基于城市流和层级性的城市群扩展模型构建

城市群是具有网络关系与层级性的区域空间,一直是中国推进城镇化与区域协调发展的主体单元。本文综合考虑城市群的网络与层级性特征,运用城市流刻画城际网络交互作用,采用分层广义线性模型（HGLM）揭示城市群分层驱动机制。同时,选取长江中游城市群开展实证研究,通过与元胞自动机（CA）耦合,构建HGLM-CA模型模拟城市群空间扩展。将模拟结果与Logistic-CA模型、BBO-CA模型进行比对,据此评析HGLM-CA模型的优劣与改进方向。实证结果表明：城市群空间扩展是多层驱动因素共同作用的结果,城市流不仅会推动城市群空间扩展,而且对元胞层因素起到重要的调节作用,使之具有城际分异性;HGLM-CA模型相比Logistic-CA模型模拟精度更高,说明顾及城市流与层级性的城市群空间扩展模拟结果更为精准;与智能模型BBO-CA相比,HGLM-CA模型模拟精度较低,但其便于从层级性角度把握城市群空间扩展机制。     

北京城市边缘区城市化过程与空间扩展——以大兴区为例

城市边缘区空间扩展研究是探讨城市未来空间结构和形态演变的基础。本文基于北京大兴区1994、2001和2006年3期TM遥感影像资料提取城镇用地信息,通过对城市扩展强度、城市扩展梯度、城市边缘区空间扩展模式等建设用地的总体扩张行为进行研究,分析研究区十多年来城市化进程中城镇建设用地扩展的时间过程和空间格局特征,对明确未来城市边缘区土地利用发展方向,提高土地利用效率和城乡建设效益提供基本依据。结果显示,大兴区城市土地利用扩展强度不断增强;中心城区以及中心区面积的不断扩张,导致建设用地在高指数区间集中的趋势明显,农村地区小城镇建设的高速发展使得低指数区间的建设用地面积大幅度增加;根据城市化扩展梯度,大兴区分为城市化高速扩展带、城市化快速扩展带和城市化低速扩展带;紧邻中心区的城市化高速扩展带,以集中连片式扩展为主,该模式在边缘区空间扩展中居于主导地位。城市化快速发展带土地利用以轴向扩展模式为主,轴向扩展稳定地影响着大兴区城市化进程。独立发展模式随着城市经济的快速发展其影响将明显增强,逐渐成为城市边缘区空间扩展的主要形式。     

Modeling urban land-use dynamics in a fast developing city using the modified logistic cellular automaton with a patch-based simulation strategy

Cellular automata (CA) have been used to understand the complexity and dynamics of cities. The logistic cellular automaton (Logistic-CA) is a popular urban CA model for simulating urban growth based on logistic regression. However, this model usually employs a cell-based simulation strategy without considering the spatial evolution of land-use patches. This drawback largely constrains the Logistic-CA for simulating realistic urban development. We proposed a Patch-Logistic-CA to deal with this problem by incorporating a patch-based simulation strategy into the conventional cell-based Logistic-CA. The Patch-Logistic-CA differentiates new developments into spontaneous growth and organic growth, and uses a moving-window approach to simulate the evolution of urban patches. The Patch-Logistic-CA is tested through the simulation of urban growth in Guangzhou, China, during 2005–2012. The cell-based Logistic-CA was also implemented using the same set of data to make a comparison. The simulation results reflect that the Patch-Logistic-CA has slightly lower cell-level agreement than the cell-based Logistic-CA. However, visual inspection of the results reveals that the cell-based Logistic-CA fails to reflect the actual patterns of urban growth, because this model can only simulate urbanized cells around the edges of initial urban patches. Actually, the pattern-level similarities of the Patch-Logistic-CA are over 18% higher than those of the cell-based Logistic-CA. This indicates that the Patch-Logistic-CA has much better performance of simulating actual development patterns than the cell-based Logistic-CA. In addition, the Patch-Logistic-CA can correctly simulate the fractal structure of actual urban development patterns. By varying the control parameters, the Patch-Logistic-CA can also be used to assist urban planning through the exploration of different development alternatives.     

