Ordered weighted averaging with fuzzy quantifiers: GIS-based multicriteria evaluation for land-use suitability analysis

The objective of this paper is to incorporate the concept of fuzzy (linguistic) quantifiers into the GIS-based land suitability analysis via ordered weighted averaging (OWA). OWA is a multicriteria evaluation procedure (or combination operator). The nature of the OWA procedure depends on some parameters, which can be specified by means of fuzzy (linguistic) quantifiers. By changing the parameters, OWA can generate a wide range of decision strategies or scenarios. The quantifier-guided OWA procedure is illustrated using land-use suitability analysis in a region of Mexico.     

基于GIS的OWA方法在城市防灾规划中的应用

作为一个多准则评价的相对较新概念,基于GIS的OWA方法可以通过权重计算产生多种决策策略。分析了OWA方法与布尔决策和权重线性叠加（WLC）等多准则评价方法在决策策略上的区别,介绍了依据次序重要性来计算次序权重和应用层次分析程序（AHP）构建比较矩阵来计算准则权重的方法,并应用于唐山市防灾规划,计算了唐山市地质灾害影响下的土地利用适宜度。在分析计算结果的基础上,为唐山市土地资源的合理开发提出了建议。     

Web-enabled spatial decision analysis using Ordered Weighted Averaging (OWA)

 This paper presents a spatial decision support tool that implements the Ordered Weighted Averaging (OWA) method. OWA is a family of multicriteria evaluation operators characterised by two sets of weights: criterion importance weights and order weights. We propose a highly interactive way of choosing, modifying, and fine-tuning the decision strategy defined by the order weights. This exploratory approach to OWA is supported by a graphical representation of the operator's behaviour in terms of decision risk and tradeoff/dispersion between criteria. Our prototype implementation is based on the CommonGIS software, and thus, Web-enabled and working with vector data. We successfully demonstrate online, exploratory support of spatial decision strategies using a data set of skiing resorts in Wallis, Switzerland. Received: 24 September 2002 / Accepted: 10 January 2003     

Multi-criteria,personalized route planning using quantifier-guided ordered weighted averaging operators

This paper presents a generic model for using different decision strategies in multi-criteria, personalized route planning. Some researchers have considered user preferences in navigation systems. However, these prior studies typically employed a high tradeoff decision strategy, which used a weighted linear aggregation rule, and neglected other decision strategies. The proposed model integrates a pairwise comparison method and quantifier-guided ordered weighted averaging (OWA) aggregation operators to form a personalized route planning method that incorporates different decision strategies. The model can be used to calculate the impedance of each link regarding user preferences in terms of the route criteria, criteria importance and the selected decision strategy. Regarding the decision strategy, the calculated impedance lies between aggregations that use a logical “and” (which requires all the criteria to be satisfied) and a logical “or” (which requires at least one criterion to be satisfied). The calculated impedance also includes taking the average of the criteria scores. The model results in multiple alternative routes, which apply different decision strategies and provide users with the flexibility to select one of them en-route based on the real world situation. The model also defines the robust personalized route under different decision strategies. The influence of different decision strategies on the results are investigated in an illustrative example. This model is implemented in a web-based geographical information system (GIS) for Isfahan in Iran and verified in a tourist routing scenario. The results demonstrated, in real world situations, the validity of the route planning carried out in the model.     

Towards an automated approach to map flooded areas from Sentinel-2 MSI data and soft integration of water spectral features

In this work we propose an approach for mapping flooded areas from Sentinel-2 MSI (Multispectral Instrument) data based on soft fuzzy integration of evidence scores derived from both band combinations (i.e. Spectral Indices - SIs) and components of the Hue, Saturation and Value (HSV) colour transformation. Evidence scores are integrated with Ordered Weighted Averaging (OWA) operators, which model user’s decision attitude varying smoothly between optimistic and pessimistic approach. Output is a map of global evidence degree showing the plausibility of being flooded for each pixel of the input Sentinel-2 (S2) image. Algorithm set up and validation were carried out with data over three sites in Italy where water surfaces are extracted from stable water bodies (lakes and rivers), natural hazard flooding, and irrigated paddy rice fields. Validation showed more than satisfactory accuracy for the OR-like OWA operators (F-score > 0.90) with performance slightly decreased (F-score < 0.75) over heterogeneous conditions (e.g. rice fields). The algorithm was applied with no changes and/or tuning to independent sites from the Copernicus Emergency Management Service (EMS) activations to simulate operational conditions. Over these sites, the proposed approach achieved greater, more consistent and robust mapping accuracy compared to traditional approaches based on the segmentation of single input features. Moreover, OWA operators offer an appealing way of combining and aggregating multiple information in decision making by modelling uncertainty in decision process.     

