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Thematic Cartography and Geovisualization: International Student Edition 4th edition [Kietas viršelis]

3.97/5 (38 ratings by Goodreads)
(Pennsylvania State University, PA, USA), , (University of Kansas, USA), (American River College, USA)
  • Formatas: Hardback, 584 pages, aukštis x plotis: 280x210 mm, weight: 2560 g, 39 Tables, black and white; 90 Line drawings, color; 4 Line drawings, black and white; 372 Halftones, color; 12 Halftones, black and white; 462 Illustrations, color; 16 Illustrations, black and white
  • Išleidimo metai: 18-Aug-2022
  • Leidėjas: CRC Press
  • ISBN-10: 0367712709
  • ISBN-13: 9780367712709
Kitos knygos pagal šią temą:
Thematic Cartography and Geovisualization: International Student Edition 4th editionDidesnis paveikslėlis
  • Formatas: Hardback, 584 pages, aukštis x plotis: 280x210 mm, weight: 2560 g, 39 Tables, black and white; 90 Line drawings, color; 4 Line drawings, black and white; 372 Halftones, color; 12 Halftones, black and white; 462 Illustrations, color; 16 Illustrations, black and white
  • Išleidimo metai: 18-Aug-2022
  • Leidėjas: CRC Press
  • ISBN-10: 0367712709
  • ISBN-13: 9780367712709
Kitos knygos pagal šią temą:
Pastovi nuoroda: https://www.kriso.lt/db/9780367712709.html
Raktažodžiai:
This comprehensive and well-established cartography textbook covers the theory and the practical applications of map design and the appropriate use of map elements. It explains the basic methods for visualizing and analyzing spatial data and introduces the latest cutting-edge data visualization techniques. The fourth edition responds to the extensive developments in cartography and GIS in the last decade, including the continued evolution of the Internet and Web 2.0; the need to analyze and visualize large data sets (commonly referred to as Big Data); the changes in computer hardware (e.g., the evolution of hardware for virtual environments and augmented reality); and novel applications of technology.

Key Features of the Fourth Edition:











Includes more than 400 color illustrations and it is available in both print and eBook formats.





A new chapter on Geovisual Analytics and individual chapters have now been dedicated to Map Elements, Typography, Proportional Symbol Mapping, Dot Mapping, Cartograms, and Flow Mapping.





Extensive revisions have been made to the chapters on Principles of Color, Dasymetric Mapping, Visualizing Terrain, Map Animation, Visualizing Uncertainty, and Virtual Environments/Augmented Reality.





All chapters include Learning Objectives and Study Questions.





Provides more than 250 web links to online content, over 730 references to scholarly materials, and additional 540 references available for Further Reading.

There is ample material for either a one or two-semester course in thematic cartography and geovisualization. This textbook provides undergraduate and graduate students in geoscience, geography, and environmental sciences with the most valuable up-to-date learning resource available in the cartographic field. It is a great resource for professionals and experts using GIS and Cartography and for organizations and policy makers involved in mapping projects.

Recenzijos

Interest in professional cartography has decreased since the 1980s at the expense of newer and emergent geographic information systems (GIS) software and related technologies. However, the fourth edition of this classic cartography textbook features significant additions made since its previous edition (2009) and reclaims geographic analysis as the realm of digital cartography. This text is admirably comprehensive in describing the development of the field of modern cartography from the 1950s to the present and surprisingly current in its engagement with the latest research. The text is organized into three main parts covering, respectively, principles, techniques, and geovisualization. The principles section covers foundational cartographic topics, including symbolization, classification, map projections, and map production. The techniques section covers choropleth maps and more advanced approaches, including highly informative chapters on intelligent dasymetric mapping (IDM) and multivariate mapping. The geovisualization chapters (part 3) include the most significant additions, including details of geovisual data analytics, map animation, and virtual environments. This edition clearly conveys the relevance of digital cartography to the emerging field of data science and will continue to be a required resource for academic programs offering the GIS specialization. This latest version is a teaching resource for undergraduates, graduate students, and professionals offering entrée to the classic and latest cartographic innovations.

C. A. Badurek, SUNY Cortland

Overall, to my mind, this impressive book stands far above any other cartographic textbook available. I rec­ommend it as required reading for every GIS/cartographic program across academia and will remain a rich and relevant resource of cartographic and geovisualization knowledge for some years to come.

