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Choropleth map

About: Choropleth map is a research topic. Over the lifetime, 369 publications have been published within this topic receiving 8331 citations. The topic is also known as: blot map.


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Journal ArticleDOI
TL;DR: Heatmapper is a freely available web server that allows users to interactively visualize their data in the form of heat maps through an easy-to-use graphical interface and is designed to appeal to a wide range of users.
Abstract: Heatmapper is a freely available web server that allows users to interactively visualize their data in the form of heat maps through an easy-to-use graphical interface Unlike existing non-commercial heat map packages, which either lack graphical interfaces or are specialized for only one or two kinds of heat maps, Heatmapper is a versatile tool that allows users to easily create a wide variety of heat maps for many different data types and applications More specifically, Heatmapper allows users to generate, cluster and visualize: (i) expression-based heat maps from transcriptomic, proteomic and metabolomic experiments; (ii) pairwise distance maps; (iii) correlation maps; (iv) image overlay heat maps; (v) latitude and longitude heat maps and (vi) geopolitical (choropleth) heat maps Heatmapper offers a number of simple and intuitive customization options for facile adjustments to each heat map's appearance and plotting parameters Heatmapper also allows users to interactively explore their numeric data values by hovering their cursor over each heat map cell, or by using a searchable/sortable data table view Heat map data can be easily uploaded to Heatmapper in text, Excel or tab delimited formatted tables and the resulting heat map images can be easily downloaded in common formats including PNG, JPG and PDF Heatmapper is designed to appeal to a wide range of users, including molecular biologists, structural biologists, microbiologists, epidemiologists, environmental scientists, agriculture/forestry scientists, fish and wildlife biologists, climatologists, geologists, educators and students Heatmapper is available at http://wwwheatmapperca