GIS-based ordered weighted averaging and Dempster–Shafer methods for landslide susceptibility mapping in the Urmia Lake Basin,Iran

In this paper, GIS-based ordered weighted averaging (OWA) is applied to landslide susceptibility mapping (LSM) for the Urmia Lake Basin in northwest Iran. Nine landslide causal factors were used, whereby the respective parameters were extracted from an associated spatial database. These factors were evaluated, and then the respective factor weight and class weight were assigned to each of the associated factors using analytic hierarchy process (AHP). A landslide susceptibility map was produced based on OWA multicriteria decision analysis. In order to validate the result, the outcome of the OWA method was qualitatively evaluated based on an existing inventory of known landslides. Correspondingly, an uncertainty analysis was carried out using the Dempster–Shafer theory. Based on the results, very strong support was determined for the high susceptibility category of the landslide susceptibility map, while strong support was received for the areas with moderate susceptibility. In this paper, we discuss in which respect these results are useful for an improved understanding of the effectiveness of OWA in LSM, and how the landslide prediction map can be used for spatial planning tasks and for the mitigation of future hazards in the study area.     

On the Use of Weighted Linear Combination Method in GIS: Common and Best Practice Approaches

The weighted linear combination (WLC) technique is a decision rule for deriving composite maps using GIS. It is one of the most often used decision models in GIS. The method, however, is frequently applied without full understanding of the assumptions underling this approach. In many case studies, the WLC model has been applied incorrectly and with dubious results because analysts (decision makers) have ignored or been unaware of the assumptions. This paper provides a critical overview of the current practice with respect to GIS/WLC and suggests the best practice approach.     

Locally weighted linear combination in a vector geographic information system

Weighted linear combination is a multi-criteria decision analysis technique that can be used by decision-makers to select an optimal location from a collection of alternative locations. Its local form takes into account the range of attribute values within a user-defined neighbourhood in accordance with the range-sensitivity principle. This research explores locally weighted linear combination in a vector-based geographic information system. A custom application in ArcGIS 10 allows the user to select a neighbourhood definition from a standard set including contiguity, distance, and k-nearest neighbours, for which local weights are generated. A case study on vulnerability to heat-related illness in Toronto is used to illustrate the technique. The impact of local weighting on the heat vulnerability index is examined using visual analysis of the spatial patterns of heat vulnerability under the global and local approaches, as well as the sensitivity of the local approach to the selected neighbourhood definition. A trade-off analysis of the local weights is also presented. The combination of socio-demographic and environmental determinants in a locally weighted index results in patterns of heat vulnerability that could support targeted hot weather response at a micro-geographic level within urban neighbourhoods.     

Application of fuzzy combination operators to flood vulnerability assessments in Seoul,Korea

The goal of this study was to apply, verify and compare fuzzy models with various fuzzy combination operators to analyze the vulnerability to flooding in Seoul, Korea, and to create flood vulnerability maps. We employed the IPCC concept of vulnerability, which comprises exposure to climate, sensitivity and the adaptive capacity, to identify factors that influence flooding. Eleven factors were compiled in a spatial database using geographical information system. The relative weight of each factor was converted into a fuzzy membership value, which was integrated to obtain a flood vulnerability index using five fuzzy combination operators (fuzzy AND, fuzzy OR, fuzzy algebraic sum, fuzzy algebraic product and fuzzy gamma). Overall, the fuzzy models were quite effective tools for flood vulnerability assessment. Of the five fuzzy combination operators, the fuzzy AND operator obtained the highest prediction accuracy of 88.68%. This study achieved better flood vulnerability assessments by employing and comparing fuzzy combination operators.     

Map-Based Exploratory Evaluation of Non-Medical Determinants of Population Health

Multi‐criteria evaluation (MCE) and decision‐making are increasingly combined with interactive tools to assist users with visual thinking and exploring decision strategies. The interactive control of criterion combination rules and the simultaneous observation of geographic space and criterion space provide a means of investigating the sensitivity of the decision outcome to the decision‐maker's preferences. The Analytic Hierarchy Process (AHP) is an MCE method that has been successfully implemented in management processes including those addressed by Geographic Information Systems. In this paper, we present a map‐based, interactive AHP implementation, which provides a link between a well‐understood decision support method and exploratory geographic visualization. Using a case study with public health data for the Province of Ontario, Canada, we demonstrate that exploratory map use increases the effectiveness of the AHP‐based evaluation of population health.     