Daniel G. Cole, Smithsonian Institution, published in Cartographic Perspectives #103, 2024 (full review https://cartographicperspectives.org/index.php/journal/article/view/1919/2283 )

Slocum, McMaster, Kessler, and Howard have done an excellent job in both updating the previous edition and adding new material. This is a first-class textbook that I recommend without reservation. Thematic cartography and visualization are, in my view, increasingly important topics. The basic elements of cartography remain central, but students must be exposed to the latest cutting-edge visualization techniques, which this volume does very well.

Fraser Taylor, Carleton University, published in Cartographica, Vol. 59, No. 2, 2024 (full review https://www.utpjournals.press/doi/full/10.3138/cart-2024-0011)

The long-awaited update of this book is welcomed. It provides a good overview of many developments in recent cartographic research in a manner that is accessible to upper-level undergraduate students or (post-)graduate students. Its breadth might mean that students need to purchase only one book for multiple courses. For those cartographic practitioners who may have come to the discipline from another industry and who are looking to increase their technical knowledge, this is also a fine reference that introduces the scholarship that sits behind many mapping techniques.

Amy L. Griffin, School of Science, RMIT University, Melbourne, Australia Published in the International Journal of Cartography, 05 Nov 2024 (full review: https://www.tandfonline.com/doi/full/10.1080/23729333.2024.2423320)

