基于MAS模型的土地利用空间优化研究方法综述

土地利用空间优化是实现土地资源合理利用和区域可持续发展的重要途径和手段,是目前研究的一个热点,在文献阅读的基础上,分析比较了数理统计模型、CLUE-S模型、元胞自动机模型、多智能体系统模型四种土地利用空间优化方法的优缺点.结果是:多智能体系统模型从土地利用的主体出发,选择影响土地利用空间优化的驱动因素,抽象定量化表达智能体的行为准则,利用智能优化算法来选择土地利用类型在空间上的演变过程,并在多目标函数及约束条件下判断土地利用空间优化方案的优劣性,很好的解决了土地利用空间优化过程中土地利用主体、土地利用环境、土地利用类型三个最主要问题在空间上的演变,比数理统计模型、CLUE-S模型、元胞自动机模型在土地利用空间优化方面更具有优势,是未来土地利用空间优化方法的发展趋势.     

规划情景约束下的城市土地利用空间格局模拟

以上海市为例,采用遥感与GIS技术,基于遥感影像及土地利用现状和社会经济统计数据,构建Dyna-CLUE模型模拟土地资源利用规模在土地利用规划政策情景约束下的空间格局,旨在为城市化进程中的土地利用规划实施,特别是土地利用宏观需求的空间配置提供技术思路。结果表明:遥感、GIS和Dyna-CLUE模型的集成应用,可从地理空间上定量刻画土地变化的驱动力,是模拟政策情景约束条件下土地资源空间分配问题的有效手段。     

北京市土地利用总体规划执行情况的评价方法

象任何一种决策一样, 土地利用总体规划也存在与现实情况的不符之处。因此, 在开展新一轮规划修编时 前有必要对上一轮的规划执行情况进行评价, 为规划修编提供借鉴和参考。基于《北京市土地利用总体规划( 1997~ 2010 年) 实施评价》研究时收集的相关资料, 借助ARCGIS9.0 的空间分析功能, 利用GIS 的技术和方法, 在分析和 研究土地利用变化的基础上, 识别规划执行最关心的三种类型: 符合规划地块、超出规划地块和规划未实施地块, 并将三种类型的地块定位和定量地绘制在规划执行情况评价图上。作为一种探索, 作者设计了一套针对土地利用 总体规划执行情况评价的GIS 技术路线和方法。本方法具有简便、操作性强, 可进行常规性或经常性的规划执行情 况监测等特点。     

流域土地可持续利用规划方法及应用研究

土地利用既受自然环境条件的种种制约,又对生态环境,尤其是水资源和水环境,产生深刻影响。因此,进行系统规划优化土地利用结构、协调土地利用和其他经济活动及生态环境保护的关系是非常必要的。基于土地利用系统是一个本征性灰色系统,本文以灰色多目标规划(GMOP)方法为核心,提出了一套流域土地利用灰色多目标规划模型。该方法既可有效地处理信息的不完备性和系统的动态性,又可全面地表达土地利用的多目标性。在对密云土地利用规划研究中,通过应用交互式调整和情景分析方法,得到该模型在两种情景下的优化方案,并结合密云实际情况综合分析,进行了方案筛选。     

淅川县土地利用结构低碳优化研究

在借鉴低碳经济、土地利用碳排放以及土地利用规划等理论成果和方法的基础上,以低碳理念为切入点,将低碳理念与土地利用结构优化相结合,提出低碳型土地利用结构优化的内涵、目标.通过线性规划模型,对土地利用的结构进行低碳优化,并对优化方案进行碳排放的估算评价,以验证规划的低碳性.结合河南省淅川县的实际情况进行实证研究,建立低碳型土地利用结构优化的多目标规划模型,在考虑土地利用经济效益的同时,强调土地利用的碳排放效益,以经济效益最大化和土地利用总碳排放量最小化2个目标函数来确定土地利用结构.     

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。     

基于多源数据融合的济南市西部新区碳排放评价研究（英文）

人类活动的碳排放量与城市化进程息息相关,城市土地利用、功能活力和交通系统组织是影响城市碳排放的重要因素。本文在厘清低碳生态城市空间结构特征的基础上,结合"评建结合"思想跟踪对比低碳生态城市建设情况,从规划方案和规划建成后两方面选取可量化的低碳生态城市空间特征为指标,评价并对比城市规划方案及规划建成后碳排放潜力。以济南市西部新城为例,测度其规划方案的建设用地多样性、到公共中心碳排放潜力、地块临街路网可达性及地块周边路网密度,测度建成后新区的城市功能混合度、城市功能密度、公交站点步行可达域和公交站点线路密度,并分别对其指标归一化后划分层级及等权重叠加,从区域及片区两层级评估碳排放潜力。评价结果表明:(1)规划方案中低碳排放潜力区域基本达到规划目标,体现了低碳生态的规划目标;(2)规划方案中各片区间及指标间不协调,建设用地多样性、地块邻接路网可达性区域差异较小,而出行碳排放潜力、路网可达性在各地块间差异较大;(3)规划建成后碳排放潜力尚未达到规划预期,低碳排放地块集中分布在长清老城区及党家镇中心地区;(4)建成后各片区碳排放指标差异较大,公共交通线路密度及城市功能混合度存在严重分布不均衡现象。     

