Integrating GIS and spatial data analysis: problems and possibilities

Abstract

This article is an agreed summary of a workshop held in Sheffield between 18-20 March 1991. The focus here is on three of the themes of the workshop: the mutual benefits of closer links between geographical information systems (GIS) and the methods of spatial data analysis (SDA); the specific areas of SDA that should be linked with GIS; how the linkage should be made in practice. Directions for future research are also reviewed. The emphasis throughout is on statistical SDA and principally from the perspective of human rather than physical geography.     

Detecting outliers in irregularly distributed spatial data sets by locally adaptive and robust statistical analysis and GIS

In this paper, we propose a new method for detecting outliers in an irregularly distributed spatial data set. Our method has two desirable properties. First, it is functionally effective due to the introduction of sensitive outlier indices and locally adaptive and robust statistical criteria. Second, it is computationally efficient because of the use of super-block based spatial data sorting and searching scheme. Our method has been implemented using the C programming language and integrated with the Arc/Info GIS system. The integration leads to a powerful exploratory data analysis tool for checking and analysing anomalous values in a GIS environment. Local outliers can be automatically labeled with our method, subject to some user-defined parameters. Outliers represent anomalous or suspicious values in a statistical sense, which may not necessarily be erroneous values. Instead of being simply discarded, statistical outliers should be investigated further using prior qualitative knowledge or in association with other GIS data layers.     

GIS and spatial analysis in the media

It is not uncommon to see maps and more advanced statistical or spatial analysis reported in the media. Geographical information systems (GIS) have no doubt facilitated access to and analysis of spatial information. This article is the outgrowth of contact by the Boston Globe and subsequent published articles examining structure fires and the location of fire stations in Massachusetts. The questions asked by the Boston Globe are important geographical ones regarding location specific urban/rural service provision issues, and to answer these questions requires the use of spatial analysis. This article focuses on the use of methods for answering the questions raised in the context of applying academic research, an issue that continues to be a challenge.     

Providing spatial statistical data analysis functionality for the GIS user: the SAGE project

Geographic representation has become more complex through time as researchers have added new concepts, leading to apparently endless proliferation and creating a need for simplification. We show that many of these concepts can be derived from a single foundation that we term the atomic form of geographic information. The familiar concepts of continuous fields and discrete objects can be derived under suitable rules applied to the properties and values of the atomic form. Fields and objects are further integrated through the concept of phase space, and in the form of field objects. A second atomic concept is introduced, termed the geo‐dipole, and shown to provide a foundation for object fields, metamaps, and the association classes of object‐oriented data modelling. Geographic dynamics are synthesized in a three‐dimensional space defined by static or dynamic object shape, the possibility of movement, and the possibility of dynamic internal structure. The atomic form also provides a tentative argument that discrete objects and continuous fields are the only possible bases for geographic representation.     

Testing spatial heterogeneity in geographically weighted principal components analysis

We propose a method to evaluate the existence of spatial variability in the covariance structure in a geographically weighted principal components analysis (GWPCA). The method, that is extensive to locally weighted principal components analysis, is based on performing a statistical hypothesis test using the eigenvectors of the PCA scores covariance matrix. The application of the method to simulated data shows that it has a greater statistical power than the current statistical test that uses the eigenvalues of the raw data covariance matrix. Finally, the method was applied to a real problem whose objective is to find spatial distribution patterns in a set of soil pollutants. The results show the utility of GWPCA versus PCA.     

空间数据统计分析的思想起源与应用演化

系统总结了空间数据统计分析的发展历程,并分为五个时期：① 早期孕育（计量革命之前）,其重要思想是19世纪初德国的区位论;② 计量革命（1950-1960年代）,主要是经典统计学的应用和理论探索;③ 空间统计学（1970-1980年代）,重点是空间点数据、面数据和空间连续性数据的分析;④ 成熟与扩散（1990-2000年代）,空间数据统计分析发展成熟并快速向其他领域扩散;⑤ 时空大数据（2010年以后）。换句话说,计量革命开始后的空间数据统计分析大约每20年有重要的新技术或方法出现,到现在已经具有成熟、系统化的方法和显著的社会效益。而在当前的时空大数据时期,其发展需要计算机科学家、统计学家和地理学家等不同学科领域人员的共同努力。     

