Toward micro-scale spatial modeling of gentrification

 A simple preliminary model of gentrification is presented. The model is based on an irregular cellular automaton architecture drawing on the concept of proximal space, which is well suited to the spatial externalities present in housing markets at the local scale. The rent gap hypothesis on which the model's cell transition rules are based is discussed. The model's transition rules are described in detail. Practical difficulties in configuring and initializing the model are described and its typical behavior reported. Prospects for further development of the model are discussed. The current model structure, while inadequate, is well suited to further elaboration and the incorporation of other interesting and relevant effects. Received: 1 November 2001 / Accepted: 12 April 2002 Town centres data were made available by kind permission of the UK Department of the Environment, Transport and the Regions.     

Stochastic sketching of infiltration-advance isochrones

A technique has been developed for predicting the irregular advance pattern often observed as water spreads on the surface of the ground. The technique is a combination of stochastic sketching, potential theory, probability theory, and a mass balance equation in the form of an advance equation. The technique can be used on flat as well as sloping terrain and addresses any form of obstructions or constraints to the flow of the water. The stochastic sketching portion of the technique uses cellular automata with transition probability movement rules to sketch the dynamics of small volume water elements in the defined environment. Randomly selected small volume flow path segments are computed and plotted. The envelope of these segments defines the wetted area and the advance front. Several examples are presented showing the patterns produced for various situations.     

A cellular automata model of surface water flow

Previous cellular automata models of surface water flow have been constructed to reflect steady, gradually‐varied flow conditions. While these models are extremely important in showing the near‐equilibrium forms that result from the interactions of water and boundary material, highly dynamic forms and processes require models that represent unsteady flow conditions. In order to simulate unsteady flow in a cellular model of surface water flow, the conservation of mass and the Manning's equations are coupled with an algorithm to delay the movement of water from one pixel to the next until the correct timing is reached. This approach yields highly realistic flood wave hydrographs when compared with flood observations in the Walnut Gulch Experiment Watershed. Coupling this unsteady flow model with simple laws of sediment erosion, transport, and deposition should allow event‐based simulations of watershed and river channel geomorphologic change. Copyright © 2007 John Wiley & Sons, Ltd.     

山城眺望空间OSCA模型构建及应用

山体是大自然赋予城市的天然景观资源,通过山与城市中建筑群构成的山城空间关系,可形成多类型的眺望景观。当前山城眺望景观在建设热潮中不断被破坏,逐渐消失在林立的高楼中,需要进行一定的控制和保护。以济南市中心城区为例,基于眺望控制分区,寻找城市建筑发展演变、分区建设的规律,结合元胞自动机与多智能体,提出基于眺望景观控制下的山城眺望空间CA-OSCA模型（Overlooking Space Cellular Automata）,构建山城眺望空间演变模型。利用GIS等数据分析平台,对模拟结果进行分析,构建真实城市空间下的未来山城眺望空间景观三维模型,以更加直观、真实地方法探讨在眺望景观分区控制的影响下,未来城市空间结构的发展模式,最终为未来山城眺望景观空间的控制与保护以及眺望景观保护下,山城城市未来空间发展结构提出发展策略。     

城市元胞自动机扩展邻域效应的测量与校准研究

城市元胞模型由于在定量分析与预测城市动态的潜力而受到众多研究者的持续关注.邻域规则是主导城市元胞模型模拟过程的关键组件.研究表明,不同土地利用组合间存在显著的邻域效应,且邻域效应具有惯性、排斥和吸引等影响.然而,传统城市元胞模型主要考虑的是特定分辨率下较小窗口的邻域范围.本文尝试刻画更大窗口的邻域效应及其对元胞模型的影响.基于测量的扩展邻域因子,应用粒子群优化算法校准大窗口邻域规则,并创建了考虑扩展邻域效应的城市元胞模型.为验证模型有效性,将其应用于模拟厦门市1995-2010年期间的城市扩张动态.与3×3摩尔邻域的逻辑回归模型相比较,1995-2010年期间的建设用地模拟精度从80.7％提高到83.9％,总体精度从87.8％提高到89.6％,Kappa系数从70.0％提高到74.5％,表明考虑扩展邻域效应的城市模型取得了更好的模拟效果.     

