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1.
城市居住用地防灾适宜度评价的OWA方法 总被引：1，自引：1，他引：0
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。 相似文献
2.
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。 相似文献
3.
一种结合GIS的双重目标多准则决策方法及其应用 总被引：1，自引：0，他引：1
钮心毅 《地理与地理信息科学》2008,24(2):91-95
在土地适宜性评价中,现有结合GIS的多准则决策方法难以适用于存在多个冲突决策目标的问题。该文对已有方法进行改进,提出一种适用于相互冲突双重目标的多准则决策方法。该方法应用矢量数据模型,逐个进行单一目标的多准则决策,根据决策结果建立决策平面;根据两个目标间的权重划分决策平面,采用图解算法实现双重目标的决策。与现有的线性整数规划、遗传算法等相比,该方法简单易用,适用于城市规划中具有大量候选项的土地适宜性评价和土地布局研究。 相似文献
4.
Bakhtiar Feizizadeh Thomas Blaschke 《International journal of geographical information science》2014,28(3):610-638
GIS-based multicriteria decision analysis (MCDA) methods are increasingly being used in landslide susceptibility mapping. However, the uncertainties that are associated with MCDA techniques may significantly impact the results. This may sometimes lead to inaccurate outcomes and undesirable consequences. This article introduces a new GIS-based MCDA approach. We illustrate the consequences of applying different MCDA methods within a decision-making process through uncertainty analysis. Three GIS-MCDA methods in conjunction with Monte Carlo simulation (MCS) and Dempster–Shafer theory are analyzed for landslide susceptibility mapping (LSM) in the Urmia lake basin in Iran, which is highly susceptible to landslide hazards. The methodology comprises three stages. First, the LSM criteria are ranked and a sensitivity analysis is implemented to simulate error propagation based on the MCS. The resulting weights are expressed through probability density functions. Accordingly, within the second stage, three MCDA methods, namely analytical hierarchy process (AHP), weighted linear combination (WLC) and ordered weighted average (OWA), are used to produce the landslide susceptibility maps. In the third stage, accuracy assessments are carried out and the uncertainties of the different results are measured. We compare the accuracies of the three MCDA methods based on (1) the Dempster–Shafer theory and (2) a validation of the results using an inventory of known landslides and their respective coverage based on object-based image analysis of IRS-ID satellite images. The results of this study reveal that through the integration of GIS and MCDA models, it is possible to identify strategies for choosing an appropriate method for LSM. Furthermore, our findings indicate that the integration of MCDA and MCS can significantly improve the accuracy of the results. In LSM, the AHP method performed best, while the OWA reveals better performance in the reliability assessment. The WLC operation yielded poor results. 相似文献
5.
Mariana Madruga de Brito Adrian Almoradie Mariele Evers 《International journal of geographical information science》2019,33(9):1788-1806
This study presents a methodology for conducting sensitivity and uncertainty analysis of a GIS-based multi-criteria model used to assess flood vulnerability in a case study in Brazil. The paper explores the robustness of model outcomes against slight changes in criteria weights. One criterion was varied at-a-time, while others were fixed to their baseline values. An algorithm was developed using Python and a geospatial data abstraction library to automate the variation of weights, implement the ANP (analytic network process) tool, reclassify the raster results, compute the class switches, and generate an uncertainty surface. Results helped to identify highly vulnerable areas that are burdened by high uncertainty and to investigate which criteria contribute to this uncertainty. Overall, the criteria ‘houses with improper building material’ and ‘evacuation drills and training’ are the most sensitive ones, thus, requiring more accurate measurements. The sensitivity of these criteria is explained by their weights in the base run, their spatial distribution, and the spatial resolution. These findings can support decision makers to characterize, report, and mitigate uncertainty in vulnerability assessment. The case study results demonstrate that the developed approach is simple, flexible, transparent, and may be applied to other complex spatial problems. 相似文献
6.
Jacek Malczewski 《International journal of geographical information science》2013,27(8):955-971
Abstract The multiple criteria group decision-making problem involves a set of feasible alternatives that are evaluated on the basis of multiple, conflicting and noncommensurate criteria by a group of individuals. This paper is concerned with developing a GIS-based approach to group decision-making under multiple criteria. The approach integrates, within a raster GIS environment, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Borda's choice rule. TOPSIS orders the feasible alternatives according to their closeness to the ideal solution. It is used to derive the individual preference orderings. Borda's method combines the individual preferences into a group preference or consensus/compromise ranking. The approach is implemented within the IDRISI GIS and illustrated on a hypothetical decision situation. 相似文献
7.
Piotr Jankowski 《International journal of geographical information science》2013,27(3):251-273
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. 相似文献
8.