Preface xxi
Acknowledgments xxv
About the Authors xxvii
Chapter 1 Introduction
1(24)
1.1 Overview
1(1)
1.2 Learning Objectives
2(1)
1.3 What Is a Thematic Map?
2(1)
1.4 How Are Thematic Maps Used?
2(3)
1.5 Basic Steps for Communicating Map Information
5(3)
1.6 Technological Change in Cartography and Its Consequences
8(3)
1.7 What Is Geovisualization?
11(3)
1.8 Related GIScience Techniques
14(2)
1.9 Cognitive Issues in Cartography
16(1)
1.10 Social and Ethical Issues in Cartography
17(1)
1.11 Summary
18(1)
1.12 Study Questions
19(6)
References
20(5)
Part I Principles of Cartography
Chapter 2 A Historical Perspective on Thematic Cartography
25(18)
2.1 Introduction
25(1)
2.2 Learning Objectives
25(1)
2.3 A Brief History of Cartography
26(1)
2.4 History of Thematic Cartography
27(3)
2.4.1 The Rise of Social Cartography
28(2)
2.5 History of U.S. Academic Cartography
30(6)
2.5.1 Period 1: Early Beginnings
30(1)
2.5.1.1 John Paul Goode
30(1)
2.5.1.2 Erwin Raisz
31(1)
2.5.1.3 Guy-Harold Smith
31(1)
2.5.1.4 Richard Edes Harrison
32(1)
2.5.2 Period 2: The Post-War Era and the Building of Core Academic Programs
32(1)
2.5.2.1 University of Wisconsin
32(1)
2.5.2.2 University of Kansas
33(1)
2.5.2.3 University of Washington
34(1)
2.5.3 Period 3: Growth of Secondary Programs
35(1)
2.5.4 Period 4: Integration with GI Science
36(1)
2.6 European Thematic Cartography
36(1)
2.6.1 The Swiss School
36(1)
2.6.2 The British Experimental Cartographic Unit
36(1)
2.6.3 Bertin and French Thematic Cartography
37(1)
2.7 The Paradigms of American Cartography
37(2)
2.7.1 Analytical Cartography
37(1)
2.7.2 Maps and Society
38(1)
2.7.2.1 Privacy
39(1)
2.7.2.2 Power and Access
39(1)
2.7.2.3 Ethics
39(1)
2.7.2.4 Public Participation GIS/Mapping
39(1)
2.8 Summary
39(2)
2.9 Study Questions
41(2)
References
41(2)
Chapter 3 Statistical and Graphical Foundation
43(20)
3.1 Introduction
43(1)
3.2 Learning Objectives
43(1)
3.3 Population and Sample
43(1)
3.4 Descriptive versus Inferential Statistics
43(2)
3.5 Analyzing the Distribution of Individual Attributes
45(4)
3.5.1 Tables
45(1)
3.5.1.1 Raw Table
45(1)
3.5.1.2 Grouped-Frequency Table
45(1)
3.5.2 Graphs
46(1)
3.5.2.1 Point and Dispersion Graphs
46(1)
3.5.2.2 Histogram
47(1)
3.5.3 Numerical Summaries
47(1)
3.5.3.1 Measures of Central Tendency
47(1)
3.5.3.2 Measures of Dispersion
48(1)
3.6 Analyzing the Relationship between Two or More Attributes
49(6)
3.6.1 Tables
49(1)
3.6.2 Graphs
50(1)
3.6.3 Numerical Summaries
51(1)
3.6.3.1 Bivariate Correlation
51(2)
3.6.3.2 Bivariate Regression
53(1)
3.6.3.3 Reduced Major-Axis Approach
54(1)
3.6.3.4 Multiple Regression and Other Multivariate Techniques
54(1)
3.6.3.5 Considerations in Using Correlation-Regression
54(1)
3.7 Exploratory Data Analysis
55(1)
3.8 Numerical Summaries for Geographic Data
56(4)
3.8.1 Geographic Center
56(1)
3.8.2 Spatial Autocorrelation and Measuring Spatial Pattern
57(1)
3.8.3 Measuring Map Complexity
58(2)
3.9 Summary
60(1)
3.10 Study Questions
60(3)
References
61(2)
Chapter 4 Principles of Symbolization
63(20)
4.1 Introduction
63(1)
4.2 Learning Objectives
63(1)
4.3 Nature of Geographic Phenomena
63(4)
4.3.1 Spatial Dimension
63(1)
4.3.2 Models of Geographic Phenomena
64(1)
4.3.3 Phenomena versus Data
65(2)
4.4 Levels of Measurement
67(1)
4.5 Visual Variables
67(4)
4.5.1 Visual Variables for Quantitative Phenomena
68(1)
4.5.1.1 Spacing
68(1)
4.5.1.2 Size
69(1)
4.5.1.3 Perspective Height
69(1)
4.5.1.4 Hue, Lightness, and Saturation
69(1)
4.5.2 Visual Variables for Qualitative Phenomena
69(1)
4.5.2.1 Orientation and Shape
69(1)
4.5.2.2 Arrangement
69(1)
4.5.2.3 Hue
69(1)
4.5.3 Some Considerations in Working with Visual Variables
69(2)
4.6 Comparison of Four Common Thematic Mapping Techniques
