的空间权衡过程,探讨流动人口的空间权衡对其居住自选择和居住空间格局形成的作用。结果表明：2010-2015年,成都流动人口在主城区南部和城市中心快速增加,其集聚态势为西高东低;流动人口相较于本地户籍人口表现出一定程度的居住空间分异性;流动人口占常住人口比、居住区面积、房租、公交、企业及生活服务设施对流动人口居住自选择有明显影响,且流动人口占常住人口比、居住区面积和房租影响显著,但影响关系受流动人口空间自相关影响显著;地理加权回归结果显示不同变量对居住自选择的解释能力存在空间差异性,流动人口通过不同变量空间分布的差异性权衡不同区域,以此完成居住自选择并最终形成居住空间格局。     

The Slums of Aspen: Immigrants vs. the Environment in America's Eden. Lisa Sun-Hee Park and David Naguib Pellow

In the past decade, Beijing has experienced dramatic spatial restructuring. In this paper, we test whether the conventional monocentric model of urban spatial structure can explain recent developments in Beijing’s land market. Using official land transaction data from 2008 through 2012, we find that (1) for commercial, mixed-use, and residential land parcels, both land prices and development intensities do not decline with distance from the urban center; (2) for industrial land parcels, land prices increase with distance from the urban center. These insignificant and positive land-price gradients defy the predictions of the monocentric model; such results are explained by examining Beijing’s evolution from a monocentric to a polycentric spatial configuration, which has been driven by various urban planning efforts and institutional reforms. Our analysis of post-Olympic Beijing land market dynamics leads to a fresh understanding of the city’s emerging polycentric metropolitan structure.     

Using multiple scale spatio-temporal patterns for validating spatially explicit agent-based models

Spatially explicit agent-based models (ABMs) have been widely utilized to simulate the dynamics of spatial processes that involve the interactions of individual agents. The assumptions embedded in the ABMs may be responsible for uncertainty in the model outcomes. To ensure the reliability of the outcomes in terms of their space-time patterns, model validation should be performed. In this article, we propose the use of multiple scale spatio-temporal patterns for validating spatially explicit ABMs. We evaluated several specifications of vector-borne disease transmission models by comparing space-time patterns of model outcomes to observations at multiple scales via the sum of root mean square error (RMSE) measurement. The results indicate that specifications of the spatial configurations of residential area and immunity status of individual humans are of importance to reproduce observed patterns of dengue outbreaks at multiple space-time scales. Our approach to using multiple scale spatio-temporal patterns can help not only to understand the dynamic associations between model specifications and model outcomes, but also to validate spatially explicit ABMs.     

ASSURE: a model for the simulation of urban expansion and intra-urban social segregation

Numerous cities in developing regions worldwide are expanding at a tremendous rate. This requires adequate strategies to address the needs of these growing cities with diverse populations. Nonetheless, the development of urban policies is often hampered by the lack of reliable data or insight in the socio-spatial dynamics of this urban expansion. This paper therefore presents ASSURE, a spatially and temporally explicit model that can simulate urban growth and intra-urban social segregation, taking into account alternative policy strategies and expected social dynamics. The model has a flexible structure that allows incorporating specific city conditions that influence residential decision-making and adapting the simulation to the data available. This, in combination with the transparent model structure, makes ASSURE a potentially valuable decision support tool for urban planning. The potential is demonstrated with an example where the urban growth of and social segregation in Kampala (Uganda) is simulated based on (semi-)quantitative and qualitative data for ca. 800 households collected through interviews. The results of the simulations show that depending on the scenario, the spatial segregation and accessibility problems will evolve highly differently.     

中国城市群的空间模式——分散性区域集聚的理论背景、形成机理及最新进展

从空间模式而言,城市群的本质是人口和经济活动在更大范围城市地域实体内的集聚。在这一集聚体内,原乡村地区密集参与着工业化、经济发展。在国内外经典文献分析的基础上,论文将城市群这一特征概括为分散性区域集聚,并认为分散性区域集聚是信息技术革命以来经济全球化空间选择的结果,也是中国政策制度背景的产物。作为全球制造业生产平台和协调控制中心在空间上的独特反映,这一根本属性使得城市群区别于传统区域,在空间上并不遍在;其分散性的发展特征使得它同时代表着最为严重的资源环境约束,值得特别关注。从分散性的地域单元入手的规划策略较目前的城市群整体战略而言,可能较易实施和取得效果。同时,随着中国内需战略和“一带一路”倡议的实施,城市群发生发展的国内外背景正在发生重要转变。分散性区域集聚的空间模式并不一定适用于中国所有区域,在进行规划管理时,必须审慎对待这一客观事实。     

