A Review of “Geographies of Media and Communication”

Contemporary cartographic research on mapmaking and map use has a broad mandate and, as a consequence, researchers need a broad suite of methods. Consistent with research developments in other geographic subdisciplines, cartographic researchers now use qualitative methods. They offer the advantage of bringing research closer to the problem-solving realms of mapmakers and map users. Our purpose here is to discuss an array of qualitative methods for mapmaking and map use. Questionnaires, interviews, and protocol methods are used to gather verbal data about mapmaking and map use. Ethnographies produce data from direct observation of mapmakers and users. Maps also are sources for document analysis. We use examples of published cartographic research to elaborate on each of these methods.     

Ventures into Viral Cartography: Waffle House,Educational Attainment,and the Social Life of Maps

Viral maps—ones that are shared widely on social media and media outlets—have become an increasingly common part of online conversations about a range of issues. Despite the increasing prevalence of these viral maps, only a few academic researchers have examined the factors leading to their popularity or their social use and effect. In this article, we analyze two case studies of viral maps, a viral tweet about the August 2017 total eclipse and an interactive tool for exploring educational attainment by neighborhood in the United States. By reflecting on our experience as authors of these maps and analyzing the reactions they elicited, we identify several key elements of these maps and their circulation. First, viral maps act as a form of phatic communication, allowing users to restate and react to shared social identities. Second, maps are read from specific times and places, and this spatiotemporal context significantly shapes the reactions of map readers. Finally, viral maps illustrate gaps or improvements in trust between mapmakers and map readers, including questions about map accuracy or the intentions behind the map. We close by considering implications for future research and viral cartography. Key Words: online maps, social networks, viral cartography.     

Fundamental operations in computer-assisted map analysis

Abstract

Geographical information systems (GIS) provide capabilities for the mapping, management and analysis of cartographic information. Unlike most other disciplines, GIS technology was born from specialized applications. A comprehensive theory relating the various techniques used in these applications is only now emerging. By organizing the set of analytic methods into a mathematical structure, a generalized framework for cartographic modelling is developed. Within this framework, users logically order primitive operators on map variables in a manner analogous to traditional algebra and statistics. This paper describes the fundamental classes of operations used in computer-assisted map analysis. Several of the procedures are demonstrated using a fourth-generation computer language for personal computers.     

社会地图研究综述与展望

用地图方法研究社会空间已有较长历史,在不同的研究背景下形成了多种研究模式。近年来,大数据的出现和空间信息可视化技术的发展,不仅为社会地图的广泛应用提供了更多数据和方法支撑,也为社会空间的再认识提供了新的契机和可能。本文在对面向社会空间研究的国内外社会地图运用成果进行系统梳理的基础上, 将社会地图的研究应用归纳为要素呈现、问题解释和理论验证3个阶段,并对其具体应用内容、方法和数据形式进行了综述,总结为统计图、点值图、网格图、密度图等四种类型,并就社会地图在中国社会空间研究中的应用可能性及其方向进行了讨论和展望。     

定性地理信息系统在城市社会空间研究中的应用

定性地理信息系统(定性GIS)是西方人文地理学定性研究的重要方法。它集成了定性和空间元素,更全面地阐明空间背景是如何被社会建构的。这种多元要素的整合,可以表达人们生活空间的多样性和复杂性,有助于展示生活路径的三维可视化细节,实现可视化社会空间过程。本文试图梳理西方定性GIS的方法论并探讨其在基于情感表达的个体数据采集分析、基于混合方法的可视化活动空间研究以及基于多重互动视角的社会空间研究中的应用。定性GIS包含微观和宏观层面的多重含义,使得研究者可以从多个有利位置观察问题并参与其中,有助于城市社会空间研究理论创新,为社会空间研究提供可探索空间。最后,从学科建设、方法论拓展、研究成果表达和研究议题选择等方面对中国开展同类研究进行展望。     

Cartographic generalisation of lines based on a B‐spline snake model

The automation of cartographic map production is still an important research field in Geographical Information Systems (GIS). With the increasing development of monitoring and decision‐aid systems either on computer networks or wireless networks, efficient methods are needed to visualise geographical data while respecting some application constraints (accuracy, legibility, security, etc.). This paper introduces a B‐spline snake model to deal with the current operators involved in the cartographic generalisation process of lines. This model enables us to perform those operators with a continuous approach. In order to avoid local conflicts such as intersections or self‐intersections, the consistency of the lines is checked and discrete operations such as segment removal are performed during the process. We apply the method to map production in the highly constrained domain of maritime navigation systems. Experimental results of marine chart generalisation yield some discussions about generalisation robustness and quality.     