71(3)
4.6.1 Choropleth Map
71(1)
4.6.2 Proportional Symbol Map
72(2)
4.6.3 Isopleth Map
74(1)
4.6.4 Dot Map
74(1)
4.6.5 Discussion
74(1)
4.7 Selecting Visual Variables for Choropleth Maps
74(3)
4.8 Using Senses Other than Vision to Interpret Spatial Patterns
77(4)
4.8.1 Sound
78(1)
4.8.2 Touch (or Haptics)
79(1)
4.8.3 Smell
80(1)
4.9 Summary
81(1)
4.10 Study Questions
81(2)
References
82(1)
Chapter 5 Data Classification
83(16)
5.1 Introduction
83(1)
5.2 Learning Objectives
83(1)
5.3 Data to Be Classified
83(2)
5.4 Equal Intervals Method
85(2)
5.5 Quantiles Method
87(1)
5.6 Mean-Standard Deviation Method
88(1)
5.7 Natural Breaks
89(1)
5.8 Optimal
89(3)
5.8.1 The Jenks-Caspall Algorithm
89(1)
5.8.2 The Fisher-Jenks Algorithm
90(1)
5.8.3 Advantages and Disadvantages of Optimal Classification
91(1)
5.9 Head/Tail Breaks: A Novel Classification Method
92(2)
5.10 Criteria for Selecting a Classification Method
94(1)
5.11 Considering the Spatial Distribution of the Data
95(1)
5.12 Summary
96(1)
5.13 Study Questions
97(2)
References
98(1)
Chapter 6 Scale and Generalization
99(18)
6.1 Introduction
99(1)
6.2 Learning Objectives
99(1)
6.3 Geographic and Cartographic Scale
99(1)
6.3.1 Multiple-Scale Databases
100(1)
6.4 Definitions of Generalization
100(1)
6.4.1 Definitions of Generalization in the Manual Domain
100(1)
6.4.2 Definitions of Generalization in the Digital Domain
101(1)
6.5 Models of Generalization
101(3)
6.5.1 Robinson et al.'s Model
101(1)
6.5.2 McMaster and Shea's Model
101(1)
6.5.2.1 Why Generalization Is Needed: The Conceptual Objectives of Generalization
101(2)
6.5.2.2 When Generalization Is Required
103(1)
6.6 The Fundamental Operations of Generalization
104(6)
6.6.1 A Framework for the Fundamental Operations
104(1)
6.6.2 Vector-Based Operations
104(1)
6.6.2.1 Simplification
104(1)
6.6.2.2 Smoothing
104(1)
6.6.2.3 Aggregation
104(2)
6.6.2.4 Amalgamation
106(1)
6.6.2.5 Collapse
106(1)
6.6.2.6 Merging
106(1)
6.6.2.7 Refinement
106(1)
6.6.2.8 Exaggeration
106(1)
6.6.2.9 Enhancement
107(1)
6.6.2.10 Displacement
107(1)
6.6.3 The Simplification Process
107(3)
6.7 An Example of Generalization
110(2)
6.8 New Developments in Cartographic Generalization
112(2)
6.8.1 Measurement of Scale Change
112(1)
6.8.2 Fully Automated Generalization
112(1)
6.8.3 Data Models for Generalization
113(1)
6.8.4 New Forms of Cartographic Data
113(1)
6.9 Summary
114(1)
6.10 Study Questions
114(3)
References
114(3)
Chapter 7 The Earth and Its Coordinate System
117(18)
7.1 Introduction
117(1)
7.2 Learning Objectives
117(1)
7.3 Basic Characteristics of Earth's Graticule
117(4)
7.3.1 Latitude
118(1)
7.3.2 Longitude
118(2)
7.3.3 Distance and Directions on Earth's Spherical Surface
120(1)
7.4 Determining Earth's Size and Shape
121(10)
7.4.1 Earth's Size
121(1)
7.4.2 Earth's Shape
122(1)
7.4.2.1 The Prolate versus Oblate Spheroid Controversy
122(2)
7.4.2.2 Reference Ellipsoid and the Graticule
124(2)
7.4.2.3 The Geoid
126(2)
7.4.2.4 Geodetic Datum
128(2)
7.4.2.5 Geodetic Datums and Thematic Cartography
130(1)
7.5 Summary
131(1)
7.6 Study Questions
131(4)
References
133(2)
Chapter 8 Elements of Map Projections
135(24)
8.1 Introduction
135(1)
8.2 Learning Objectives
135(1)
8.3 The Map Projection Concept
136(1)
8.4 The Reference Globe and Developable Surfaces
136(1)
8.5 The Mathematics of Map Projections
136(3)
8.6 Map Projection Characteristics
139(6)
8.6.1 Class
139(4)
8.6.2 Case
143(1)
8.6.3 Aspect
144(1)
8.7 Distortion on Map Projections
145(7)
8.7.1 A Visual Look at Distortion
145(1)
8.7.2 Scale Factor
146(1)
8.7.3 Tissot's Indicatrix
147(1)
8.7.4 Distortion Patterns
148(1)
8.7.5 Using Geocart to Visualize Distortion Patterns
148(4)
8.8 Projection Properties
152(4)