“规土融合”的城乡结合部土地集约利用评价——基于城市规划目标导向的方法创新与实践

城乡结合部是城乡用地争夺的焦点区域和城市扩张的前沿阵地,开展土地集约利用评价、促进其土地的集约利用对保障城市未来发展空间至关重要。但由于城乡结合部土地权属复杂、土地利用类型多样、开发建设活动频繁,城乡结合部成为土地集约利用评价工作的难点。通过分析传统的基于土地利用现状的集约利用评价方法在城乡结合部应用的弊端,提出城乡结合部土地集约利用评价的重点在于考虑规划目标的土地利用潜力挖掘,进而构建"规土融合"的城乡结合部土地集约利用评价方法。结合城市规划边界、规划管理单元和规划地块确定评价范围和评价单元,从宏观、中观和微观3个层面提出包括人口、经济和生态承载力在内的评价体系。通过"规土融合"思想在城乡结合部土地集约利用评价过程的融入,达到以评价促规划、以规划管控土地集约利用的目的。     

土地混合使用视角下的地块间兼容度测度

在梳理已有土地兼容度的测度思路后,基于社会分隔的空间测度算法提出了一种从地块和街区双尺度测度地块间兼容度的新方法。与既有方法相比,新算法一方面将所有建设与非建设用地均纳入计算,力求更好地体现用地兼容度格局;另一方面也充分考虑了诸如相邻边长,领域面积等土地利用格局的重要空间几何特征,避免了传统算法无法量化距离衰减的缺陷,从而更加科学地描绘土地利用兼容度的分布特征。以湖南省湘潭市市辖区作为案例,在地块和街区2种尺度上进行实证研究。结果发现,湘潭市土地利用现状整体较为兼容,但仍然存在部分兼容度较低的聚集区域。这类区域基本位于城市郊区的工业园区和村集体用地上。其主要原因有二：其一,在工业园区中,过分重视工业企业的招商引资而忽视了规划管理,导致土地的真实利用情况与既有规划不符,一定程度上造成用地的不兼容现象;其二,在城边村的集体用地上,部分村级工业地块的无序扩张加剧了与宅基地、耕地等环境敏感用地的交织,继而形成不兼容的用地景象。最后,基于测度结果,从街区尺度上对湘潭市不兼容区域提出了对应的完善策略,以求在后续空间规划中提升湘潭市土地的混合利用程度。     

土地混合使用视角下的地块间兼容度测度——以湖南省湘潭市市辖区为例

在梳理已有土地兼容度的测度思路后,基于社会分隔的空间测度算法提出了一种从地块和街区双尺度测度地块间兼容度的新方法。与既有方法相比,新算法一方面将所有建设与非建设用地均纳入计算,力求更好地体现用地兼容度格局;另一方面也充分考虑了诸如相邻边长,领域面积等土地利用格局的重要空间几何特征,避免了传统算法无法量化距离衰减的缺陷,从而更加科学地描绘土地利用兼容度的分布特征。以湖南省湘潭市市辖区作为案例,在地块和街区2种尺度上进行实证研究。结果发现,湘潭市土地利用现状整体较为兼容,但仍然存在部分兼容度较低的聚集区域。这类区域基本位于城市郊区的工业园区和村集体用地上。其主要原因有二:其一,在工业园区中,过分重视工业企业的招商引资而忽视了规划管理,导致土地的真实利用情况与既有规划不符,一定程度上造成用地的不兼容现象;其二,在城边村的集体用地上,部分村级工业地块的无序扩张加剧了与宅基地、耕地等环境敏感用地的交织,继而形成不兼容的用地景象。最后,基于测度结果,从街区尺度上对湘潭市不兼容区域提出了对应的完善策略,以求在后续空间规划中提升湘潭市土地的混合利用程度。     

A heuristic cellular automata approach for modelling urban land-use change based on simulated annealing

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.     