Road network simplification with knowledge-based spatial analysis

A typical requirement in digital society is the rapid distribution and effective application of digital products. Geographical data bases are far more complex than other ones in that both attribute and spatial data have to be stored and handled under the same framework. On the other hand, the number of end users of digital cartographic data is explosively increasing, ranging from professional map makers to vehicle drivers and individual tourists. Thus arises a question: how can a data supplier give the “best” service to each user? In nature it involves such difficult problems as cartographic generalization and map simplification. In this paper, the author argues that the visual knowledge or perception experience can be effectively exploited and used to guide the process of data simplification. We have developed a prototype system with a subset of the vector road database covering Munich city.

     

GIS-cartography: visual decision support for spatio-temporal data handling

Abstract

This paper describes a new joint Dutch research initiative ‘GIS-cartography’, combining the research efforts of the cartographers of Utrecht University, Delft University of Technology and the International Institute for Aerospace Survey and Earth Sciences (ITC) in Enschede. The research initiative focuses on the quantification and visualization of data quality, which will be placed in the context of providing automated visual decision support in specific map use strategies. As these map use strategies can only be performed if the relevant cartographic images can be created, studies of both physical access to the data, user interfaces and the provision of sufficient support to allow the user to understand and to derive sensible conclusions from the data are included in the project. Before modules automatically visualizing data quality can be implemented, data documentation, standardization and integration have to be effected, therefore these issues are also covered.     

Multicriteria generalization (MCG): a decision-making framework for formalizing multiscale environmental data reduction

Environmental simulation models need automated geographic data reduction methods to optimize the use of high-resolution data in complex environmental models. Advanced map generalization methods have been developed for multiscale geographic data representation. In the case of map generalization, positional, geometric and topological constraints are focused on to improve map legibility and communication of geographic semantics. In the context of environmental modelling, in addition to the spatial criteria, domain criteria and constraints also need to be considered. Currently, due to the absence of domain-specific generalization methods, modellers resort to ad hoc methods of manual digitization or use cartographic methods available in off-the-shelf software. Such manual methods are not feasible solutions when large data sets are to be processed, thus limiting modellers to the single-scale representations. Automated map generalization methods can rarely be used with confidence because simplified data sets may violate domain semantics and may also result in suboptimal model performance. For best modelling results, it is necessary to prioritize domain criteria and constraints during data generalization. Modellers should also be able to automate the generalization techniques and explore the trade-off between model efficiency and model simulation quality for alternative versions of input geographic data at different geographic scales. Based on our long-term research with experts in the analytic element method of groundwater modelling, we developed the multicriteria generalization (MCG) framework as a constraint-based approach to automated geographic data reduction. The MCG framework is based on the spatial multicriteria decision-making paradigm since multiscale data modelling is too complex to be fully automated and should be driven by modellers at each stage. Apart from a detailed discussion of the theoretical aspects of the MCG framework, we discuss two groundwater data modelling experiments that demonstrate how MCG is not just a framework for automated data reduction, but an approach for systematically exploring model performance at multiple geographic scales. Experimental results clearly indicate the benefits of MCG-based data reduction and encourage us to continue expanding the scope of and implement MCG for multiple application domains.     

Cartographic Visualization: An Assessment and Epistemological Review*

This article examines the concept of cartographic visualization. The value of cartographic visualization as an essential component in the study of geographic phenomena is discussed. Ontological and epistemological perspectives are addressed, with examinations of positivist, realist, postmodern, feminist, and anarchist approaches to visualization. Critiques of cartographic visualization from social theorists and quantitative positivists are presented. The author asserts that cartographic visualization is not restricted to any one particular epistemological framework but may combine methods of knowledge production. For comprehensive analysis of spatial data, cartographic visualization must be included along with other qualitative and quantitative analysis.     