An agent-integrated irregular automata model of urban land-use dynamics

Urban growth models are useful tools to understand the patterns and processes of urbanization. In recent years, the bottom-up approach of geo-computation, such as cellular automata and agent-based modeling, is commonly used to simulate urban land-use dynamics. This study has developed an integrated model of urban growth called agent-integrated irregular automata (AIIA) by using vector geographic information system environment (i.e. both the data model and operations). The model was tested for the city of San Marcos, Texas to simulate two scenarios of urban growth. Specifically, the study aimed to answer whether incorporating commercial, industrial and institutional agents in the model and using social theories (e.g. utility functions) improves the conventional urban growth modeling. By validating against empirical land-use data, the results suggest that a holistic framework such as AIIA performs better than the existing irregular-automata-based urban growth modeling.     

基于CA模型的佛山市建设用地动态变化研究

元胞自动机具有能模拟复杂动态系统的强大能力,本文采用了多约束条件的元胞自动机模型,以广东佛山市2000年、2006年和2012年建设用地的变化为例,从自然、社会经济发展等方面综合考虑选取了高程、坡度、人口密度、道路交通、水系等对城市建设用地发展变化起决定作用的诸多因子,利用马尔科夫概率矩阵计算2000年~2006年建设用地变化,推算建设用地转移总量。结合Logistic-CA模型和决策树-CA模型,预测模拟了2012年的建设用地分布并与实际相比较,分析其整体精度和误差来源。结果显示基于CA模型的建设用地动态发展模拟具有良好的效果,可以为城市的发展规划,过程演变提供虚拟的实验手段和科学依据。     

基于人工蜂群CA模型的南京市土地利用变化模拟与预测

以南京市为例,构建人工蜂群元胞自动机（CA_ABC）模型,对2000—2007年的土地利用变化进行模拟以实现CA_ABC模型的校正,并以2007—2015年的土地利用变化为案例,验证该模型的有效性。模拟结果总体精度（OA）2007年为87.79%,2015年为80.61%;模拟结果的品质因数（FOM）2007年为21.23%,2015年为19.25%。基于CA_ABC模型和马尔可夫链预测未来城市土地总量,对南京市2025和2035年的土地利用格局进行了预测,对城市扩张和生态用地被侵占现象进行分析。模型预测结果表明,未来20年的城市扩张主要以牺牲耕地和林地为代价,2025和2035年80%的城市扩张面积来源于对耕地面积的侵占,17%的城市面积扩张是由2015年的林地转换得到的。研究表明,准确模拟、预测未来城市格局及评估城市扩张能够对生态用地侵占,以及为决策者合理规划城市、推动城市可持续发展提供帮助。     

顾及空间尺度效应的城市土地利用变化精细化模拟

城市土地利用变化模拟是优化土地资源配置的科学依据,提高其精细化程度和可靠性有助于准确把握城市用地发展趋势,对城市土地资源精准调控具有重要意义。基于宏观遥感分类的土地利用变化模拟,难以在街区尺度上揭示城市用地社会功能变化及精细化模拟中空间尺度效应来源和作用机理。本文联合遥感影像和POI数据识别出城市土地利用精细化特征,运用响应面法率定土地利用精细化模拟的最优空间尺度组合,在此基础上,利用CA-Markov模型开展了未来土地利用变化的精细化模拟。以武汉市中心城区为应用案例,研究结果表明：基于POI 的城市土地利用精细化识别方法,可以深度解析城市建设用地的社会功能,极大改善了传统基于遥感的土地覆被宏观解译效果;研究区土地利用变化元胞自动机精细化模拟的最优空间尺度组合是30 m元胞、7×7邻域以及冯诺依曼邻域类型,采用最优空间尺度组合能够提高土地利用变化精细化模拟的可靠性。响应面试验设计结果可有效识别精细化模拟过程中空间尺度效应的主要来源,并区分其对模拟精度的影响程度与正负效应;预计到2025年,研究区建设用地范围将继续向周边扩张,各类型用地之间互为交织,土地利用空间格局将呈更加破碎化趋势。     

基于CA模型的佛山市建设用地动态变化研究

元胞自动机具有能模拟复杂动态系统的强大能力,本文采用了多约束条件的元胞自动机模型,以广东佛山市2000年、2006年和2012年建设用地的变化为例,从自然、社会经济发展等方面综合考虑选取了高程、坡度、人口密度、道路交通、水系等对城市建设用地发展变化起决定作用的诸多因子,利用马尔科夫概率矩阵计算2000年～2006年建设用地变化,推算建设用地转移总量。结合Logistic-CA模型和决策树-CA模型,预测模拟了2012年的建设用地分布并与实际相比较,分析其整体精度和误差来源。结果显示基于CA模型的建设用地动态发展模拟具有良好的效果,可以为城市的发展规划,过程演变提供虚拟的实验手段和科学依据。