STEPHEN J. CARVER 《International journal of geographical information science》2013,27(3):321-339
Abstract Geographical information systems (GIS) provide the decision-maker with a powerful set of tools for the manipulation and analysis of spatial information. The functionality of GIS is, however, limited to certain deterministic analyses in key application areas such as spatial search. The integration of multi-criteria evaluation (MCE) techniques with GIS is forwarded as providing the user with the means to evaluate various alternatives on the basis of multiple and conflicting criteria and objectives. An example application based on the search for suitable sites for the disposal of radioactive waste in the UK using the Arc/Info GIS is included. The potential use of a combined GIS-MCE approach in the development of spatial decision support systems is considered. 相似文献
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10.
L. Bingham A. Escalona D. Karssenberg 《International journal of geographical information science》2016,30(8):1552-1578
This article applies error propagation in a Monte Carlo simulation for a spatial-based fuzzy logic multi-criteria evaluation (MCE) in order to investigate the output uncertainty created by the input data sets and model structure. Six scenarios for quantifying uncertainty are reviewed. Three scenarios are progressively more complex in defining observational data (attribute uncertainty); while three other scenarios include uncertainty in observational data (position of boundaries between map units), weighting of evidence (fuzzy membership assignment), and evaluating changes in the MCE model (fuzzy logic operators). A case study of petroleum exploration in northern South America is used. Despite the resources and time required, the best estimate of input uncertainty is that based on expert-defined values. Uncertainties for fuzzy membership assignment and boundary transition zones do not affect the results as much as the attribute assignment uncertainty. The MCE fuzzy logic operator uncertainty affects the results the most. Confidence levels of 95% and 60% are evaluated with threshold values of 0.7 and 0.5 and show that accepting more uncertainty in the results increases the total area available for decision-making. Threshold values and confidence levels should be predetermined, although a series of combinations may yield the best decision-making support. 相似文献
11.
Michele Crosetto Stefano Tarantola 《International journal of geographical information science》2013,27(5):415-437
A novel procedure to analyse the uncertainty associated to the output of GIS-based models is presented. The procedure can handle models of any degree of complexity that accept any kind of input data. Two important aspects of spatial modelling are addressed: the propagation of uncertainty from model inputs and model parameters up to the model output (uncertainty analysis); and the assessment of the relative importance of the sources of uncertainty in the output uncertainty (sensitivity analysis). Two main applications are proposed. The procedure allows implementation of a GIS-based model whose output can reliably support the decision process with an optimized allocation of resources for spatial data acquisition. This is possible in low cost strategy, based on numerical simulations on a small prototype of the GIS-based model. Furthermore, the procedure provides an effective model building tool to choose, from a group of alternative models, the best one in terms of cost-benefit analysis. A comprehensive case study is described. It concerns the implementation of a new GIS-based hydrologic model, whose goal is providing near real-time flood forecasting. 相似文献
12.
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。 相似文献
13.
基于OWA-GIS的巢湖流域洪涝灾害风险评价 总被引：2，自引：1，他引：1
随着全球气候变化和城市化进程加快,洪涝灾害的灾情日益严重。在流域风险识别的基础上,从致灾因子、孕灾环境、承灾体和防灾减灾能力4个方面选取评价指标,建立评价指标体系。运用层次分析法确定指标的准则权重,基于有序加权平均法（OWA）计算指标的次序权重;构建OWA-GIS洪涝灾害风险评价模型,对巢湖流域洪涝灾害风险进行评价。研究表明：巢湖流域的东南部洪涝灾害风险较大,特别是庐江、无为、居巢区、和县等地。低风险区主要分布在巢湖流域的西南部、西北部和北部,舒城、肥西、肥东县风险低。随着决策系数的增大,决策者的态度由乐观到悲观,得到的风险值也越来越大。基于OWA-GIS的洪涝灾害风险评价是一种情景分析,评价不同决策态度下的风险状况,可拟定更多的复合情景,预测未来某种自然及经济条件下和不同决策态度下的风险,为区域制定规划和灾害风险管理提供科学依据。 相似文献
14.
FULONG WU 《International journal of geographical information science》2013,27(1):63-82
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
15.
Cathlin M. Lord Kylie P. Wirebach Jennifer Tompkins Casey Bradshaw-Wilson 《International journal of geographical information science》2020,34(8):1628-1647
ABSTRACT European bison (Bison bonasus), a flagship species for the burgeoning re-wildling movement, faced challenges common to large mammals globally. These include deforestation, land use conversion, poaching, and a lack of genetic diversity. Despite these limitations, organizations such as Rewilding Europe seek to reintroduce the species to its historic range. This study focused on finding suitable reintroduction locations for a population of at least 120 individuals. Through GIS-based multi-criteria decision-making using weighted linear combination and analytical hierarchy process, a model based on known bison habitat preferences, human-centered habitat constraints, and surface geography was used to identify regions large enough to accommodate a new herd. The study area included central-eastern Europe Union countries, specifically Germany, Poland, Lithuania, and Latvia. The model identified several highly suitable regions large enough to support a new herd, with the most optimal located in Poland. Highly suitable areas represented 2.7% of the study region. Relative isolation of suitable regions reinforced the challenges of promoting gene flow between reintroduced European bison herds. This model can be replicated in other conservation planning contexts, including reintroduction of large herbivores considering anthropogenic, ecological, and physical conditions. 相似文献
16.