区域尺度城市增长时空动态模型及其在京津唐都市圈应用

Dynamic urban expansion simulation at regional scale is one of the important re-search methodologies in Land Use/Cover Change (LUCC) and global environmental change influenced by urbanization.However,previous studies indicate that the single urban expan-sion simulation for future scenarios at local scale cannot meet the requirements for charac-terizing and interpreting the interactive mechanisms of regional urbanization and global en-vironmental change.This study constructed a regional Dynamic Urban Expansion Model (Reg-DUEM) suitable for different scenarios by integrating the Artificial Neural Network (ANN) and Cellular Automaton (CA) model.Firstly we analyzed the temporal and spatial character-istics of urban expansion and acquired a prior knowledge rules using land use/cover change datasets of Beijing-Tianjin-Tangshan metropolitan area.The future urban expansion under different scenarios is then simulated based on a baseline model,economic models,policy models and the structural adjustment model.The results indicate that Reg-DUEM has good reliability for a non-linear expansion simulation at regional scale influenced by macro-policies.The simulating results show that future urban expansion patterns from different scenarios of the metropolitan area have the tremendous spatio-temporal differences.Future urban ex-pansion will shift quickly from Beijing metropolis to the periphery of Tianjin and Tangshan city along coastal belt.     

一种顾及驱动因子重要性的双约束RF-Patch-CA城市扩张模拟方法

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。     

Modeling different urban growth patterns based on the evolution of urban form: A case study from Huangpi,Central China

Spatial patterns of urban expansion mainly include infilling, edge expansion, and outlying growth patterns. The cellular automata (CA) model, is an important spatio-temporal dynamic model and effectively simulates infilling and edge-expansion urban expansion. but is evidently lacking in outlying scenarios. In addition, CA cannot explain the causes and processes of urban land expansion. Given these limitations, we proposed a novel urban expansion model called simulation model of different urban growth pattern (SMDUGP), which can work well in both adjacent (i.e., infilling and edge expansion) and outlying growth patterns. SMDUGP has two main components. First, we divided the non-urban region into two categories, namely, candidate region for adjacent pattern urban growth (CRFAP) and candidate region for outlying pattern urban growth (CRFOP). Second, different methods were utilized to simulate urban expansion in the different categories. In CRFAP, a CA model based on the potential of urban growth was proposed to simulate urban growth in relatively randomly selected urban growth regions based on the discrete selection model and Monte Carlo method as the expansion area was implemented in CRFOP. Huangpi, a suburban area in Wuhan, is utilized as the case study area to simulate the spatial and temporal dynamics of urban growth from 2004 to 2024. SMDUGP can effectively simulate outlying urban growth with a highly improved simulation precision compared with the traditional CA model and can explain the causes and processes of urban land expansion.     

Analyzing the Impacts of Urban Expansion on Green Fragmentation Using Constraint Gradient Analysis

Many existing gradient analysis methods are arbitrary or too simple in gradient partitioning and unsuitable for cities with irregular forms. We propose an improved gradient analysis method with urban structural features as spatial constraints to properly partition an urban area into more homogeneous buffers. Taking the Wuhan metropolitan area in China as an example, we use the improved gradient partitioning method and six landscape metrics to characterize urban expansion and green space fragmentation in 1989, 2001, and 2013 and investigate the relationship between urban green fragmentation and urban expansion using correlation analysis and regression modeling. The results show that the fragmentation of built-up area in each buffer generally decreases from 1989 to 2013, but the fragmentation of green space increases. For each time point, with growing distance from urban centers, the fragmentation of built-up area increases and green space fragmentation decreases. This shows that urbanization exerts a significant influence on fragmentation of urban green space from both a temporal and a spatial perspective. Intensive urban expansion moved outward mainly at the cost of agricultural land and resulted in more fragmented green space in the urban fringe. Further quantitative analyses show that the area ratio and fragmentation of the built-up area are statistically negatively correlated with the fragmentation of green space. The improved gradient analysis with spatial constraints can generate more homogeneous ring gradients and then lead to more reasonable results, thereby helping to better understand how urban expansion affects landscape dynamics.     

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。     

长三角地区城市化空间关联特征及内在机制

中国正处于城市化快速发展阶段,但当前研究在综合反映城市化的时空特征时,往往忽略区域城市间的空间关联及其演化过程,无法有效地揭示区域城市间的相互影响和内在机制。基于空间极化及扩散理论和系统分析方法,剖析了长三角地区城市化的空间演化过程。结果显示:① 1995—2015年间长三角地区城市化的规模等级特征明显,作为区域增长极,上海处于第一等级,南京、杭州、苏州为第二等级;城市化空间关联指数也表明,以上海、苏州、杭州等10个城市构成区域最为密集的空间联系网络。② 研究时段内,城市化过程中空间极化和空间扩散同时存在,且空间极化的城市往往会进入新的扩散阶段,以南京、杭州等城市表现最为明显。该结果证实了各城市间在不同发展阶段具有不同的空间作用关系。本文还探讨了区域城市化的驱动机制,表明区域内产业升级和转移是形成空间极化或扩散作用的主要内生动力。本研究可为区域发展规划提供重要的科学支撑。     