Integrating space,spatial tools,and spatial analysis into the human dimensions of parks and outdoor recreation

The analysis of space and the use of geographic information systems (GIS) have long been important to natural resource applications. More recently, social scientists have been exploring ways to integrate spatial concepts with social science data related to natural resources for theoretical, practical, and methodological reasons. This trend is particularly evident with research in park and protected area (PPA) management and outdoor recreation. The purpose of this paper is to present an updated review of how space has been incorporated into PPA research, integrate concepts and methods, identify gaps, and propose future directions for research. Overall, this review suggests that the incorporation of spatially-related social science data is advancing the field PPA research in an effective and viable way.     

Integrating GIS into the Undergraduate Learning Environment

Abstract

Despite the promise of GIS, substantial barriers have prevented its widespread use in geographic education. Among the key factors are technical impediments stemming from software complexity, pedagogic issues related to the lack of experienced faculty and the shortage of curriculum materials, and systemic issues associated with faculty motivation. This case study describes strategies that were employed for addressing each of these barriers in a large enrollment, multisection world geography course. Successful implementation of those strategies has enabled large numbers of students in classes taught by instructors with no formal GIS experience to spend a substantial amount of time learning geography with the help of simple, easy-to-use GIS software applications.     

基于空间结构分析的地图概括研究

在地理信息系统(GIS)中,点、线、面等基本图形要素不仅直接表示了各种地理现象,而且隐含地表示了地理现象的空间结构,例如斑块结构、棋盘结构。在许多GIS应用中,需要对图形数据进行概括处理,以派生出较小比例尺的数据集或地图。由于地理现象的空间结构是地理规律和地理景观格局的重要反映,因此需要识别数据库中隐含的空间结构,并在概括后的数据库中有意识地反映这种空间结构。     

A unified approach for location-allocation analysis: integrating GIS,distributed computing and spatial optimization

Location-allocation modeling is an important area of research in spatial optimization and GIScience. A large number of analytical models for location-allocation analysis have been developed in the past 50 years to meet the requirements of different planning and spatial-analytic applications, ranging from the location of emergency response units (EMS) to warehouses and transportation hubs. Despite their great number, many location-allocation models are intrinsically linked to one another. A well-known example is the theoretical link between the classic p-median problem and coverage location problems. Recently, Lei and Church showed that a large number of classic and new location models can be posed as special case problems of a new modeling construct called the vector assignment ordered median problem (VAOMP). Lei and Church also reported extremely high computational complexity in optimally solving the best integer linear programming (ILP) formulation developed for the VAOMP even for medium-sized problems in certain cases.

In this article, we develop an efficient unified solver for location-allocation analysis based on the VAOMP model without using ILP solvers. Our aim is to develop a fast heuristic algorithm based on the Tabu Search (TS) meta-heuristic, and message passing interface (MPI) suitable for obtaining optimal or near-optimal solutions for the VAOMP in a real-time environment. The unified approach is particularly interesting from the perspective of GIScience and spatial decision support systems (DSS) as it makes it possible to solve a wide variety of location models in a unified manner in a GIS environment. Computational results show that the TS method can often obtain in seconds, solutions that are better than those obtained using the ILP-based approach in hours or a day.     

Integrating attribute and space characteristics in choropleth display and spatial data mining

This paper develops an interactive approach for exploratory spatial data analysis. Measures of attribute similarity and spatial proximity are combined in a clustering model to support the identification of patterns in spatial information. Relationships between the developed clustering approach, spatial data mining and choropleth display are discussed. Analysis of property crime rates in Brisbane, Australia is presented. A surprising finding in this research is that there are substantial inconsistencies in standard choropleth display options found in two widely used commercial geographical information systems, both in terms of definition and performance. The comparative results demonstrate the usefulness and appeal of the developed approach in a geographical information system environment for exploratory spatial data analysis.     