新创企业的时空分异与区位选择——基于中国汽车制造业的实证研究

新创企业区位选择不仅是企业重要的决策活动,也深刻影响中国制造业地理空间格局演变。在全球化、市场化、分权化背景下,基于“中国工业企业数据库（1998—2012）”和“中国城市统计年鉴（1999—2013）”中新创企业及城市属性数据,采用随机效应面板Tobit模型分析中国汽车制造业新创企业的时空分异与区位选择。研究发现：① 1998—2012年,中国汽车新创企业活跃地区由东部沿海地区向中西部地区转移,尤其是2010—2012年,新创企业呈现向中西部大规模扩散趋势,西部成渝地区逐渐成为新热点区域。② 从新创企业区位选择时空综合机制来看,全球化影响不显著,而市场化和分权化均存在显著影响,其中劳动力、集聚经济、市场潜力与区位商等因素能促使新创企业成立,而国有企业占比则会阻碍新创企业成立。③ 在时间特征差异上,全球化表现不显著,分权化则始终保持对新创企业的显著影响。市场化的劳动力因素影响作用变化说明新创企业区位选择正逐渐从关注劳动力成本转向于关注劳动力质量,而集聚经济和市场潜力在多样化和城市化经济的冲击下作用减弱。④ 在空间特征差异上,全球化的出口因素在东部地区影响显著,但在中西部地区表现不明显,市场化中劳动力因素和市场潜力在东部地区影响不显著,而在中西部地区劳动力因素则显著为正,除此之外,外商直接投资、集聚经济、区位商和国有企业占比对不同区域新创企业区位选择影响大体相同。在经济高质量发展情景下,揭示新创企业时空分异及区位选择机制,强调“区位机会窗口”对某些地区实现企业区位空间调整及其把握企业与政府关系的重要性,不仅能丰富演化经济地理学视角下的企业区位选择的研究,还能更好地理解中国典型区域正在发生的经济转型和空间重构。     

Comparative performance of logistic regression and survival analysis for detecting spatial predictors of land-use change

Although survival analysis is known to outperform logistic regression, theoretically and according to evidence from other disciplines, little is known about how true this is in situations where the goal is detecting spatial predictors of land change. Furthermore, with the increasing availability of longitudinal land-change data, evidence is needed on the relative performance of these two different methods in situations with differing levels of data abundance. To fill this gap, we generated a pseudo land-change data set using an agent-based model of residential development in a virtual landscape. This agent-based model simulated the decisions of homebuyers in choosing residential locations based on the values of several spatial variables. Pseudo land-change maps, generated by the agent-based model with different weights on these spatial variables, were exposed to statistical analysis under the logistic and survival approaches. We evaluated how well the two approaches could reveal the spatial variables that were used in the agent-based model and compared the performance of the two methods when land-change data were collected under different sampling frequencies. Our results suggest that survival analysis outperforms logistic regression in detecting the variables that were included in agent decisions, largely because it takes into account time-dependent variables. Also, this research suggests that various properties of land-change processes (like amount of developed area and access of agents to information) affect the relative performance of these statistical approaches aimed at uncovering land-change predictor variables.     

基于CA-ABM模型的福州城市用地扩张研究

以中国海西地区重要门户福州市为研究区,结合其地理位置多层次约束性条件,以地理加权回归模型作为元胞自动机(CA)层的转换规则,同时以2000-2015年多期LandsatTM/ETM+影像的城市用地情况为参照,借助GIS空间分析技术,对CA和多智能体(ABM)相耦合的城市用地扩张模型进行改进。然后利用传统的和改进后的CA-ABM模型,多角度、多层次地模拟福州市2000年、2005年、2010年、2015年城市用地扩张在微观格局上的变化。结果表明,传统的和改进后的CA-ABM模型的整体精度均在80%以上,模拟结果具有较强的可信度;改进的 CA-ABM模型模拟的点对点总体精度和Kappa系数均高于传统的CA-ABM模型,而且模拟结果更加接近实际的城市用地扩张分布情况。结论可为平衡城市化进程和合理规划城市用地提供重要的理论技术支撑。