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1.
杨青生  黎夏 《地理学报》2006,61(8):882-894
为了更有效地模拟地理现象的复杂演变过程,提出了用粗集理论来确定元胞自动机 (CA)不确定性转换规则的新方法。CA可以通过局部规则来有效地模拟许多地理现象的演变过程。但目前缺乏很好定义CA转换规则的方法。往往采用启发式的方法来定义CA的转换规则,这些转换规则是静态的,而且其参数值多是确定的。在反映诸如城市扩张、疾病扩散等不确定性复杂现象时,具有一定的局限性。利用粗集从GIS和遥感数据中发现知识,自动寻找CA的不确定性转换规则,基于粗集的CA在缩短建模时间的同时,能提取非确定性的转换规则,更好地反映复杂系统的特点。采用所提出的方法模拟了深圳市的城市发展过程,取得了比传统MCE方法更好的模拟效果。  相似文献   

2.
基于动态约束的元胞自动机与复杂城市系统的模拟   总被引:2,自引:0,他引:2  
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。  相似文献   

3.
This article presents a novel cellular automata (CA) approach to simulate the spatio-temporal process of urban land-use change based on the simulated annealing (SA) algorithm. The SA algorithm enables dynamic optimisation of the CA's transition rules that would otherwise be difficult to configure using conventional mathematical methods. In this heuristic approach, an objective function is constructed based on a theoretical accumulative disagreement between the simulated land-use pattern and the actual land-use pattern derived from remotely sensed imagery. The function value that measures the mismatch between the actual and the simulated land-use patterns would be minimised randomly through the SA process. Hence, a set of attribution parameters that can be used in the CA model is achieved. An SA optimisation tool was developed using Matlab and incorporated into the cellular simulation in GIS to form an integrated SACA model. An application of the SACA model to simulate the spatio-temporal process of land-use change in Jinshan District of Shanghai Municipality, PR China, from 1992 to 2008 shows that this modelling approach is efficient and robust and can be used to reconstruct historical urban land-use patterns to assist with urban planning policy-making and actions. Comparison of the SACA model with a typical CA model based on a logistic regression method without the SA optimisation (also known as LogCA) shows that the SACA model generates better simulation results than the LogCA model, and the improvement of the SACA over the LogCA model is largely attributed to higher locational accuracy, a feature desirable in most spatially explicit simulations of geographical processes.  相似文献   

4.
基于神经网络的元胞自动机及模拟复杂土地利用系统   总被引:57,自引:9,他引:57  
黎夏  叶嘉安 《地理研究》2005,24(1):19-27
本文提出了基于神经网络的元胞自动机(CellularAutomata),并将其用来模拟复杂的土地利用系统及其演变。国际上已经有许多利用元胞自动机进行城市模拟的研究,但这些模型往往局限于模拟从非城市用地到城市用地的转变。模拟多种土地利用的动态系统比一般模拟城市演化要复杂得多,需要使用许多空间变量和参数,而确定模型的参数值和模型结构有很大困难。本文通过神经网络、元胞自动机和GIS相结合来进行土地利用的动态模拟,并利用多时相的遥感分类图像来训练神经网络,能十分方便地确定模型参数和模型结构,消除常规模拟方法所带来的弊端。  相似文献   

5.
本文提出一种基于随机森林的元胞自动机城市扩展(RF-CA)模型。通过在多个决策树的生成过程中分别对训练样本集和分裂节点的候选空间变量引入随机因素,提取城市扩展元胞自动机的转换规则。该模型便于并行构建,能在运算量没有显著增加的前提下提高预测的精度,对城市扩展中存在的随机因素有较强的容忍度。RF-CA模型可进行袋外误差估计,以快速获取模型参数;也可度量空间变量重要性,解释各空间变量在城市扩展中的作用。将该模型应用于佛山市1988-2012年的城市扩展模拟中,结果表明,与常用的逻辑回归模型相比,RF-CA模型进行模拟和预测分别能够提高1.7%和2.6%的精度,非常适用于复杂非线性特征的城市系统演变模型与扩展研究;通过对影响佛山市城市扩展的空间变量进行重要性度量,发现对佛山城市扩张模拟研究而言,距国道的距离与距城市中心的距离具有最重要的作用。  相似文献   