A Review of: “Applications of Spatial Data Structures: Computer Graphics,Image Processing,and GIS”. By H. SAMET. (Addison-Wesley Publishing Company,Inc, 1989.) [Pp. xv + 507; figures,tables, appendix,references, name and credit index,subject index.] Price US $49.95. ISBN 020150300 X (hardback).

The introduction of automated generalisation procedures in map production systems requires that generalisation systems are capable of processing large amounts of map data in acceptable time and that cartographic quality is similar to traditional map products. With respect to these requirements, we examine two complementary approaches that should improve generalisation systems currently in use by national topographic mapping agencies. Our focus is particularly on self‐evaluating systems, taking as an example those systems that build on the multi‐agent paradigm. The first approach aims to improve the cartographic quality by utilising cartographic expert knowledge relating to spatial context. More specifically, we introduce expert rules for the selection of generalisation operations based on a classification of buildings into five urban structure types, including inner city, urban, suburban, rural, and industrial and commercial areas. The second approach aims to utilise machine learning techniques to extract heuristics that allow us to reduce the search space and hence the time in which a good cartographical solution is reached. Both approaches are tested individually and in combination for the generalisation of buildings from map scale 1:5000 to the target map scale of 1:25 000. Our experiments show improvements in terms of efficiency and effectiveness. We provide evidence that both approaches complement each other and that a combination of expert and machine learnt rules give better results than the individual approaches. Both approaches are sufficiently general to be applicable to other forms of self‐evaluating, constraint‐based systems than multi‐agent systems, and to other feature classes than buildings. Problems have been identified resulting from difficulties to formalise cartographic quality by means of constraints for the control of the generalisation process.     

Counting for Women*

Despite their limitations, quantitative methods have an important role in feminist geographic research. As discussed in this essay, quantitative methods can contribute by describing and analyzing the broad contours of difference, by providing a basis for informed policy making and progressive political change, by identifying people and places for in-depth study, and by situating qualitative research in a broader context. At the same time, feminist insights can enhance quantitative analysis. Collaboration between quantitative and qualitative researchers is essential.     

Land cover and land use change in the Italian central Apennines: A comparison of assessment methods

Analyses of land-use cover changes (LUCC) are fundamental to the understanding of numerous social, economical and environmental problems and can be carried out rapidly, using either cartographic or census data. However, the trends of the two methods differ in direction and quantity.For this study, a historical and a recent remote sensing-derived map were homogenized to reduce misleading changes and to assess spatial aggregation errors. This was carried out by means of a data integration procedure based on landscape metrics, allowing cartographic and census trends to be compared. Discrepancies between data were thus highlighted, both in absolute surface value and in evolution.The methodology presented, and the results obtained, could be employed to evaluate and improve LUCC analyses aimed at assessing landscape identity, both in the case of analyses based only on LU census data, or of those based only on LC cartographic data. This could lead to benefits for both biodiversity conservation and environmental planning on a large scale.     

Beyond Abstract Map Symbols

Abstract

Crucial aspects of the referent phenomena which provide the subject matter for cartographic symbolism are often overlooked by map interpreters in their haste to “read maps at a glance.” The blame rests largely on those practitioners of the environmental sciences who stress the simple, intuitive nature of maps, while effectively ignoring the true complexity of the cartographic communication process. Those persons who are responsible for traditional map interpretation training programs are also at fault for implying, through long emphasis, that symbol identification, position location, and navigation constitute the essence of map analysis. The intuitive acceptability of map symbols in spite of their abstract character is also a deceptive factor. The fact that there is far “more than meets the eye” to map interpretation is easily demonstrated by looking closely at several basic cartographic symbols. In order to become an effective map user the environmental scientist apparently must go well beyond the mastery of conventional map reading principles and learn to deal with diverse informational dimensions in the context of the map use purpose and the physical/cultural make-up of the geographical region under study.     

Map Reading and Abuse

Abstract

The various advantages and limitations of geographical mapping known to map users can be functionally related to the few basic principles which constitute the very nature of the cartographic technique. Numerous map interpretation errors may be traced in large part to a common failure on the part of map users to grasp and effectively deal with these same mapping principles. Since it is possible to identify situations in environmental decision making and planning where the misuse of maps, or outright map reading abuses, could lead to adverse human and environmental impact, the problem is indeed serious. Strategies for minimizing the misuse or abuse of geographical maps appear to rely most heavily on a thorough understanding of basic mapping principles.     