Simulating urban dynamics by coupling top-down and bottom-up strategies

ABSTRACT

Cellular automata (CA) are effective tools for simulating urban dynamics. Coupling top-down and bottom-up CA models are often used to address macro-scale demand and micro-scale allocation in the simulation of urban dynamics. However, those models typically ignore spatial differences in terms of the coupling process between macro-scale demand and micro-scale allocation. Herein, a novel approach for combining top-down and bottom-up strategies based on simulating urban dynamics is proposed. An optimizing strategy was used to predict the parameter of the inverse S-shaped function of future urban land use pattern and further deduce urban land increment within each concentric ring. The maximum probability transformation rule was incorporated into the CA model to address the micro-scale allocation. Wuhan was selected to test the performance of the proposed approach, and the conventional and the proposed approaches were compared. The results demonstrated that the proposed approach can not only retain the model’s accuracies but also better simulate the macro morphology of urban development dynamics and generate more realistic urban dynamic pattern in the urban sub-center and fringe regions. The proposed coupling approach can also be used to generate different development scenarios. The approach is expected to provide new perspectives for coupling top-down and bottom-up CA models in modeling urban expansion.     

中国城镇建设用地投入非协调性的动态演变研究

基于国情和现实发展,对中国城镇建设用地投入非协调性进行了分析。通过构建城镇建设用地投入非协调性指数模型,综合测度了2000~2009年期间中国各省区城镇建设用地投入之于城镇人口、GDP、固定资产投资、地方财政税收、产业就业非农化以及社会非农化的非协调性程度及其动态演变过程、趋势和类别,并在此基础上对其产生的原因进行剖析,最后就如何协调中国城镇建设用地投入提出调控对策与优化途径。结果表明:中国城镇建设用地投入非协调整体呈"波浪式"的下降趋势,但整体效益水平还有待提高;非协调性分类及其演化以相对协调型和滞后型为主,且有着明显的区域特征;演变机理分析表明资源要素禀赋与区域差异、国家宏观调控、体制制约、历史遗留和行政区划调整是造成非协调性的主要原因;最后从体制环境改革、全国主体功能区划和区级财政转移支付视角提出优化调控对策。     

Parallel cellular automata for large-scale urban simulation using load-balancing techniques

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.     

基于Logistic回归的CA模型改进方法——以广州市为例

基于Logistic回归的CA模型因其结构简单和数据要求相对较小的优势,被广泛应用于城市模拟领域,但数据的空间自相关性影响了模型机制挖掘与模拟精度。通过将影响城市发展演变的各种约束条件划分为强制和普通约束条件,以及运用主成分分析降低普通约束条件的数据相关性,构建了改进型Logistic回归CA模型,并在2000~2008年广州市城市增长模拟研究中进行应用。结果表明:与传统型Logistic回归CA模型相比,改进型Logistic回归CA模型在模型拟合度和精度上均有4%左右的提高。其中约束条件划分对非城市像元模拟精度约有6%的提高,对整体精度有3%的提高。更为重要的是,降低数据相关性后,Logistic回归CA模型对于城市扩展机制的解释更符合实际。本研究旨在寻求一种简单可行且易于构建的CA模型,探求城市发展机理,为城市规划管理提供更为准确的科学依据。     

地理元胞自动机模型研究进展

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：① 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;② 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;③ 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。     

中国省际教育城镇化的时空特征及影响因素

构建教育城镇化水平测度方法,利用变化弹性系数、变异系数、多元回归模型分析了1987~2014年中国省际教育城镇化的时空特征及影响因素。研究表明：① 教育城镇化水平稳步上升,整体呈现“快-慢-快”的时序变化特征。② 教育城镇化变化弹性系数波动显著,教育城镇化提升速度整体高于人口城镇化。③ 教育城镇化水平区域差异明显,省际教育城镇化差异度逐渐减小,省际均衡性明显提升。④ 人口城镇化水平、城乡发展差距、城乡教育制度二元化3个主要影响因素的时空变迁及其叠加作用的变迁共同推动了中国教育城镇化时空格局演变。     