8.8.1 Preserving Areas
152(1)
8.8.2 Preserving Angles
152(1)
8.8.3 Preserving Distances
152(2)
8.8.4 Preserving Directions
154(2)
8.8.5 Compromise Projections
156(1)
8.9 Summary
156(1)
8.10 Study Questions
157(2)
References
158(1)
Chapter 9 Selecting an Appropriate Map Projection
159(24)
9.1 Introduction
159(1)
9.2 Learning Objectives
159(1)
9.3 Potential Selection Guidelines
160(4)
9.3.1 Snyder's Hierarchical Selection Guideline
160(1)
9.3.1.1 World Map Projections
160(3)
9.3.1.2 Map Projections for a Hemisphere
163(1)
9.3.1.3 Map Projections for a Continent, Ocean, or Smaller Region
163(1)
9.3.1.4 Map Projections for Special Properties
164(1)
9.4 Examples of Selecting Projections
164(15)
9.4.1 Mapping World Literacy Rates
164(3)
9.4.2 Mapping Russian Population Distribution
167(1)
9.4.3 Mapping Migration to the United States
168(2)
9.4.4 Mapping Tornado Paths across Kansas
170(4)
9.4.5 Mapping a Flight Path from Fairbanks, AK to Seoul, South Korea
174(1)
9.4.5.1 Mapping the Flight Path from Space
175(1)
9.4.5.2 Mapping the Flight Path's Direction
175(1)
9.4.5.3 Mapping the Flight Path Distance
176(1)
9.4.5.4 Mapping the Great Circle Flight Path
176(1)
9.4.5.5 Mapping the Rhumb Line
177(1)
9.4.5.6 Mapping the Flight Path Using Google Maps
177(1)
9.4.6 Discussion
178(1)
9.5 Web-Based Interactive Map Projection Selection
179(1)
9.6 Summary
180(1)
9.7 Study Questions
181(2)
References
182(1)
Chapter 10 Principles of Color
183(20)
10.1 Introduction
183(1)
10.2 Learning Objectives
183(1)
10.3 How Color Is Processed by the Human Visual System
183(6)
10.3.1 Visible Light and the Electromagnetic Spectrum
183(1)
10.3.2 Structure of the Eye
184(2)
10.3.3 Theories of Color Perception
186(1)
10.3.4 Simultaneous Contrast
186(1)
10.3.5 Color Vision Impairment
187(1)
10.3.6 Beyond the Eye
187(2)
10.4 Models for Specifying Color
189(5)
10.4.1 The RGB Model
189(1)
10.4.2 The CMYK Model
189(1)
10.4.3 The HSV Model
190(1)
10.4.4 The Munsell Model
190(2)
10.4.5 The CIE Model
192(2)
10.4.6 Discussion
194(1)
10.5 Terminology and Principles in the Practical Use of Color
194(5)
10.5.1 Color Wheels
194(2)
10.5.2 Tints, Shades, and Tones
196(1)
10.5.3 Qualitative Color Conventions
196(2)
10.5.4 Quantitative Color Conventions
198(1)
10.5.5 Theme-Oriented Color Schemes
198(1)
10.6 Summary
199(1)
10.7 Study Questions
200(3)
References
201(2)
Chapter 11 Map Elements
203(16)
11.1 Introduction
203(1)
11.2 Learning Objectives
203(1)
11.3 Alignment and Centering
203(1)
11.4 Common Map Elements
203(14)
11.4.1 Frame Line and Neat Line
205(1)
11.4.2 Mapped Area
205(2)
11.4.3 Inset
207(1)
11.4.4 Title and Subtitle
207(2)
11.4.5 Legend
209(3)
11.4.6 Data Source
212(2)
11.4.7 Scale
214(2)
11.4.8 Orientation
216(1)
11.4.9 Relative Type Sizes for Certain Map Elements
217(1)
11.5 Summary
217(1)
11.6 Study Questions
218(1)
References
218(1)
Chapter 12 Typography
219(12)
12.1 Introduction
219(1)
12.2 Learning Objectives
219(1)
12.3 What Is Typography?
219(3)
12.3.1 Characteristics of Type
219(3)
12.4 General Typographic Guidelines
222(1)
12.5 Specific Typographic Guidelines
223(5)
12.5.1 All Features (Point, Linear, and Areal)
223(1)
12.5.2 Point Features
224(1)
12.5.3 Linear Features
225(1)
12.5.4 Areal Features
226(2)
12.6 Automated Type Placement
228(1)
12.7 Summary
228(1)
12.8 Study Questions
228(3)
References
229(2)
Chapter 13 Cartographic Design
231(22)
13.1 Introduction
231(1)
13.2 Learning Objectives
231(1)
13.3 Elements of Cartographic Design
231(10)
13.3.1 The Design Process
234(1)
13.3.2 Visual Hierarchy
234(1)
13.3.3 Contrast
235(2)
13.3.4 Figure-Ground
237(2)
13.3.5 Balance
239(2)
13.4 Case Study: Real Estate Site Suitability Map
241(10)
13.4.1 Steps 1-3 of the Map Communication Model
243(1)
