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。     

基于多智能体的居住空间格局演变的真实场景模拟

多智能体建模方法为城市研究提供了一种新的研究思路.采用自下而上的多智能体方法构建真实场景的居住决策模型,并研究城市居住格局的形成和演变具有重要的理论意义和应用价值.但目前的多智能体模型通常把空间抽象为均质空间.无法反映真实的地理空间.通过对居住环境的"宜居性"评价,作为居民智能体对居住环境评价的影响因子.将多智能体模型与GIS相结合.为智能体模型提供一个异质的、动态变化的模拟环境.由此居民智能体根据自身的经济状况以及对居住环境的偏好不断地调整其在城市中的居住地,模拟出城市居住空间格局的演变过程.将模型应用于广州市海珠区,其模拟的住宅价格空间分布与实际情况相关系数在0.6以上,说明模拟结果与实际的情况比较吻合.模拟结果在一定程度上为理解和探讨居住空间格局的成因和动态变化提供帮助,为发展和验证城市理论提供一种重要的分析手段和模拟方法.     

基于多智能体的地理空间分异现象模拟 ——-以城市居住空间演变为例

许多地理现象都存在一定的空间分异规律。研究地理空间分异现象的形成与发展有重要的理论意义。基于“从上至下”的方程式方法很难对这些现象的形成过程进行解析。采用“自下而上”的多智能体系统, 对复杂地理现象的分异过程进行了重现。采用java-swarm 仿真技术, 以城市居住空间分异现象为例, 模拟出城市系统从无序走向有序的过程, 为发展和验证城市理论提供了一种重要的分析手段。基于多智能体的居住空间分异模型展现了居民智能体聚集现象的产生过程及对房屋价值的影响, 比较了居民不同收入差异情况下对居住空间分异的影响。模拟结果表明居住空间分异现象是一个历史的必然; 收入差异扩大使中低收入阶层在居住的空间区位选择上处于被动地位。     

芜湖市就业与居住空间匹配研究

借助偏离度指数分析法从宏观层面研究了芜湖市辖区的就业—居住空间匹配状况的变化特点,利用问卷调查数据,从微观角度分析了市区居民通勤的时间、距离、方式及费用。研究结果表明:芜湖市就业—居住空间匹配度趋于下降,核心区为服务业就业主导区,北部以制造业就业为主导功能,南部居住功能占主导,带来各区居住人口和就业人口的空间流动。居民通勤平均距离约为4km,平均时间约为25min,通勤方式以电动车、公交车为主。目前,居民对就业—居住地匹配状况的满意程度总体尚好,还需要采取措施以进一步提高满意度。     

基于社会属性的北京市居民居住与就业空间集聚特征

制度转型期,中国城市居民社会空间发生了新的变化,居民居住和就业空间组织也变得更为复杂,并引起了广泛关注。基于2010 年问卷调查数据,采用缓冲区、最近邻层次聚类和Ripley K函数等空间分析方法对北京城市不同社会属性居民的居住和就业空间分布特征进行实证分析。研究发现：① 总体上,北京城市居民居住和就业空间圈层分异明显。在各圈层内部,不同人群的居住和就业空间分布比例亦存在相对差异;职住空间错位程度表明距市中心15 km左右是城市就业功能和居住功能主导地位转化的分界线;职住平衡度整体上呈现出由内圈层到外圈层递减的趋势,但高收入阶层和年轻白领的职住平衡度相对较低。② 不同人群居住与就业空间集聚特征存在明显差异。一般平民居住和就业均呈散点状集聚;年轻打工族居住和就业集聚区域紧邻,主要集聚在四环以内的城市东部区域;高收入阶层居住呈现“小集中、大分散”集聚特征,就业集聚区多集中在四环以内的城市东部和西北部区域;年轻白领居住集聚区呈现城市西部条带状和东部散点状相结合特征,就业集聚区主要在中关村和CBD为中心的两条轴状区域。③ 不同人群居住和就业空间集聚的尺度特征较为相似,呈现随距离增加“先增后减”变化趋势,但距离阈值存在差异。表现为高收入群体居住空间可选范围较小,一般平民就业空间可选范围较小,而年轻白领居住和就业空间可选范围均较大。     