Using simulated annealing for resource allocation

Many resource allocation issues, such as land use- or irrigation planning, require input from extensive spatial databases and involve complex decisionmaking problems. Spatial decision support systems (SDSS) are designed to make these issues more transparent and to support the design and evaluation of resource allocation alternatives. Recent developments in this field focus on the design of allocation plans that utilise mathematical optimisation techniques. These techniques, often referred to as multi-criteria decision-making (MCDM) techniques, run into numerical problems when faced with the high dimensionality encountered in spatial applications. In this paper we demonstrate how simulated annealing, a heuristic algorithm, can be used to solve high-dimensional non-linear optimisation problems for multi-site land use allocation (MLUA) problems. The optimisation model both minimises development costs and maximises spatial compactness of the land use. Compactness is achieved by adding a non-linear neighbourhood objective to the objective function. The method is successfully applied to a case study in Galicia, Spain, using an SDSS for supporting the restoration of a former mining area with new land use.     

Allocation of urban land uses by Multi-Objective Particle Swarm Optimization algorithm

Considering the ever-increasing urban population, it appears that land management is of major importance. Land uses must be properly arranged so that they do not interfere with one another and can meet each other's needs as much as possible; this goal is a challenge of urban land-use planning. The main objective of this research is to use Multi-Objective Particle Swarm Optimization algorithm to find the optimum arrangement of urban land uses in parcel level, considering multiple objectives and constraints simultaneously. Geospatial Information System is used to prepare the data and to study different spatial scenarios when developing the model. To optimize the land-use arrangement, four objectives are defined: maximizing compatibility, maximizing dependency, maximizing suitability, and maximizing compactness of land uses. These objectives are characterized based on the requirements of planners. As a result of optimization, the user is provided with a set of optimum land-use arrangements, the Pareto-front solutions. The user can select the most appropriate solutions according to his/her priorities. The method was tested using the data of region 7, district 1 of Tehran. The results showed an acceptable level of repeatability and stability for the optimization algorithm. The model uses parcel instead of urban blocks, as the spatial unit. Moreover, it considers a variety of land uses and tries to optimize several objectives simultaneously.     

Urban growth simulation by incorporating planning policies into a CA-based future land-use simulation model

Urban land-use change is affected by urban planning and government decision-making. Previous urban simulation methods focused only on planning constraints that prevent urban growth from developing in specific regions. However, regional planning produces planning policies that drive urban development, such as traffic planning and development zones, which have rarely been considered in previous studies. This study aims to design two mechanisms based on a cellular automata-based future land-use simulation model to integrate different planning drivers into simulations. The first update mechanism considers the influence of traffic planning, while the second mechanism can model the guiding effect of planning development zones. The proposed mechanisms are applied to the Pearl River Delta region, which is one of the fastest growing areas in China. The first mechanism is validated using simulations from 2000–2013 and demonstrates that simulation accuracy is improved by the consideration of traffic planning. In the simulation from 2013–2052, the two mechanisms are implemented and yield more realistic urban spatial patterns. The simulation outcomes can be employed to identify potential urban expansion inside the master plan. The proposed methods can serve as a useful tool that assists planners in their evaluation of urban evolvement under the impact of different planning policies.     

基于GIS的城市用地布局多情景模拟与方案评价——以江苏省太仓市为例

用地布局一直是城市总体规划中的关键难题,以往的规划方案多凭借规划师的经验判断、简单的图层叠加和有限的公众参与生成。然而新的城乡规划法要求从多角度综合考虑城乡用地布局问题,更加注重规划过程的科学性和准确性,也就特别需要有一种适应多情景分析下的城市用地布局模拟与方案评价方法。文章以江苏省太仓市为例,借助GIS技术的强大空间分析功能,探讨了这种方法的技术流程：① 参考已有的大尺度城市未来模型,结合我国特别是研究区的区域特点,构建一个实用的城市未来模型(Urban Future Model,UFM);② 通过用地评价、战略归纳、情景模拟等步骤,生成若干个可选的用地布局模拟方案;③ 应用多目标达成矩阵法从粮食、生态、灾害等多个角度对这些方案进行综合评价,并根据评价结果选择一个最佳方案作为本轮总规用地布局的规划参考方案。     

Simulating land-use dynamics under planning policies by integrating artificial immune systems with cellular automata

Cellular automata (CA) have been increasingly used in simulating urban expansion and land-use dynamics. However, most urban CA models rely on empirical data for deriving transition rules, assuming that the historical trend will continue into the future. Such inertia CA models do not take into account possible external interventions, particularly planning policies, and thus have rarely been used in urban and land-use planning. This paper proposes to use artificial immune systems (AIS) as a technique for incorporating external interventions and generating alternatives in urban simulation. Inspired by biological immune systems, the primary process of AIS is the evolution of a set of ‘antibodies’ that are capable of learning through interactions with a set of sample ‘antigens’. These ‘antibodies’ finally get ‘matured’ and can be used to identify/classify other ‘antigens’. An AIS-based CA model incorporates planning policies by altering the evolution mechanism of the ‘antibodies’. Such a model is capable of generating different scenarios of urban development under different land-use policies, with which the planners will be able to answer ‘what if’ questions and to evaluate different options. We applied an AIS-based CA model to the simulation of urban agglomeration development in the Pearl River Delta in southern China. Our experiments demonstrate that the proposed model can be very useful in exploring various planning scenarios of urban development.     