6.
Simulation and quantitative analysis of urban land use change are effective ways to investigate urban form evolution. Cellular Automata (CA) has been used as a convenient and useful tool for simulating urban land use change. However, the key issue for CA models is the definition of the transition rules, and a number of statistical or artificial intelligence methods may be used to obtain the optimal rules. Neighborhood configuration is a basic component of transition rules, and is characterized by a distance decay effect. However, many CA models do not consider the neighbor decay effect in cellular space. This paper presents a neighbor decay cellular automata model based on particle swarm optimization (PSO-NDCA). We used particle swarm optimization (PSO) to find transition rules and considered the decay effect of the cellular neighborhood. A negative power exponential function was used to compute the decay coefficient of the cellular neighborhood in the model. By calculating the cumulative differences between simulation results and the sample data, the PSO automatically searched for the optimal combination of parameters of the transition rules. Using Xiamen City as a case study, we simulated urban land use changes for the periods 1992–1997 and 2002–2007. Results showed that the PSO-NDCA model had a higher prediction accuracy for built-up land, and a higher overall accuracy and Kappa coefficient than the urban CA model based on particle swarm optimization. The study demonstrates that there exist optimal neighborhood decay coefficients in accordance with the regional characteristics of an area. Urban CA modelling should take into account the role of neighborhood decay.  相似文献   

7.
This paper reviews the practices, problems, and prospects of GISbased urban modelling. The author argues that current stand-alone and various loose/tight coupling approaches for GIS-based urban modelling are essentially technology-driven without adequate justification and verification for the urban models being implemented. The absolute view of space and time embodied in the current generation of GIS also imposes constraints on the type of new urban models that can be developed. By reframing the future research agenda from a geographical information science (GISci) perspective, the author contends that the integration of urban modelling with GIS must proceed with the development of new models for the informational cities, the incorporation of multi-dimensional concepts of space and time in GIS, and the further extension of the feature-based model to implement these new urban models and spatial-temporal concepts according to the emerging interoperable paradigm. GISci-based urban modelling will not only espouse new computational models and implementation strategies that are computing platform independent but also liberate us from the constraints of existing urban models and the rigid spatial-temporal framework embedded in the current generation of GIS, and enable us to think above and beyond the technical issues that have occupied us during the past ten years.  相似文献   

8.
基于遗传算法自动获取CA模型的参数   总被引:11,自引:1,他引:10  
杨青生  黎夏 《地理研究》2007,26(2):229-237
本文提出了基于遗传算法来寻找CA模型最佳参数的方法。CA被越来越多地应用于城市和土地利用等复杂系统的动态模拟。CA模型中变量的参数值对模拟结果有非常重要的影响。如何获取理想的参数值是模型的关键。传统的逻辑回归模型运算简单,常常用来获取模型的参数值,要求解释变量间线性无关,所以获取的城市CA模型参数具有一定的局限性。遗传算法在参数优化组合、快速搜索参数值方面有很大的优势。本文利用遗传算法来自动获取优化的CA模型参数值,并获得了纠正后的CA模型。将该模型应用于东莞1988~2004年的城市发展的模拟中,得到了较好的效果。研究结果表明,遗传算法可以有效地自动获取CA模型的参数,其模拟的结果要比传统的逻辑回归校正的CA模型模拟精度高。  相似文献   