1,483 citations

Book
04 Dec 1998
TL;DR: Thematic Cartography and Geovisualization as mentioned in this paper is an important area of research in the field of map design and has been extensively studied in the last few hundred years.
Abstract: PART I Introduction 1. Thematic Cartography and Geovisualization 1.1 What is a Thematic Map? 1.2 How are Thematic Maps Used? 1.3 Basic Steps for Communicating Map Information 1.4 Consequences of Technological Change in Cartography 1.5 Geovisualization 1.6 Related Techniques 1.7 Cognitive Issues in Cartography 1.8 Social and Ethical Issues in Cartography 2. A Historical Perspective on Thematic Cartography 2.1 A Brief History of Cartography 2.2 History of Thematic Cartography 2.3 History of U.S. Academic Cartography 2.4 The Paradigms of American Cartography 3. Statistical and Graphical Foundation 3.1 Population and Sample 3.2 Descriptive Versus Inferential Statistics 3.3 Methods for Analyzing Spatial Data, Ignoring Location 3.4 Numerical Summaries in Which Location Is an Integral Component PART II Principles of Cartography 4. Data Classification 4.1 Common Methods of Data Classification 4.2 Using Spatial Context to Simplify Choropleth Maps 4.3 Using Multiple Criteria to Determine Class Intervals 5. Principles of Symbolization 5.1 Nature of Geographic Phenomena 5.2 Levels of Measurement 5.3 Visual Variables 5.4 Comparison of Choropleth, Proportional Symbol, Isopleth, and Dot Mapping 5.5 Selecting Visual Variables for Choropleth Maps 6. Scale and Generalization 6.1 Geographic and Cartographic Scale 6.2 Definitions of Generalization 6.3 Models of Generalization 6.4 The Fundamental Operations of Generalization 6.5 An Example of Generalization 6.6 MapShaper: A Free Web-Based Generalization Service 7. The Earth and Its Coordinate System 7.1 Basic Characteristics of the Earth's Graticule 7.2 A Brief History of Latitude and Longitude 7.3 Determining the Earth's Size and Shape 8. Elements of Map Projections 8.1 The Map Projection Concept 8.2 The Reference Globe and Developable Surfaces 8.3 The Mathematics of Map Projections 8.4 Map Projection Characteristics 8.5 Distortion on Map Projections 8.6 Projection Properties 9. Selecting an Appropriate Map Projection 9.1 Potential Selection Guidelines 9.2 Examples of Selecting Projections 10. Principles of Color 10.1 How Color Is Processed by the Human Visual System 10.2 Hardware Considerations in Producing Color Maps for Graphics Displays 10.3 Models for Specifying Color 11. Map Elements and Typography 11.1 Alignment and Centering 11.2 Map Elements 11.3 Typography 12. Cartographic Design 12.1 Cartographic Design 12.2 Case Study: Real Estate Site Suitability Map 13. Map Reproduction 13.1 Reproduction Versus Dissemination 13.2 Planning Ahead 13.3 Map Editing 13.4 Raster Image Processing for Print Reproduction 13.5 Screening for Print Reproduction 13.6 Aspects of Color Printing 13.7 High-Volume Print Reproduction 13.8 Nonprint Reproduction and Dissemination PART III Mapping Techniques 14. Choropleth Mapping 14.1 Selecting Appropriate Data 14.2 Data Classification 14.3 Factors for Selecting a Color Scheme 14.4 Details of Color Specification 14.5 Legend Design 14.6 Classed Versus Unclassed Mapping 15. Dasymetric Mapping 15.1 Selecting Appropriate Data and Ancillary Information 15.2 Eicher and Brewer's Work 15.3 Mennis and Hultgren's Intelligent Dasymetric Mapping (IDM) 15.4 LandScan 15.5 Langford and Unwin's Generalized Dasymetric Approach 16. Isarithmic Mapping 16.1 Selecting Appropriate Data 16.2 Manual Interpolation 16.3 Automated Interpolation for True Point Data 16.4 Criteria for Selecting an Interpolation Method for True Point Data 16.5 Limitations of Automated Interpolation Approaches 16.6 Tobler's Pycnophylactic Approach: An Interpolation Method for Conceptual Point Data 16.7 Symbolization 17. Proportional Symbol and Dot Mapping 17.1 Selecting Appropriate Data For Proportional Symbol Maps 17.2 Kinds of Proportional Symbols 17.3 Scaling Proportional Symbols 17.4 Legend Design for Proportional Symbol Maps 17.5 Handling Overlap on Proportional Symbol Maps 17.6 Redundant Symbols 17.7 Selecting Appropriate Data for Dot Maps 17.8 Creating a Dot Map 18. Multivariate Mapping 18.1 Bivariate Mapping 18.2 Multivariate Mapping Involving Three or More Attributes 18.3 Cluster Analysis 19. Cartograms and Flow Maps 19.1 Cartograms 19.2 Flow Mapping Part IV Geovisualization 20. Visualizing Terrain 20.1 Nature of the Data 20.2 Vertical Views 20.3 Oblique Views 20.4 Physical Models 21. Map Animation 21.1 Early Developments 21.2 Visual Variables and Categories of Animation 21.3 Examples of Animations 21.4 Using 3-D Space to Display Temporal Data 21.5 Does Animation Work? 22. Data Exploration 22.1 Goals of Data Exploration 22.2 Methods of Data Exploration 22.3 Examples of Data Exploration Software 23. Visualizing Uncertainty 23.1 Basic Elements of Uncertainty 23.2 General Methods for Depicting Uncertainty 23.3 Visual Variables for Depicting Uncertainty 23.4 Applications of Visualizing Uncertainty 23.5 Studies of the Effectiveness of Methods for Visualizing Uncertainty 24. Web Mapping 24.1 A Brief History of Web Mapping 24.2 Cartographic Web Sites: A Classification 24.3 Tying Together the Five Continua 25. Virtual Environments 25.1 Defining Virtual and Mixed Environments 25.2 Technologies for Creating Virtual Environments 25.3 The Four "I" Factors of Virtual Environments 25.4 Applications of Geospatial Virtual Environments 25.5 Research Issues in Geospatial Virtual Environments 25.6 Developments in Mixed Environments 25.7 Health, Safety, and Social Issues 26. Trends in Research and Development 26.1 Linked Micromap Plots and Conditioned Choropleth Maps 26.2 Using Senses Other Than Vision to Interpret Spatial Patterns 26.3 Collaborative Geovisualization 26.4 Multimodal Interfaces 26.5 Information Visualization and Spatialization 26.6 Spatial Data Mining 26.7 Visual Analytics 26.8 Mobile Mapping and Location-Based Services 26.9 Keeping Pace with Recent Developments Appendix: Lengths of One Degree Latitude and Longitude Glossary References Index