基于约束性CA方法的北京城市形态情景分析

约束性元胞自动机(Constrained cellular automata,Constrained CA) 在模拟城市增长方面已有诸多实践,已有文献常利用各种反映土地利用需要、区位影响、管理制度等的政策参数,设定不同的城市空间发展情景以反映未来的城市形态。在基于约束性CA进行城市形态情景分析时,以各种政策参数作为情景条件的研究实例较多。而在中国的城市规划实践中,城市规划用于建设管理的审批,对应明确的城市形态,因而如何利用城市形态作为情景条件分析所需政策,也有实践意义,可以解决一些广为关注的重要问题,例如已有的发展政策是否与期望的城市形态相匹配,不同规划方案所需采取的政策有什么区别等。本文提出了以城市形态作为情景条件(即形态情景分析) 的新方法,该方法基于约束性CA,改变了传统的约束性CA情景条件的设置方法,以期望的未来城市形态为目标,识别相应需要的发展政策。并将北京市域的4 个规划城市形态作为情景条件进行了实证分析,对多个规划方案实施的可能性和政策参数进行对比分析,证明该方法具有较好的适用性和可行性,是将约束性CA的应用扩展到城市规划领域的又一尝试。     

Planning for growth in a natural resource boomtown: challenges for urban planners in Fort McMurray,Alberta

Between 2000 and 2010, the population of the city of Fort McMurray, Alberta increased by 80%, mainly due to the expansion of oil extraction projects and subsidiary industries. Population growth of this magnitude has significant consequences for city planning. While Fort McMurray struggles to keep up with enormous numbers of in-migrants, the cost of living in the city has skyrocketed. Using interviews with city planners and field experience in the city, in this paper I examine the current challenges faced by urban planners in Fort McMurray against the backdrop of global economic decision-making, corporate influence, and commodity dynamics. While the recession of 2008 gave city planners some breathing room, they still struggle with gathering accurate census information and predicting population growth, providing affordable housing, and balancing short-range planning with their long-term goals. Attempts by city planners to address these challenges could provide a contemporary model for urban planning in rapidly growing, resource-dependent communities.     

Planning Beijing: socialist city,transitional city,and global city

Cities are centers of economic, social, and political change, and urban planning is a process responding to and guiding urban change and development. In the Maoist era and under the influence of socialist ideology, China limited urbanization while promoting industrialization, and urban planning served as an instrument for socialist construction. Since the reform of the late 1970s, Chinese cities have experienced unprecedented growth and restructuring. However, the gradualist, exploratory reform—exemplified by Deng Xiaoping’s slogan “crossing the river by feeling the stones”—makes Chinese cities constantly change without clear directions for future development. This paper uses Beijing as a case study to analyze changing institutional and global contexts underlying the transformation of Chinese cities, and planners’ responses and dilemmas in making plans and implementing them. We found that market reforms, rapid growth, and dramatic change make urban master plans quickly out of date, forcing Chinese planners to frequently revise these master plans. We also found that the content of urban master planning in China has broadened from physical planning, and Chinese planning has adapted to market reform through utilizing concepts of visioning, flexibility, and governance. Increasingly what we call a “hybrid” form of planning is arising in which global concepts and Chinese ideas interweave in order to direct the shape and form of the Chinese metropolis.     

Integration of linear programming and GIS for land-use modelling

Abstract

Geographical Information Systems (GIS) are becoming basic tools for a wide variety of earth science and land-use applications. This article presents linear programming (LP) as a promising tool for spatial modelling within a GIS. Although LP is not properly a spatial technique, it may be used to optimize spatial distributions or to guide the integration of variables. An example of the use of LP in land-use planning is described, with minimizing rural unemployment as the main goal. Technical, financial and ecological constraints are established to show the influence of several limitations on achieving the optimal solution. LP makes it possible to achieve optimal land-use, where the objective is maximized and the constraints respected. LP can also be used to simulate different planning scenarios, by modifying both the objective function coefficients and the constraints. The integration of LP and GIS is presented in two phases: (i) acquisition of attribute data for the LP model, and (ii) modelling and mapping the results.