基于GIS场模型的城市餐饮服务热点探测及空间格局分析

餐饮服务是城市生活的重要组成部分,提取城市餐饮服务热点并识别其空间分布模式,对于理解城市形态结构具有重要意义。针对过去基于POI进行城市形态特征定量分析的不足,利用GIS场模型对城市特征要素的空间分布模式进行识别,并采用地学信息图谱对其模式进行可视化和分析。以济南市主城区4.71万个餐饮服务POI作为主要数据源,首先基于密度场热点探测模型提取餐饮服务热点并按照密度值进行等级划分;然后采用广义对称结构图谱和数字场层次结构图谱表达餐饮服务热点的空间分布结构特征和规模等级结构特征,并构建其分布模式图谱;最后对结果展开讨论。研究表明：① 数字场热点探测模型能够有效地从POI中识别出不同等级的热点。② 广义对称结构图谱和基于GIS场模型的层级结构图谱能够分别从纵横两个方面分析和表达餐饮热点的空间分布结构和层次等级结构特征。综上所述,本研究为基于POI的城市特征要素提取和城市形态研究提供了一种有效的定量分析思路,其方法也可以推广至其他城市特征要素的提取、分析和表达当中。     

Infometric and statistical diagnostics to provide artificially-intelligent support for spatial analysis: the example of interpolation

The wider uptake of GIS tools by many application areas outside GIScience means that many newer users of GIS will have high-level knowledge of the wider task, and low-level knowledge of specific system commands as given in reference manuals. However, these newer users may not have the intermediate knowledge that experts in GI science have gained from working with GI systems over several years. Such intermediate knowledge includes an understanding of the assumptions implied by the use of certain functions, and an appreciation of how to combine functions appropriately to create a workflow that suits both the data and overall goals of the geographical analysis task.

Focusing on the common but non-trivial task of interpolating spatial data, this paper considers how to help users gain the necessary knowledge to complete their task and minimise the possibility of methodological error. We observe that both infometric (or cognitive) knowledge and statistical knowledge are usually required to find a solution that jointly and efficiently meets the requirements of a particular user and data set. Using the class of interpolation methods as an example, we outline an approach that combines knowledge from multiple sources and argue the case for designing a prototype ‘intelligent’ module that can sit between a user and a given GIS.

The knowledge needed to assist with the task of interpolation is constructed as a network of rules, structured as a binary decision tree, that assist the user in selecting an appropriate method according to task-related knowledge (or ‘purpose’) and the characteristics of the data sets. The decision tree triggers exploratory diagnostics that are run on the data sets when a rule requires to be evaluated. Following evaluation of the rules, the user is advised which interpolation method might be and should not be considered for the data set. Any parameters required to interpolate the particular data set (e.g. a distance decay parameter for Inverse Distance Weighting) are also supplied through subsequent optimisation and model selection routines. The rationale of the decision process may be examined, so the ‘intelligent interpolator’ also acts as a learning tool.     

Use of GIS for a spatial and temporal analysis of Kenyan wildlife with generalised linear modelling

This paper applies generalised linear statistical techniques in a GIS to analyse wildlife data from a Kenyan wildlife reserve and its surrounding areas. Attention focuses on the spatial distribution of elephant during nine successive surveys, analysing their temporal and spatial relationship to 12 environmental covariates. A principal component analysis identifies five major determining factors, thereby reducing dimensionality in the data, while a simple spatial analysis procedure, suitable for wildlife data obtained from airborne surveys, quantfies clustering for different animal species. The number of explanatory variables appearing in abundance models is found to be subject to large variations during successive surveys with a minimum and maximum of four and eight variables, respectively. Species from highly clustered populations are found to have over 20 times more observations within short distances compared to the rest. The study concludes that a combination of generalised linear modelling and GIS gives deeper insight into the dynamics of wildlife species in and around well-defined nature reserves.     

Integrating algebraic multigrid method in spatial aggregation of massive trajectory data

The advanced technologies in location-based services and telecom have yield large volumes of trajectory data. Understanding these data effectively requires intuitive yet accurate visual analysis. The visual analysis of massive trajectory data is challenged by the numerous interactions among different locations, which cause massive clutter. This paper presents a new methodology for visual analysis by integrating algebraic multigrid (AMG) method in data aggregation. The non-parametric method helps to build a multi-layer node representation from a graph which is extracted from trajectory data. The comparison with AMG and other methods shows that AMG method is more advanced in both the spatial representation and the importance of nodes. The new method is tested with real-world dataset of cell-phone signalling records in Beijing. The results show that our method is suitable for processing and creating abstraction of massive trajectory dataset, revealing inherent patterns and creating intuitive and vivid flow maps.     