基于多智能体模型与建筑物信息的高空间分辨率人口分布模拟

自上而下的人口分布模拟模型自动化程度较低,难以分析人口分布成因,且因精细尺度的人口样本较难获取而不太适用于高空间分辨率人口分布模拟。提出了一种基于多智能体模型和建筑物信息的高空间分辨率人口分布模拟模型。首先利用建筑物三维分布数据提取住宅建筑,构建智能体人口分布模拟模型的环境;然后基于统计、调研数据定义智能体属性,确定智能体居住选择行为规则;最后以泰日社区为例进行了居住人口分布仿真模拟。研究结果表明,基于建筑物信息的人口分布多智能体模型,可以获取每栋建筑物上的人口,改进了当前高分辨率人口模拟主要只模拟小区或者居委会人口的不足;多智能体模型具有较高的自动化程度,不仅能获得较好的模拟结果,而且可在一定程度上从微观机理解释宏观居住分布模式,是对传统统计模型的有益补充。     

城市工业空间增长的多智能体模型

城市工业及基本就业空间的增长,是城市空间增长的动力源.有效模拟和预测城市基本就业空间的增长,对城市整体空间增长和城市系统的调控有着重要的作用.以城市工业及基本就业空间增长的决策主体--工业企业商和政府决策者,作为多智能体,通过多智能体之间的交流、竞争和协作,多智能体和环境间的交互作用,决定已存在工业区位的迁移和新工业空间区位的选择,形成城市工业及基本就业空间增长的动态微观模型.以珠江三角洲东部城市快速发展的樟木头镇为例,采用提出的方法模拟了该地区1988-2004年的工业及基本就业空间增长,获得了良好的模拟结果.     

基于生态位理论的居住区位及居住空间分异

将生态位理论应用于居住区研究,家庭月收入、户主文化程度作为居住态评价因素,交通条件、区位、生活条件、自然环境作为居住势评价因素,构建居住生态位评价模型.该模型在对居住区评价时更好的体现居民因素,比先前区位评价方法更为全面,能更好的解释由于居民因素变化而导致的居住区位变化.对大连建成区37个街道进行居住态、居住势、居住生态位评价,并以居住生态位为切入点,分析不同居住生态位等级的街道居住态及居住势状况,探究居住生态位、居住势、居住态空间分布规律及空间相互关系.进一步研究居住态,从居住态角度分析大连居住空间分异.最后得出结论为大连市居住生态位呈现以中心繁华城区为核心由中心向外围的环带状分布,居住态呈现由东南向西北递减的趋势.高低值区域交错布局空间分布状况,大连市居住空间分异与居住生态位区位分布不完全一致.     

基于多智能体建模技术的城市用地时空演化研究

为应对现代城市发展在用地资源分配和生态环境保护上遇到的巨大挑战,研究在综合复杂系统理论、城市经济学以及地理信息系统等多种学科技术的前提下,应用多智能体建模软件NetLogo构建了一个以“由下至上”运行机制为主的城市用地拓展模型,通过不同微观个体之间的互动反馈行为来实现对圣地亚哥城市宏观用地布局的模拟,并应用逐点比对和整体比对两种不同的精度检验方法来测算模型分析结果的准确性;针对当前模型研究存在的问题和未来可能的改进方向进行了归纳分析。     

城市居住空间扩张的多主体模拟模型研究

借助GIS技术,本文构建了包含微观智能主体和环境主体的城市居住空间演化的多主体模型,旨在探讨城市居住空间增长的过程中市场机制和计划机制之间的相互作用和消长规律。模型分析总结了城市居住空间增长过程中城市居民、住宅开发商和城市政府的目标函数,认为城市空间扩张形态和土地集约利用水平主要取决于土地市场发育状态的不同阶段及城市政府的土地利用决策。通过调整城市政府主体的土地利用和环境政策设定了城市居住空间扩张的紧凑型、松散型和适度型3种情景类型,以ArcGIS和VC为运行环境实现情景模型,为城市政府的土地利用规划政策提供事前指导。以武汉市的洪山和武昌两区为实验区,分别模拟了基于3种规定情景下1998-2008年期间的居住空间演化情况,并与实验区居住空间的实际演化情况进行了形态、土地利用结构变化和土地利用社会效用的概略对比分析,结论为实验区1998-2008年的居住空间扩张基本属于适度型,但尚需要加强城市的内城市化。     

