景观连通性理论在城市土地适宜性评价与优化方法中的应用

针对传统的土地适宜性分析方法忽略景观水平生态过程的问题,本文将景观连通性理论应用于土地适宜性评价方法的不同阶段,以达到优化城市生态系统的目标。首先选择影响生物水平流动的主要要素作为评价因子,应用于长沙市望城区滨江片区,确定案例区的土地适宜性评价结果,建构城市土地景观过程阻力评价体系。通过水文连通性分析方法及分布式水文模型确定案例区的潜在雨水生态廊道,将之与土地适宜性评价结果进行加权叠加,根据评估结果,提出案例城市土地适宜性评价的优化方案。结果表明:景观连通性方法适用于传统城市土地适宜性评价方法的改进以及评价结果的优化。     

土地利用规划的多目标规划模式探讨

根据多目标决策理论，探讨了土地利用总体规划实现的方法模式。多目标规划模式是以计算机和ＧＩＳ技术为手段，以建立土地资源数据库－进行土地多宜性评价－多目标决策－多方案比较选优为主要过程实现规划的方法。     

基于次序权重平均法的购房选择地理空间多准则决策

居民的购房选择是对居住区位进行选择的复杂过程,其实质是居住空间的个人行为决策问题。在调研工作基础上,论文分析并构建了居民购房选择决策评价指标体系,以北京市为实验区应用GIS制作居住适宜性基础准则(指标)地图。研究一种可以适应购房者差异化的购房需求与偏好的购房地理空间决策方法,通过层次分析法提取购房个体的偏好信息,确定个人准则权重。采用次序加权平均算法(Ordered Weighted Averaging,OWA)针对个人准则权重计算个人次序权重,结合二者对居住适宜性基础准则地图进行集结,计算多种决策风险下的个人居住适宜性准则地图,对意向住房进行分析评价,动态生成相应决策方案,为购房者提供购房决策支持,减少主观意愿与客观环境带来的决策风险。最后通过一个实验对以上方法进行实现。     

土地利用规划的多目标规划模式探讨

根据多目标决策理论，探讨土地利用总体规划实现的方法模式。多目标规划模式是以计算机和ＧＩＳ技术为手段，以建立土地资源数据库—进行土地多宜性评价—多目标决策一多方案比较选优为主要过程实现规划的方法     

国外基于GIS土地适宜性评价研究进展及展望

土地适宜性评价是土地利用总体规划的一项基本工作和重要内容。随着全球人口的增长及环境问题的日益加剧,研究探讨土地适宜性是处理好人口与资源、走可持续发展之路的重要课题。通过对大量文献的检索,较为系统地总结了国外学者有关基于GIS的土地适宜性评价的观点,按照土地适宜性评价方法的发展历程,将其分为三个方面：计算机辅助叠加制图、基于GIS多指标决策方法和人工智能建模。对于目前常用的基于GIS多指标决策和人工智能建模两种方法进行了评析;并提出评价方法正向精确化、综合化和动态化的方向发展,建议注重土地适宜性评价方法的空间尺度转换,力争在未来实现网络化、可视化。     

基于LP-MCDM-CA模型的土地利用结构优化研究——以天水市为例

土地利用类型数量在地域空间上的优化配置是实现土地可持续利用,提高土地聚集效应和保持土地生态系统平衡的重要途径.针对当前土地利用优化配置模型存在的不足,构建了基于多目标线性规划与元胞自动机的土地利用优化配置模型(MCDM-CA),在定义邻域规则、转换规则和土地适宜性评价的基础上,开展了基于经济效益、生态效益最大化的土地利用空间配置,实现了土地资源数量结构优化与空间布局优化的统一;并运用该模型对天水市土地利用结构优化进行了实证研究.研究表明,该模型兼顾到区域宏观水平上的土地利用数量结构与局部尺度上的土地利用适宜性,能够较好地同时模拟不同土地利用类型以及不同人类决策情景下的土地利用效果.本研究可为解决土地利用规划中的资源优化配置关键问题提供新的技术方法.     

基于多目标决策和CA 模型的土地利用变化 预测模型及其应用

结合宏观用地总体需求与微观土地利用适宜性, 集成灰色预测模型、多目标决策模型、 元胞自动机模型、地理信息系统技术方法, 建立了GCMG 土地利用变化预测模型。GCMG 模型包括非空间和空间2 个模块, 非空间模块侧重依据宏观社会经济发展趋势预测研究区未 来的总体用地需求变化, 而空间模块集成多目标决策模型、元胞自动机、地理信息系统等技 术方法实现了基于土地适宜性的土地利用空间配置。运用该模型对龙海市2000-2010 年土地 利用变化进行了情景模拟, 结果表明园地和建设用地是该区域内变化最为显著的用地类型, 基本农田保护政策严格实施与否将对龙海市未来土地利用变化产生深远的影响。GCMG 模型 在龙海市的应用实例表明, 该模型将土地利用系统作为一个整体, 兼顾到区域宏观水平上的 土地利用需求与局部尺度上的土地利用适宜性, 能够较好地同时模拟不同土地利用类型以及 不同人类决策情景下的土地利用转换概率, 因而可为理解土地利用多尺度复杂系统提供一定 的帮助。     