A multi‐criteria decision‐making approach for geometric matching of areal objects

We propose a method for geometric areal object matching based on multi‐criteria decision making. To enable this method, we focused on determining the matched areal object pairs that have all relations, one‐to‐one relationships to many‐to‐many relationships, in different spatial data sets by fusing geometric criteria without user invention. First, we identified candidate corresponding areal object pairs with a graph‐based approach in training data. Second, three matching criteria (areal hausdorff distance, intersection ratio, and turning function distance) were calculated in candidate corresponding pairs and these criteria were normalized. Third, the shape similarity was calculated by weighted linear combination using the normalized matching criteria (similarities) with the criteria importance through intercriteria correlation method. Fourth, a threshold (0.738) of the shape similarity estimated in the plot of precision versus recall versus all possible thresholds of training data was applied, and the matched pairs were determined and identified. Finally, we visually validated the detection of similar areal feature pairs and conducted statistical evaluation using precision, recall, and F‐measure values from a confusion matrix. Their values were 0.905, 0.848, and 0.876, respectively. These results validate that the proposed classifier, which detects 87.6% of matched areal pairs, is highly accurate.     

Evaluating the compatibility of multi-functional and intensive urban land uses

This research is aimed at developing a model for assessing land use compatibility in densely built-up urban areas. In this process, a new model was developed through the combination of a suite of existing methods and tools: geographical information system, Delphi methods and spatial decision support tools: namely multi-criteria evaluation analysis, analytical hierarchy process and ordered weighted average method. The developed model has the potential to calculate land use compatibility in both horizontal and vertical directions. Furthermore, the compatibility between the use of each floor in a building and its neighboring land uses can be evaluated. The method was tested in a built-up urban area located in Tehran, the capital city of Iran. The results show that the model is robust in clarifying different levels of physical compatibility between neighboring land uses. This paper describes the various steps and processes of developing the proposed land use compatibility evaluation model (CEM).     

The lay of the language: surveying the cartographic characteristics of language maps

Although visible in research in the 1980s and 1990s, works concerning language-mapping issues are recently rather absent. This is an unfortunate oversight given current GIS capability and its potential to tackle visualization issues that were previously simply acknowledged and accepted. Given that there are no established guidelines for language map construction, this work aims to renew attention to language mapping, beginning with a survey documenting the characteristics of published language maps. The survey components address the problematic aspects described in the literature, such as boundary representation and depicting linguistic diversity, and reveal their usage and frequency. The noted map characteristics include, but are not limited to: publication type, publication year, coverage area, language data or variable used, and symbology details. For consistent classification, we use a language-map symbology classification scheme found in previous research. In general, chorochromatic maps using polygonal map units dominate our survey. We also find further evidence supporting the problems outlined in language mapping literature with the widespread use of solid-line boundaries and depiction of only one language or feature per place. However, we also note some unique strategies used for handling uncertainty and linguistic plurality. Observations of tactics not captured by the existing 20-year-old typology lead us to create an updated language map symbology typology consistent with the trends observed in our survey. Overall, we document language mapping strategies in practice and provide direction for future research by highlighting the pros and cons of current cartographic approaches for depicting language.     

Evaluating Alternative Line Simplification Strategies for Multiple Representations of Cartographic Lines

Two basic strategies have been identified for handling multiple representations of line features in digital databases. Either a finite number of scale-dependent representations of cartographic lines can be explicitly stored, or a scale-independent database is generated from which subsequent scale representations can be extracted as needed. These two strategies parallel differences in hierarchical and non-hierarchical line simplification operators. Non-hierarchical line-simplification can produce the most geometrically accurate simplification at any scale, while hierarchical operators are often associated with scale-independent databases. In this research, hierarchical and non-hierarchical line simplification operators are evaluated by comparing both the points retained by these different algorithms and the overall quality of the graphic portrayal for sample lines of different complexity and at different scales. Visual inspection of the results did not reveal any discernable difference at any scale for any line. Subsequent numerical analyses shows some differences but overall little geometric quality is lost by using a hierarchical operator as opposed to a non-hierarchical one and given the greater flexibility of scale representations that is possible, hierarchical methods appear to be more satisfactory.     