The Role of Residential Location in Conditioning the Effect of Metropolitan Economic Structure on Male Youth Employment

Youths have increasingly experienced labor market problems over the last several decades. One fruitful line of explanation focuses on structural changes in the demand for labor stemming from deindustrialization, changing skill requirements for employees, and increasing supply competition from women and recent immigrants. While these explanations merit attention, they have not adequately considered facts that condition their impact. This paper considers the argument that intra-metropolitan residential location conditions the effects of metropolitan labor market structure on black and white male youths' employment probabilities. Using a sample of individual-level data drawn from the 1990 census combined with metropolitan-level indicators of economic structure, it was found that some structural effects varied between central-city and suburban male youths. The conditioning role of residential location, and the subsequent nature of the structural effects, varied considerably between black and white male youths. Interpretations of the conditioning role of residential location include a variety of social and institutional effects on individual residents and the stigmatizing effects of some neighborhoods, especially on black male youths.     

基于多主体模型的典型区域退耕还林工程实施空间模拟

土地利用变化是全球变化的重要驱动力,模拟是研究土地变化重要的方法。退耕还林是中国山区土地利用变化的重要原因。当前退耕还林模拟在综合社会与空间途径方面的不足限制了退耕还林模拟的空间精度及后续社会效益研究。结合社会和空间途径精确模拟退耕还林的空间过程可为该工程实施提供科学依据。本文以云南省东川区铜都镇为研究区,基于人口普查数据、地理环境数据、实地调研数据,综合考虑农民、农户和政府3类主体,基于多主体模型构建了退耕还林工程实施的空间模型,模拟了2010—2015年铜都镇具有空间特征的农户年收入、农户/政府退耕意愿和退耕还林工程空间实施过程。研究发现退耕还林工程实施主要与坡度、交通和农户收入有关,与土壤肥力相关性较小,坡度25°~30°的耕地占了81.47%,离道路0~2 km交通条件较好的地段占56.37%,农户年收入较低的区域退耕还林比例较高,且退耕还林工程的实施显著提高了铜都镇收入,2010—2015年户均收入提高了1475元。本文模拟结果空间精度为91.12%。本文构建的退耕还林工程实施空间模拟方法可为其它区域提供方法借鉴,以期为中国生态保护和精准扶贫等工程实施提供科学支撑。     

A georeferenced agent-based model to analyze the climate change impacts on ski tourism at a regional scale

One main argument for modeling socio-ecological systems is to advance the understanding of dynamic correlations between various human and environmental factors, including impacts and responses to environmental change. We explore the shift in skier distribution among ski resorts taking into account the behavioral adaptation of individuals due to the impact of climate change on snow conditions. This analysis is performed at a regional scale by means of a coupled gravity and georeferenced agent-based model. Four different scenarios are considered. Two scenarios assume an increase of winter mean temperature of +2°C and +4°C, respectively, taking into account only natural snow conditions. Two additional scenarios add the effect of snowmaking to enhance the natural snow depth and extend the skiing season in the +2°C and +4°C base scenarios. Results show differing vulnerability levels, allowing the classification of ski resorts into three distinct groups: (1) highly vulnerable ski resorts with a strong reduction in visitors attendance for all climate change scenarios, characterized by unfavorable geographical and attractiveness conditions, making it difficult to ensure snow availability in the future; (2) low vulnerability ski resorts, with moderate reduction in season length during a high climate change scenario but no reduction (or even an increase) in a low one, characterized by ski resorts with a medium capacity and attractiveness to ensure enough snow conditions and capture skiers from other ski resorts; and (3) resilient ski resorts, with good conditions to ensure future snow-reliable seasons and outstanding attractiveness, allowing them to offer longer ski seasons than their competitors and potentially attracting skiers from other closed or marginal resorts. Ski resorts included in this last group increase their skier attendance in all climate change scenarios. Although similar studies in the literature foretell a significant reduction of the ski market in the near future, another probable effect outlined in this study is a redefinition of this market due to a redistribution of skiers, from vulnerable ski resorts to more resilient ones.     

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。     

基于感知的北京居民职住空间关系生成机理

职住空间关系是洞悉城市功能空间结构并揭示城市成长与演化规律的重要研究视域.本文构建了生活实践及其感知视角下的居民职住空间关系生成路径分析框架和结构变量作用路径假设模型,基于居民职住空间关系感知调查数据,借助结构方程模型方法,从影响因素和驱动机制两个方面剖析了北京居民职住空间关系的生成机理.研究表明:①房价和住房支付能力...     

