Reducing model complexity for explanation and prediction

Numerical models can be useful for explaining poorly understood phenomena or for reliable quantitative predictions. When modeling a multi-scale system, a ‘top-down’ approach—basing models on emergent variables and interactions, rather than explicitly on the much faster and smaller scale processes that give rise to them—facilitates both goals. Parameterizations representing emergent interactions range from highly simplified and abstracted to more quantitatively accurate. Empirically based large-scale parameterizations lead more reliably to accurate large-scale behavior than do parameterizations of much smaller scale processes. Conversely, purposefully simplified representations of model interactions can enhance a model's utility for explanation, clarifying the key feedbacks leading to an enigmatic behavior. For such potential insights to be relevant, the interactions in the model need to correspond to those in the ‘real’ system in some straightforward way. Such a correspondence usually holds for models constructed for predictive purposes, although this is not a requirement. The goals motivating a modeling endeavor help determine the most appropriate modeling strategies, as well as the most appropriate criteria for judging model usefulness.     

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.     

复杂地震系统的数字模拟

借用细胞自动机的计算处理方法，对地震孕育过程中整个系统能量输入，积累，释放，传播等进行了数字模拟，并研究了复杂地震系统的整体特征，结果表明，整体调整系统，地震时能量的损耗系数，外部构造应力场的驱动力大小会影响到地震系统中能量积累和释放的状况，影响到Ｇ－Ｒ关系中ｂ值的大小。     

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.     

Analysing Lava Risk for the Etnean Area: Simulation by Cellular Automata Methods

The model SCIARA, based on the Cellular Automata paradigm, is a versatile instrument whose scope is to analyse volcanic risk from lava flows.The possible fields of intervention are:[(a)] Long term forecasting of the flow direction at various eruption rates and points of emission by locating potential risk areas and permitting the creation of detailed maps of risk;[(b)] The possibility to follow the progress of an event and predict its evolution;[(c)] The verification of the possible effects of human intervention on real or simulated flows in stream deviation.A risk scenario has been developed for the Etnean territories of the towns of Nicolosi, Pedara and S. Alfio, simulating possible episodes with different vent locations along the fracture opened in the 1989 eruption and successively activated in the 1991–1993 eruption.The main characteristics of lava flows, that might be dangerous to the inhabited areas, have been analysed on the basis of the carried out Cellular Automata.     

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。