基于SVG的地质灾害在线应急态势符号设计与实现

针对地质灾害的应急响应及处理技术系统成为近几年地质灾害领域研究的热点和重点,然而在已有的研究中,应急决策系统多为桌面应用程序,难以满足应急部署的实时性和灵活性,同时现有的地质灾害应急技术中对地质灾害应急态势标绘技术的研究较少,而应急部署又十分需要态势符号的支撑。为此,本文在分析多种在线符号绘制语言特点的基础上,提出了一种基于SVG的地质灾害在线应急态势标绘方法,对地质灾害应急需要使用的态势标绘符号进行了算法设计与系统实现。现场应用案例表明:该方法可以实现地质灾害应急态势符号的在线交互式标绘,为决策者快速、实时部署应急方案提供有效支撑。     

基于最优极化相干系数的倾斜建筑物解译研究

基于Freeman_Durden分解的全极化SAR影像分类方法能够较好地保持地物极化散射特性,但在分类的过程中,不能改变初始散射机制,导致分解结果对分类精度影响很大。在Freeman_Durden分解中,排列方向相对雷达飞行方向不平行的建筑物（简称为倾斜建筑物）常被分为体散射类型,使得该类建筑物往往被误分为植被。本文通过分析建筑物在SAR影像中的后向散射特性,利用建筑物具有较高相干性的特点,引入最优极化相干系数,在目标分解的基础上通过阈值分割将两者区分开来,进而提高反射非对称性人工目标的分类效果。通过使用E-SAR系统在德国DLR附近Oberpfaffenhofen地区获取的L波段PolInSAR影像和国内X-SAR系统在海南陵水地区获取的X波段PolInSAR影像进行实验,证明本文提出的方法能够有效地将与雷达飞行方向不平行的建筑物与森林区分开。     

基于MODIS影像多特征的CART决策树分类

以山东省为研究区域,利用2009年9月MODIS的8 d合成波段反射率产品MOD09,选择特征变量植被指数(NDVI、EVI)、NDWI、NDMI、NDSI及辅助信息DEM,通过选取其中的影像特征组合来确定分类方案,构建各波段组合的CART决策树,对MODIS影像进行分类,得到CART决策树的最优波段组合。结果表明,特征变量DEM、NDVI、EVI对分类结果贡献较大;将CART决策树的分类结果与其相对应的最大似然分类结果进行比较可知,基于影像多特征的CART决策树分类方法能明显提高分类精度。     

利用特征选择自适应决策树的层次SAR图像分类

提出了一种新的基于特征选择自适应决策树的层次分类算法,用于合成孔径雷达（synthetic apertureradar,SAR）图像的分类。采用Joint Boosting算法选择出最适用于各类的特征组合,并自适应地搜索构造出一个由两类分类器构成的层次分类器,利用特征选择结果和自适应决策树进行了SAR图像的学习和推理,实现了自动分类,在国内首批极化干涉SAR数据上的实验证明了本算法的有效性。     

基于SuperMap的日本铁道货物列车运输状态分析

铁道运输是一个具有独特技术体系的运输网络.本文研究针对铁道运输网,应用GIS技术,整合铁道线路、列车运行图、车站列车作业及装卸车计划等既有数据,基于SuperMap GIS平台对构建铁道货物运输地理信息系统(Rail Freight Geographic Information System,RF-GIS)进行了探讨,在此基础上,以日本货物铁道为例,对运行在不同行车线路、不同区间的各种货物列车进行了统计分析,并把其运输状态的分析结果显示在数字地图上,可在视觉上掌握货物列车的运输状态.本文为运输及物流管理者提供了直观的判断决策信息,可作为改进运输组织及提高铁道运输效率的基础依据.     

多特征组合与自动加权K-Means聚类算法的影像分类技术研究

为了提高遥感影像地物分类精度,提出了一种基于多特征组合与自动加权K-Means聚类算法的影像分类方法。首先提取影像的SIFT,GIST,颜色,Census和Gabor等多种类型特征,然后通过实验分析确定最佳特征组合。针对一般K-Means算法没有考虑各个特征值权重的问题,提出利用自动加权K-Means算法计算不同特征分量的权值,分别对SIFT,GIST和Gabor特征构建了基于权重的影像特征词汇表;然后利用稀疏编码算法进行影像编码;最后使用SVM算法完成影像分类。通过实验表明提出的方法能有效提高遥感影像分类准确性,并且具有较好的稳定性和鲁棒性。