605 citations

Journal ArticleDOI
TL;DR: In this article, a study of 159 counties in the eastern US using county choropleth data and ancillary land-use data and polygonal (vector) and grid (raster) dasymetric methods were tested and evaluated map accuracy using both statistical analyses and visual prese
Abstract: Dasymetric maps display statistical data in meaningful spatial zones Such maps can be preferable to choropleth maps that show data by enumeration zones, because dasymetric zones more accurately represent underlying data distributions Though dasymetric mapping has existed for well over a century, the methods for producing these maps have not been thoroughly examined In contrast, research on areal interpolation has been more thorough and has examined methods of transferring data from one set of map zones to another, an issue that is applicable to dasymetric mapping Inspired by this work, we tested five dasymetric mapping methods, including methods derived from work on areal interpolation Dasymetric maps of six socio-economic variables were produced fm a study area of 159 counties in the eastern US using county choropleth data and ancillary land-use data Both polygonal (vector) and grid (raster) dasymetric methods were tested We evaluated map accuracy using both statistical analyses and visual prese

481 citations

Journal ArticleDOI
TL;DR: The R package tmap offers a coherent plotting system for thematic maps that is based on the layered grammar of graphics, and contains several convenient functions for reading and processing spatial data.
Abstract: Thematic maps show spatial distributions. The theme refers to the phenomena that is shown, which is often demographical, social, cultural, or economic. The best known thematic map type is the choropleth, in which regions are colored according to the distribution of a data variable. The R package tmap offers a coherent plotting system for thematic maps that is based on the layered grammar of graphics. Thematic maps are created by stacking layers, where per layer, data can be mapped to one or more aesthetics. It is also possible to generate small multiples. Thematic maps can be further embellished by configuring the map layout and by adding map attributes, such as a scale bar and a compass. Besides plotting thematic maps on the graphics device, they can also be made interactive as an HTML widget. In addition, the R package tmaptools contains several convenient functions for reading and processing spatial data.

378 citations

Journal ArticleDOI
TL;DR: The authors compared seven methods using responses by fifty-six subjects in a two-part experiment involving nine series of U.S. mortality maps and found that matched legends across a series of maps (when possible) increased map-comparison accuracy by approximately 28 percent.
Abstract: Our research goal was to determine which choropleth classification methods are most suitable for epidemiological rate maps. We compared seven methods using responses by fifty-six subjects in a two-part experiment involving nine series of U.S. mortality maps. Subjects answered a wide range of general map-reading questions that involved individual maps and comparisons among maps in a series. The questions addressed varied scales of map-reading, from individual enumeration units, to regions, to whole-map distributions. Quantiles and minimum boundary error classification methods were best suited for these general choropleth map-reading tasks. Natural breaks (Jenks) and a hybrid version of equal-intervals classing formed a second grouping in the results, both producing responses less than 70 percent as accurate as for quantiles. Using matched legends across a series of maps (when possible) increased map-comparison accuracy by approximately 28 percent. The advantages of careful optimization procedures in chorop...

335 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202119
202017
201926
201817
201719
201614