基于神经网络的单元自动机CA及真实和优化的城市模拟 总被引：78，自引：8，他引：78
提出了一种基于神经网络的单元自动机（CA）。CA已被越来越多地应用在城市及其它地理现象的模拟中。CA模拟所碰到的最大问题是如何确定模型的结构和参数。模拟真实的城市涉及到使用许多空间变量和参数。当模型较复杂时，很难确定模型的参数值。本模型的结构较简单，模型的参数能通过对神经网络的训练来自动获取。分析表明，所提出的方法能获得更高的模拟精度，并能大大缩短寻找参数所需要的时间。通过筛选训练数据，本模型还可以进行优化的城市模拟，为城市规划提供参考依据。 相似文献
17.
Emily C. Hazell Claus Rinner 《International journal of geographical information science》2020,34(8):1648-1681
ABSTRACT Modelling changes in biodiversity have become a necessary component of smart urban planning practices. However, concepts such as biodiversity are often evaluated using area-based composite indices, the results of which are heavily reliant on specific parameters chosen. This paper explores the design and implementation of a butterfly biodiversity index by comparing two widely accepted modelling techniques: principal component analysis and spatial multi-criteria decision analysis (MCDA). A high degree of scale dependency has been demonstrated in previous studies exploring the use of area-based composite measures. To evaluate the impact of scale, each model was assessed at two different spatial resolutions. The outcomes were analyzed, mapped and compared using ordinary least squares, geographically weighted regression and global Moran’s I to evaluate relative biodiversity patterns across the City of Toronto, Canada. Findings indicate that the impact of spatial scale was significant, whereby the coarser resolution models were found to be more highly correlated with biodiversity, compared to the finer resolution models. The results of this study contribute to a growing body of literature that explores key conceptual questions regarding the robustness of GIS-based MCDA, the impact of scale in urban ecology studies, and the use of composite indices to manage spatial ecological data. 相似文献
18.
Natural and imposed injustices: the challenges in implementing 'fair' flood risk management policy in England 总被引：1，自引：0，他引：1
This paper examines the challenges facing English flood risk management (FRM) policy and practice when considering fair decision-making processes and outcomes at a range of spatial scales. It is recognised that flooding is not fair per se : the inherent natural spatial inequality of flood frequency and extent, plus the legacy of differential system interventions, being the cause. But, drawing on the three social justice models – procedural equality, Rawls' maximin rule and maximum utility – the authors examine the fairness principles currently employed in FRM decision-making. This is achieved, firstly, in relation to the distribution of taxpayer's money for FRM at the national, regional and local levels and, secondly, for non-structural strategies – most notably those of insurance, flood warnings and awareness raising, land use control, home owner adaptation and emergency management. A case study of the Lower Thames catchment illustrates the challenges facing decision-makers in 'real life': how those strategies which appear to be most technically and economically effective fall far short of being fair from either a vulnerability or equality perspective. The paper concludes that if we are to manage flood risk somewhat more fairly then a move in the direction of government funding of nationally consistent non-structural strategies, in conjunction with lower investment decision thresholds for other local-level FRM options, appears to offer a greater contribution to equality and vulnerability-based social justice principles than the status quo. 相似文献
19.
Natural Resources Research - In this work, a quantifier-guided ordered weighted averaging (OWA) method was employed for mineral potential mapping (MPM) in Nowchun Cu–Mo prospect, SE Iran. The... 相似文献
20.
S. Chakhar V. Mousseau 《International journal of geographical information science》2013,27(11-12):1159-1196
Multicriteria analysis is a set of mathematical tools and methods allowing the comparison of different alternatives according to many criteria, often conflicting, to guide the decision maker towards a judicious choice. Multicriteria methods are used in spatial context to evaluate and compare spatial decision alternatives, often modeled through constraint‐based suitability analysis and represented by point, line, and polygon features or their combination, and evaluated on several space‐related criteria, to select a restricted subset for implementation. Outranking methods, a family of multicriteria methods, may be useful in spatial decision problems, especially when ordinal evaluation criteria are implied. However, it is recognized that these methods, except those devoted to multicriteria classification problems, are subject to computational limitations with respect to the number of alternatives. This paper proposes a framework to facilitate the incorporation and use of outranking methods in geographical information systems (GIS). The framework is composed of two phases. The first phase allows producing a planar subdivision of the study area obtained by combining a set of criteria maps; each represents a particular vision of the decision problem. The result is a set of non‐overlapping spatial units. The second phase allows constructing decision alternatives by combining the spatial units. Point, line and polygon feature‐based decision alternatives are then constructed as an individual, a grouping of linearly adjacent or a grouping of contiguous spatial units. This permits us to reduce considerably the number of alternatives, enabling the use of outranking methods. The framework is illustrated through the development of a prototype and through a step‐by‐step application to a corridor identification problem. This paper includes also a discussion of some conceptual and technical issues related to the framework. 相似文献