基于OWA的大理市土地生态安全评价研究

从自然生态环境角度出发,从自然因子、生态环境因子、景观因子3个层面选取16项评价指标建立大理市土地生态安全评价体系,并运用IDRISI软件中的MCE模块进行有序加权平均算子（OWA）多准则决策评价,得到不同决策风险系数下的大理市土地生态安全评价结果。结果显示,由于决策者风险态度不同,得到土地生态安全评价结果差异较大,在实际应用中,必须结合研究区的实际情况以及规划的目的选择不同的风险系数进行评价,才能得到更加真实有效的结果。     

流域可持续评价的最大熵原理——投影寻踪耦合模型

在传统投影寻踪方法的基础上,综合考虑投影向量优化中的不确定性,提出基于最大熵原理的多准则投影寻踪方法,利用加速遗传算法对多准则目标函数进行优化求解。根据投影值与标准等级值的散点图趋势关系,建立了三次趋势曲线评价模型。淮河流域可持续性评价的实例结果表明了该模型在求解评价问题中的有效性。该模型同样适用于其它领域的综合评价问题。     

唐山市土地利用防灾适宜度评价方法分析

基于GIS的防灾适宜度多准则评价(MCE)是土地利用防灾规划的关键。根据唐山市地质灾害资料,建立基于距离的防灾适宜度评价准则并量化评价指标。依据决策风险指标计算次序权重,应用层次分析程序(AHP)构建比较矩阵并计算准则权重,分析基于GIS的OWA方法、布尔决策和权重线性叠加(WLC)等多准则评价方法的决策风险,确定唐山市土地利用防灾评价策略。基于决策风险和指标补偿原则计算次序权重、准则权重和一致性比率,得到唐山市土地利用防灾适宜度评价结果,据此提出唐山市土地资源合理利用建议。     

城市居住用地防灾适宜度评价的OWA方法

城市居住用地的安全受到多种灾害威胁,防灾决策的主要问题之一是开发基于GIS的多准则评价 (MCE)方法。文章介绍了在基于GIS的次序权重平均法 (OWA)中,依据重要性等级计算次序权重和应用层次分析程序 (AHP)构建比较矩阵计算准则权重的方法;通过OWA评价方法与布尔决策和权重线性叠加 (WLC)等多准则评价方法的比较,分析了不同方法的决策风险和指标等级重要次序的影响,并以唐山市为例,建立了各灾害因子的适宜度评价准则,计算了唐山市居住用地的防灾适宜度,对唐山市居住用地的合理开发提出了几点建议。     

Exploring multi-criteria decision strategies in GIS with linguistic quantifiers: an extension of the analytical network process using ordered weighted averaging operators

Many real-world spatial planning and management problems give rise to a geographical information system (GIS)-based multi-criteria decision-making. Analytical network process (ANP) provides a comprehensive methodology for representing complex multi-criteria decision-making problems as a network of criteria and alternatives, where feedback and interdependence relationships may exist within and between all the criteria and alternatives. Experts’ experiences are used to estimate relative magnitudes of tangible and intangible factors through paired comparisons in order to make rational and consistent decisions. However, the GIS-based ANP, an adoption of weighted linear aggregation rule, typically employed a high trade-off decision strategy and neglected other decision strategies. This paper develops a novel GIS-based multi-criteria evaluation (MCE) procedure by extending the ANP using fuzzy quantifiers-guided ordered weighted averaging (OWA) operators. This extension, which generalizes the aggregation process used in the ANP, would provide a generic powerful decision-making tool that allows decision-makers to define a decision strategy on a continuum between pessimistic (risk-averse) and optimistic (risk-taking) strategies. By changing the linguistic quantifiers, the GIS-based ANP–OWA can generate a wide range of decision strategies taking into accounts the level of risk the decision-makers wish to assume in their MCE. A land-use suitability analysis in a region of Saudi Arabia is presented to demonstrate the application of the proposed procedure.     