9.
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.  相似文献   

10.
基于区块特征的元胞自动机土地利用演化模型研究   总被引:1,自引:1,他引:0  
针对传统元胞自动机模型中栅格式规则空间模拟复杂地理元素精度不高的问题,提出一种基于土地区块特征的非规则空间元胞自动机模型,以地理单元实质不规则实体形状作为元胞空间单元,进行土地利用变化的仿真模拟,运用MapInfo建立非规则空间元胞自动机模型的应用软件.对头灶镇土地利用演化的实证研究表明,非规则空间元胞自动机模型可以更真实地描述元胞地理信息、局部空间关系和演化规则,可为城市规划提供决策支持.  相似文献   

11.
元胞自动机CA(Cellular Automaton)与地理信息系统(GIS)的集成弥补了GIS在时空分析和时空演化方面的不足,为昆虫种群生态学的研究提供了新的手段。利用DEM提取地形因子,使用统计分析分析了昆嵛山腮扁叶蜂与林分因子、立地因子之间的关系。主要取得了腮扁叶蜂虫口密度与立地因子关系密切,并推导出了腮扁叶蜂的虫口密度与海拔、坡度、坡向、坡位的逐步逻辑回归数学模型。以数学模型结合空间自相关函数建立时空预测模型作为转换规则,以地理信息系统为平台利用元胞自动机模型模拟腮扁叶蜂传播,预测结果给出了昆嵛山腮扁叶蜂密度分布的结果,给防治决策提供了方便。  相似文献   

12.
城市扩张模拟为实现土地资源合理分配与制定城市发展规划政策提供依据。该文针对传统元胞自动机(CA)在城市扩张模拟中存在城市元胞密集区域团簇现象,耦合随机森林(RF)与基于斑块(Patch)扩张的CA模型,在顾及驱动因子重要性基础上构建基于斑块最大面积和城市扩张总量的双约束RF-Patch-CA模型,并利用该模型模拟重庆主城都市区2010-2017年城市扩张。结果显示:该模型总体精度达97.62%,相比传统的RF-CA、ANN-CA和Logistic-CA模型,Kappa系数分别提高了0.0222、0.0231和0.0245,FoM分别提高了0.0376、0.0391和0.0414;在景观相似度上,该模型相比以上3种模型分别提高了40.92%、41.16%和32.33%,最接近真实情况,而且避免了模拟结果产生城市元胞团簇现象,有效提高了城市扩张模拟精度。  相似文献   

13.
基于CA-ABM模型的福州城市用地扩张研究   总被引:3,自引:2,他引:1  
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。  相似文献   

14.
多智能体与元胞自动机结合及城市用地扩张模拟   总被引:15,自引:3,他引:12  
杨青生  黎夏 《地理科学》2007,27(4):542-548
运用多智能体(Agent)和元胞自动机(CA)结合来模拟城市用地扩张的方法,将影响和决定用地类型转变的主体作为Agent引进元胞自动机模型中,Agent在CA确定的城市发展概率的基础上,通过自身及其周围环境的状况,综合各种因素的影响做出决策,决定元胞下一时刻的城市发展概率。运用Agent的决策结果,对CA模型中以随机变量体现的不确定性通过Agent决策行为给予地理意义的新解释。以城市郊区—樟木头镇为例,对1988~1993年城市用地扩张进行了模拟研究,取得了良好的模拟效果。  相似文献   

15.
A novel generalized pattern search (GPS)-based cellular automata (GPS-CA) model was developed to simulate urban land-use change in a GIS environment. The model is built on a fitness function that computes the difference between the observed results produced from remote-sensing images and the simulated results produced by a general CA model. GPS optimization incorporating genetic algorithms (GAs) searches for the minimum difference, i.e. the smallest accumulated residuals, in fitting the CA transition rules. The CA coefficients captured by the GPS method have clear physical meanings that are closely associated with the dynamic mechanisms of land-use change. The GPS-CA model was applied to simulate urban land-use change in Kunshan City in the Yangtze River Delta from 2000 to 2015. The results show that the GPS method had a smaller root mean squared error (0.2821) than a logistic regression (LR) method (0.5256) in fitting the CA transition rules. The GPS-CA model thus outperformed the LR-CA model, with an overall accuracy improvement of 4.7%. As a result, the GPS-CA model should be a superior tool for modeling land-use change as well as predicting future scenarios in response to different conditions to support the sustainable urban development.  相似文献   