Calibration of an urban cellular automaton model by using statistical techniques and a genetic algorithm. Application to a small urban settlement of NW Spain

Cellular automata (CA) stand out among the most commonly used urban models for the simulation and analysis of urban growth because of their ability to reproduce complex dynamics, similar to those found in real cities, from simple rules. However, CA models still have to overcome some shortcomings related to their flexibility and difficult calibration. This study combines various techniques to calibrate an urban CA that is based on one of the most widely used urban CA models. First, the number of calibration parameters is reduced by using various statistical techniques, and, second, the calibration procedure is automated through a genetic algorithm. The resulting model has been assessed by simulating the urban growth of Ribadeo, a small village of NW Spain, characterized by low, slow urban growth, which makes the identification of urban dynamics and consequently the calibration of the model more difficult. Simulation results have shown that, by automating the calibration procedure, the model can be more easily applied and adapted to urban areas with different characteristics and dynamics. In addition, the simulations obtained with the proposed model show better values of cell-to-cell correspondence between simulated and real maps, and the values for most spatial metrics are closer to real ones.     

南昌地区建设用地空间扩展的广义转移概率模型建设与应用研究

对南昌地区城市发育约束因素的分析的基础上,基于非城市像元所处的城市化梯度、距离最近建成区斑块的距离、最近建成区斑块的规模、边缘像元的邻域水平等4个城市景观格局因子和道路及地形等两个社会经济和自然影响因子,构建了广义转移概率模型,并开展了相关的动态模拟研究。表明,与传统模拟方法相比,该模型具有比较理想的精度水平,模拟结果能够很好地反映南昌地区今后城市建设用地发展趋势,提出的模型手段改进设计获得了令人满意的效果,是对现行城市景观动态模拟研究工作的一个重要的方法论补充和完善。     

长江三角洲地区城市空间扩展研究

城市化是建设用地扩展的主要驱动因素,分析建设用地时空演化格局已成为学者研究城市化过程的重要视角。采用空间自相关等方法,测度了1985年以来长江三角洲地区城市空间扩展的集聚特征并分析其演变过程;并结合格网建设用地密度频率的变化特点,将空间划分为不同的景观梯度地带,以此研究城市空间在不同地带中的扩展特点。研究结果表明,长三角城市空间扩展聚集程度先降后升,城市化区域融合趋势明显,并在城市空间扩展中表现出以上海、南京和苏州等为代表的3种模式,反应了长三角内部不同的经济发展特点。此外,在不同景观梯度下,长三角城市空间扩展表现出典型的阶段性特征。2000年以前在各个景观梯度下城市空间扩展差异较小,表现为较强的拓展性扩展;2000年以后,在城市核心区扩展强度加强,表现为填充式扩展加快。同时,城乡过渡区面积增加迅速,表明随着城市空间扩展的加速,长江三角洲地区城市土地不集约利用现象已较为突出。     

Modeling urban growth in a metropolitan area based on bidirectional flows,an improved gravitational field model,and partitioned cellular automata

Simulating urban landscape dynamics in metropolitan areas has attracted much attention lately, but the difficulty remains. Although large-scale urban simulation studies consider spatial interaction as an important factor, spatial interaction cannot be accurately measured based on a single element flow, and its effects may not strictly follow a distance decay function. Furthermore, different cities may require different transition rules. In this study, we combined bidirectional flows of population and information and an improved gravitational field model to model the urban spatial interaction, and we then integrated a partitioned cellular automata (CA) model to simulate the urban growth for different cities in the Yangtze River middle reaches megalopolis. It was found that the simulation results generated by the CA model considering spatial interaction are significantly improved. Furthermore, partitioned conversion thresholds can effectively improve the model performance. The proposed model showed a much better performance in the simulation of subordinate cities surrounding the core cities, than for the core cities and fringe cities. We suggest that large-scale urban simulation should pay more attention to the development of partitioned transition rules. The effects of intercity urban flows should also be considered in the simulation of small- and medium-sized cities near the regional cores.     

基于元胞自动机的城市发展密度模拟

元胞自动机CA越来越多地被用于模拟复杂的城市系统,但这些模拟基本不考虑城市的发展密度。不同的城市发展密度会对城市的形态有很大的影响,有必要将城市的发展密度引进CA的城市模拟中,以获得更好的模拟结果。本文将密度梯度函数引进了CA模型的转换规则中,并定义‘灰度’来反映状态的转换。利用该模型对不同可能的城市发展组合进行了模拟,为城市规划提供了辅助依据。