NEAT approach for testing and validation of geospatial network agent-based model processes: case study of influenza spread

ABSTRACT

Agent-based models (ABM) are used to represent a variety of complex systems by simulating the local interactions between system components from which observable spatial patterns at the system-level emerge. Thus, the degree to which these interactions are represented correctly must be evaluated. Networks can be used to discretely represent and quantify interactions between system components and the emergent system structure. Therefore, the main objective of this study is to develop and implement a novel validation approach called the NEtworks for ABM Testing (NEAT) that integrates geographic information science, ABM approaches, and spatial network representations to simulate complex systems as measurable and dynamic spatial networks. The simulated spatial network structures are measured using graph theory and compared with empirical regularities of observed real networks. The approach is implemented to validate a theoretical ABM representing the spread of influenza in the City of Vancouver, Canada. Results demonstrate that the NEAT approach can validate whether the internal model processes are represented realistically, thus better enabling the use of ABMs in decision-making processes.     

Simulation of spatial population dynamics based on labor economics and multi-agent systems: a case study on a rapidly developing manufacturing metropolis

Spatial population dynamics affects resource allocation in urban planning. Simulation of population dynamics can provide useful information to urban planning for rapidly developing manufacturing metropolises. In such a metropolis with a concentration of immigrant labor forces, individual employment choices could have a significant effect on their residential decisions. There remains a need for an efficient method, which can simulate spatial population dynamics by considering the interactions between employment and residential choices. This article proposes an agent-based model for simulation of spatial population dynamics by addressing the influence of labor market on individual residential decisions. Labor economics theory is incorporated into a multi-agent system in this model. The long-term equilibrium process of labor market is established to define the interactions between labor supply and labor demand. An agent-based approach is adopted to simulate the economic behaviors and residential decisions of population individuals. The residential decisions of individuals would eventually have consequences on spatial population dynamics. The proposed model has been verified by the spatial dynamics simulation (2007 to 2010) of Dongguan, an emerging and renowned manufacturing metropolis in the Pearl River Delta, China. The results indicate that the simulated population size and spatial distribution of each town in Dongguan are close to those obtained from census data. The proposed model is also applied to predict spatial population dynamics based on two economic planning scenarios in Dongguan from 2010 to2015. The predicted results provide insights into the population dynamics of this fast-growing region.     

An individual cognitive evacuation behaviour model for agent-based simulation: a case study of a large outdoor event

Route selection is a complex issue in simulating the pedestrian’s walking behaviour during the evacuation. In many current studies, the agent-based model has been widely used to simulate the individualized behaviour, and growing concern is given to the cognitive aspects in route selection. However, the influence of incomplete spatial knowledge and the preferences for different routing strategies has not been fully considered. To represent more reliable route choice by different pedestrians, this study presents an individual cognitive evacuation behaviour model which is mainly focusing on the individual differences in routing strategy and spatial knowledge. The model consists of two major components, namely the multiple routing strategies and personalized spatial cognitive road network. Based on a review of the previous studies, the potential factors that may affect the evacuation behaviour were discussed. The quantitative relationships between these potential factors and the pedestrian’s routing preference, as well as the possibilities of recognizing different roads, were explored using the regression method. As a case study, the proposed model was implemented using the data collected from a field survey of a real outdoor event. When applied in an agent-based simulation, the implemented model will support more reliable simulation of route choices corresponding to the pedestrians’ behaviour in the real event.     

利用排序多元Logit模型研究城市居民的 居住区位选择

本文将北京、上海、广州、武汉和重庆五城市的居住区位调查数据,利用排序多元Logit模型研究城市居民对居住区位的选择行为进行了实证分析。影响区位选择的因素可归纳为家庭层面和城市层面两部分,前者包括收入、工作地点、对环境的偏好等,后者则包括住房价格、城市扩张程度、郊区市政设施便利程度等,实证结果表明这些因素的影响都是显著的,且符合理论预期。收入较高的群体仍喜好选择距离城市中心偏近的居住区位,郊区基础设施和公共服务设施的不完善是制约其向郊区转移的主要因素。这些实证结论能够对城市发展布局和居住用地的规划开发起到决策支持作用。