基于空间统计理论的新疆各地州经济林营养物质积累空间关系特征分析及应用

积累营养物质是森林生态服务功能中的重要组成部分,它反映了林木生长情况和生产投入情况。基于2014年新疆七种主要经济林木积累营养物质调查数据,核算了2014年全疆经济林木氮、磷和钾的物质积累总量,折合当年化肥价值3.14×10⁸元。并利用全局空间自相关模型和地理加权模型（GWR）对该结果进行了分析。结果表明：（1）全疆不同经济林品种积累营养物质价值量的空间分布符合空间集聚理论,呈现某种经济林木在某个地区具有高度集中的种植现象;（2）GWR模型分析结果表明经济林在南疆林业中占有重要地位;（3）南疆各地州经济林发展存在明显差异,其中克孜勒苏柯尔克孜自治州、和田地区和喀什地区处在经济林发展期;阿克苏地区和巴音郭楞蒙古自治州则处在经济林衰产期。上述结果表明通过深入挖掘新疆生态服务功能价值信息,能够提取对新疆经济林产业发展规划具有重要参考价值的信息。研究所使用的思路和方法对其他类似研究具有重要的借鉴意义。     

Integrating a GIS with an expert system to identify and manage dryland salinization

To manage secondary dryland salinization successfully a coordinated regional management approach must be implemented. This paper considers the development of an interactive land classification methodology that identifies key land areas associated with the problem and then conveys information regarding the decision-making process to the end user. The developed system, Salt Manager, utilizes an expert system, a geographic information system, remotely sensed information and a relational database management system to implement the land classification method. Consideration is given in the paper to the salinization process, the problem of system integration and the provision of contextual information via graphic and textual formats.     

Integrating spatial and temporal contexts into a factorization model for POI recommendation

Matrix factorization is one of the most popular methods in recommendation systems. However, it faces two challenges related to the check-in data in point of interest (POI) recommendation: data scarcity and implicit feedback. To solve these problems, we propose a Feature-Space Separated Factorization Model (FSS-FM) in this paper. The model represents the POI feature spaces as separate slices, each of which represents a type of feature. Thus, spatial and temporal information and other contexts can be easily added to compensate for scarce data. Moreover, two commonly used objective functions for the factorization model, the weighted least squares and pairwise ranking functions, are combined to construct a hybrid optimization function. Extensive experiments are conducted on two real-life data sets: Gowalla and Foursquare, and the results are compared with those of baseline methods to evaluate the model. The results suggest that the FSS-FM performs better than state-of-the-art methods in terms of precision and recall on both data sets. The model with separate feature spaces can improve the performance of recommendation. The inclusion of spatial and temporal contexts further leverages the performance, and the spatial context is more influential than the temporal context. In addition, the capacity of hybrid optimization in improving POI recommendation is demonstrated.     

An integration of GIS,virtual reality and the Internet for visualization,analysis and exploration of spatial data

This paper explores the way in which GIS, Virtual Reality (VR) and the Internet are closely integrated through the link of Virtual Reality Modelling Language (VRML) for spatial data visualization, analysis and exploration. Integration takes advantage of each component, and enables the dynamic 3D content to be built, visualized, interacted with and deployed all on the Web. To accomplish this, a hybrid approach that merges the conventional client-side and server-side methods is proposed, which offers the best of both worlds in terms of flexibility and capability, as well as the rational use of computing resources. Based on this approach, a Web-based prototype toolkit is designed and implemented by using an affordable desktop GIS through its macro language together with Java, Common Gateway Interface (CGI) and HTML programming. This toolkit comprises a 3D visualization tool, a 3D analysis tool, and a Java/VRML interface, which are respectively used for the creation of VRML models from 2D maps, surface analysis (e.g. profile creation and visibility analysis), and interaction (e.g. selecting and querying) with the output VRML worlds of 3D visualization and analysis. It is demonstrated that this toolkit provides an integrated environment, facilitating users to gain insights from the interaction with virtual environments that are built from existing GIS databases.