Stop making sense: the trials and tribulations of qualitative data analysis

An account is given of a research project with particular attention to the place of data analysis and interpretation. It shines some light into what often remains the black box of qualitative research practice, the mysterious process of generating a research narrative based on the data. The paper provides other apprentice researchers with an insight into what the data analytical experience can be like, warts and all. It raises issues to do with qualitative data analysis, the use of CAQDAS, grounded theory, the relationship between the narratives of the researcher and the researched, and about the training of qualitative researchers.     

Improvement of GIS graphics for analysis and decision-making

Abstract

Current geographical information systems (GIS) include functions to create cartographic output interactively or automatically. However, none of the systems presently incorporates mechanisms to ensure correct application of graphic functions. Many of today's users of GIS are not trained in the design and production of graphics and may create maps that confuse or mislead map users. Poorly-designed maps may obliterate the patterns in displayed information.

This article investigates ways to improve the quality of GIS graphical displays and increase their effectiveness for decision-making. Alternatives are presented for improving map design in GIS, ranging from non-technical efforts to enhancement of software functionality. Suggestions propose augmenting users' abilities to create maps in an automated environment, using an approach termed amplified intelligence: key decisions default explicitly to users, whose knowledge is amplified by a range of high-level tools to carry out map design operations automatically.     

Mapping uncertain geographical attributes: incorporating robustness into choropleth classification design

ABSTRACT

Choropleth mapping provides a simple but effective visual presentation of geographical data. Traditional choropleth mapping methods assume that data to be displayed are certain. This may not be true for many real-world problems. For example, attributes generated based on surveys may contain sampling and non-sampling error, and results generated using statistical inferences often come with a certain level of uncertainty. In recent years, several studies have incorporated uncertain geographical attributes into choropleth mapping with a primary focus on identifying the most homogeneous classes. However, no studies have yet accounted for the possibility that an areal unit might be placed in a wrong class due to data uncertainty. This paper addresses this issue by proposing a robustness measure and incorporating it into the optimal design of choropleth maps. In particular, this study proposes a discretization method to solve the new optimization problem along with a novel theoretical bound to evaluate solution quality. The new approach is applied to map the American Community Survey data. Test results suggest a tradeoff between within-class homogeneity and robustness. The study provides an important perspective on addressing data uncertainty in choropleth map design and offers a new approach for spatial analysts and decision-makers to incorporate robustness into the mapmaking process.     

Qualitative GIS and the visualization of narrative activity space data

Qualitative activity space data, i.e. qualitative data associated with the routine locations and activities of individuals, are recognized as increasingly useful by researchers in the social and health sciences for investigating the influence of environment on human behavior. However, there has been little research on techniques for exploring qualitative activity space data. This research illustrates the theoretical principles of combining qualitative and quantitative data and methodologies within the context of geographic information systems (GIS), using visualization as the means of inquiry. Through the use of a prototype implementation of a visualization system for qualitative activity space data and its application in a case study of urban youth we show how these theoretical methodological principles are realized in applied research. The visualization system uses a variety of visual variables to simultaneously depict multiple qualitative and quantitative attributes of individuals' activity spaces. The visualization is applied to explore the activity spaces of a sample of urban youth participating in a study on the geographic and social contexts of adolescent substance use. Examples demonstrate how the visualization can be used to explore individual activity spaces to generate hypotheses, investigate statistical outliers, and explore activity space patterns among subject subgroups.     

人类移动性与健康研究中的时间问题

随着地理信息科学的发展,地理学围绕着社会热点问题不断向其他学科交叉渗透,同时学科的交叉也为地理学研究本身注入了热量。空间一直是地理学研究中的基本问题,而时间与空间密不可分,从时间维度研究人类移动性及其丰富内涵具有重要意义。本文在总结人类移动性热点问题的基础上,重点从时间维度探讨了可达性、出行体验与幸福感、人类健康与疾病等问题的研究内容和方法,并从低收入者社区医疗保健可达性研究和阿帕拉契亚乡村地区吸烟者影响因素研究等案例进行详细阐释,最后对人类移动性与健康研究的发展方向进行了展望。