16.
地理元胞自动机模型研究进展   总被引:6,自引:0,他引:6  
赵莉  杨俊  李闯  葛雨婷  韩增林 《地理科学》2016,36(8):1190-1196
元胞自动机(Cellular Automata,简称CA)是一种基于微观个体的相互作用空间离散动态模型,其强大的计算功能、固有的平行计算能力、高度动态及空间概念等特征,使它在模拟空间复杂系统的时空动态演变研究具有较强的优势。文章回顾了元胞自动机的发展历程,阐述了CA在地理学中的主要应用领域和研究进展,在此基础上,以现实世界地理实体及现代城市扩张特征为视角,分析目前CA研究所面临的问题,并对其未来的研究趋势进行了初步探讨,认为以下3个方面将是未来CA研究的热点: 利用不规则元胞及可控邻域的CA模型,对不同规则或不同邻域地理实体的模拟研究; 采用三维元胞自动机对现代城市扩张进行立体化模拟,以克服二维CA模型的缺陷; 将矢量元胞自动机模型应用于地理实体的模拟研究,进一步提高模拟精度。  相似文献   

17.
元胞自动机被广泛应用于城市及其他地理现象的模拟,模拟过程中的最大问题是如何确定模型的结构和参数。该文提出一种基于分析学习的智能优化元胞自动机,该模型在逻辑回归模型的基础上,基于分析学习的智能方法,寻找元胞自动机模型的最佳参数。该方法允许用户控制空间变量影响权重,进而模拟出不同的城市发展模式,可为城市规划提供重要参考。  相似文献   

18.
This paper presents a fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on urban development is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. A defuzzification process converts the development potential to the required neighbourhood development level, which is taken by cellular automata as initial approximation for its transition rules. Such approximations are updated through spatial calibration over townships and temporal calibration with multi‐temporal satellite images. Assessment of the modelling results is based on three evaluation measures: fitness and Type I and Type II errors. The approach is applied to model the growth of the city of Indianapolis, Indiana over a period of 30 years from 1973 to 2003. A fitness level of 100 ±20% with 30% average errors can be achieved for 80% of the townships in urban‐growth prediction.  相似文献   

19.
This paper presents a prototype of a simulation model based on cellular automata (CA), and multicriteria evaluation (MCE) and integrated with GIS. Specifically, a method, analytical hierarchy process (AHP), of MCE is used here to derive behaviour-oriented rules of transition in CA. A ‘tight' integration strategy is adopted, which means that the modules of MCE and CA are written in the C programming language and built within ARC/INFO GIS. Designed to run on a workstation Unix SimL and fully utilizes the graphical user interface (GUI),which allows the modelto be driven by menusand automate the simulation of land conversion in the urban-rural fringe. The combination of three elements, GIS, CA, and MCE, has several advantages: visualization of decision-making, easier access to spatial information, and the more realistic definition of transition rules in CA.  相似文献   

20.
Cellular automata (CA), which are a kind of bottom-up approaches, can be used to simulate urban dynamics and land use changes effectively. Urban simulation usually involves a large set of GIS data in terms of the extent of the study area and the number of spatial factors. The computation capability becomes a bottleneck of implementing CA for simulating large regions. Parallel computing techniques can be applied to CA for solving this kind of hard computation problem. This paper demonstrates that the performance of large-scale urban simulation can be significantly improved by using parallel computation techniques. The proposed urban CA is implemented in a parallel framework that runs on a cluster of PCs. A large region usually consists of heterogeneous or polarized development patterns. This study proposes a line-scanning method of load balance to reduce waiting time between parallel processors. This proposed method has been tested in a fast-growing region, the Pearl River Delta. The experiments indicate that parallel computation techniques with load balance can significantly improve the applicability of CA for simulating the urban development in this large complex region.  相似文献   

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