Multi-criteria Decision-Making Approaches to Agricultural Land Suitability Classification of Malda District,Eastern India

Land suitability classification (LSC) is an approach of land evaluation, which measures the degree of appropriateness of land for a specific land use. LSC is governed by a myriad of factors at the local and regional level including physiographic, pedologic and a host of socioeconomic and infrastructural determinants. This has called for the application of different multi-criteria decision-making (MCDM) techniques in agricultural LSC. The present study has attempted and compared various MCDM-based agricultural LSCs for Malda District in Eastern India. The study is based on multiple parameters governing agriculture, considering not only the physiographic and pedological attributes (e.g., relief, slope, soil fertility, soil organic carbon, etc.) but also the socioeconomic ones (e.g., the percentage of people engaged in agriculture, cultivator–labor ratio, degree of electrification, etc.). Four major MCDM algorithms have been applied, i.e., composite ranks, composite Z-scores, analytical hierarchy process (AHP) and weighted principal component analysis (WPCA). The results were also compared with the crop productivity-based agricultural efficiency. It was observed that about 15.44% of the area of Malda District is highly suitable for agriculture, whereas limited suitability is displayed by about 12.68% of area. The remaining part falls under moderate and marginal suitability classes. Furthermore, WPCA and AHP are superior to the nonparametric techniques of MCDM, namely composite ranks and composite Z-score. Moreover, the results of WPCA are superior to those of AHP. Due to the inherent limitations of the AHP approach, this study proposes the use of WPCA in the domain of agricultural LSC.

     

Strategies for improving land delivery for residential development: a case of the north-west metropolitan Melbourne

One of the factors affecting the housing supply is closely linked to the time taken to complete the land development assessment approval. Delays in completing the development process on time often results in difficulties of increasing housing supply. In parallel, housing demand continues to increase with increasing net population in Australian urban areas. This research aims to identify the current issues and challenges of releasing land for housing development in the established suburbs of Melbourne north-west area (involving six local government areas: Brimbank, Maribyrnong, Moreland, Moonee Valley, Hume and Melton). An application of multi-criteria decision making (MCDM) using the strategic residential potential assessment (SRPA) method is considered. This is designed to improve the method of land administration strategies for housing development. The analysis is set within the context of investigating land preparation processes and their impacts on land availability for housing supply. The research adopts interview techniques to gain insight into the processes of land release through the activities of town planners in the selected local council areas. The proposed SRPA methods are based on a land-use assessment approach that is underpinned by the current residential land-use schemes legislated by the Department of Transport Planning and Local Infrastructure.¹ The results of applying the proposed model reveal the associated spatial pattern of areas with potential for residential development relative to the public transport and public service locations.     

地理信息系统支持区域土地利用决策的研究

本文以江苏省溧阳县为例,研究地理信息系统技术在区域土地利用多目标规划中的应用,着重探讨地理信息系统支持的区域土地利用决策原理和方法。研究表明,在地理信息系统的支持下,通过单项适宜性评价模型和生产布局决策模型的建立与运行,可以有效地进行研究区合理的土地利用布局和为区域土地管理提供依据。     

Integrating geographical information systems and multiple criteria decision-making methods

Abstract

Many spatial decision-making problems, such as site selection or land use allocation require the decision-maker to consider the impacts of choice-alternatives along multiple dimensions in order to choose the best alternative. The decision-making process, involving policy priorities, trade-offs, and uncertainties, can be aided by Multiple Criteria Decision making (MCDM) methods. This paper presents a framework for integrating geographical information systems (GIS) and MCDM methods. In this framework the MCDM methods are classified and matched with choice heuristics used by the decision-makers in the presence of competing alternatives and multiple evaluation criteria. Two strategies for integrating GIS with MCDM are proposed. The first strategy suggests linking GIS and MCDM techniques using a file exchange mechanism. The second strategy suggests integrating GIS and MCDM functions using a common database. The paper presents the implementation of the first strategy using PC-ARC/INFO, a file exchange module, and four different MCDM computer programs.     

Toward mapping land-use patterns from volunteered geographic information

A large number of applications have been launched to gather geo-located information from the public. This article introduces an approach toward generating land-use patterns from volunteered geographic information (VGI) without applying remote-sensing techniques and/or engaging official data. Hence, collaboratively collected OpenStreetMap (OSM) data sets are employed to map land-use patterns in Vienna, Austria. Initially the spatial pattern of the landscape was delineated and thereafter the most relevant land type was assigned to each land parcel through a hierarchical GIS-based decision tree approach. To evaluate the proposed approach, the results are compared with the Global Monitoring for Environment and Security Urban Atlas (GMESUA) data. The results are compared in two ways: first, the texture of the resulting land-use patterns is analyzed using texture-variability analysis. Second, the attributes assigned to each land segment are evaluated. The achieved land-use map shows kappa indices of 91, 79, and 76% agreement for location in comparison with the GMESUA data set at three levels of classification. Furthermore, the attributes of the two data sets match at 81, 67, and 65%. The results demonstrate that this approach opens a promising avenue to integrate freely available VGI to map land-use patterns for environmental planning purposes.