13.4.2 Step 4 of the Map Communication Model: Design and Construct the Map
243(1)
13.4.3 Return to Procedure 4: Implementation of Map Elements and Typography
244(1)
13.4.3.1 Frame Line and Neat Line
244(1)
13.4.3.2 Mapped Area
244(3)
13.4.3.3 Inset
247(1)
13.4.3.4 Title and Subtitle
247(1)
13.4.3.5 Legend
248(1)
13.4.3.6 Data Source
249(1)
13.4.3.7 Scale
249(1)
13.4.3.8 Orientation
249(1)
13.4.4 Final Procedures
249(2)
13.5 Summary
251(1)
13.6 Study Questions
251(2)
References
251(2)
Chapter 14 Map Reproduction
253(14)
14.1 Introduction
253(1)
14.2 Learning Objectives
253(1)
14.3 Planning Ahead
253(1)
14.4 Map Editing
254(1)
14.5 Raster Image Processing for Print Reproduction
254(1)
14.5.1 Printing the Digital Map
255(1)
14.6 Screening for Print Reproduction
255(3)
14.6.1 Halftone and Stochastic Screening
256(1)
14.6.2 Halftone Screening Parameters
257(1)
14.6.3 Stochastic Screening Parameters
257(1)
14.7 Aspects of Color Printing
258(2)
14.7.1 Process Colors
258(1)
14.7.2 Spot Colors
258(1)
14.7.3 High-Fidelity Process Colors
259(1)
14.7.4 Color Management Systems
259(1)
14.8 High-Volume Print Reproduction
260(4)
14.8.1 The Prepress Phase
260(1)
14.8.2 File Formats for Prepress
260(1)
14.8.3 Proofing Methods
261(1)
14.8.4 Offset Lithographic Printing
262(2)
14.9 Summary
264(1)
14.10 Study Questions
264(3)
References
264(3)
Part II Mapping Techniques
Chapter 15 Choropleth Mapping
267(20)
15.1 Introduction
267(1)
15.2 Learning Objectives
267(1)
15.3 Selecting Appropriate Data
267(2)
15.4 Factors for Selecting a Color Scheme
269(6)
15.4.1 Kind of Data
270(1)
15.4.2 Color Naming
271(1)
15.4.3 Color Vision Impairment
272(1)
15.4.4 Simultaneous Contrast
273(1)
15.4.5 Map Use Tasks
273(1)
15.4.6 Color Associations
274(1)
15.4.7 Aesthetics
274(1)
15.4.8 Age of the Intended Audience
274(1)
15.4.9 Presentation vs. Data Exploration
275(1)
15.4.10 Economic Limitations and Client Requirements
275(1)
15.5 Systems for Specifying Color Schemes
275(3)
15.5.1 Approaches for Classed Maps
275(1)
15.5.1.1 Color Ramping and HSV Systems
275(1)
15.5.1.2 The Munsell Curve
276(1)
15.5.1.3 ColorBrewer
276(1)
15.5.2 Approaches for Unclassed Maps
277(1)
15.5.2.1 Applying the Munsell Curve
277(1)
15.5.2.2 Kovesi's Approach
277(1)
15.6 Classed vs. Unclassed Mapping
278(3)
15.6.1 Maintaining Numerical Data Relations
279(1)
15.6.2 Presentation vs. Data Exploration
280(1)
15.6.3 Summarizing the Results of Experimental Studies
280(1)
15.6.3.1 Specific Information
281(1)
15.6.3.2 General Information
281(1)
15.6.3.3 Discussion
281(1)
15.7 Legend Design
281(1)
15.8 Illuminated Choropleth Mapping
282(1)
15.9 Summary
283(1)
15.10 Study Questions
284(3)
References
285(2)
Chapter 16 Dasymetric Mapping
287(22)
16.1 Introduction
287(1)
16.2 Learning Objectives
287(1)
16.3 Selecting Appropriate Data and Ancillary Information
287(1)
16.4 Some Basic Approaches for Dasymetric Mapping
288(2)
16.5 Eicher and Brewer's Study
290(2)
16.6 Mennis and Hultgren's Intelligent Dasymetric Mapping (IDM)
292(1)
16.7 Two Approaches for Producing Dasymetric Maps of Population Density
293(9)
16.7.1 Approach One: Using Land Cover and Limiting Ancillary Data Sets
293(5)
16.7.2 Approach Two: Use Zoning Polygons and Limiting Ancillary Data Sets
298(2)
16.7.3 Discussion
300(2)
16.8 Socscape: A Web App for Visualizing Racial Diversity
302(1)
16.9 Mapping the Global Population Distribution
302(4)
16.9.1 Gridded Population of the World
302(1)
16.9.2 LandScan
303(1)
16.9.3 Global Human Settlement Layer
304(2)
16.10 Summary
306(1)
16.11 Study Questions
307(2)
References
307(2)
Chapter 17 Isarithmic Mapping
309(20)
17.1 Introduction
309(1)
17.2 Learning Objectives
309(1)
17.3 Selecting Appropriate Data
309(1)
17.4 Manual Interpolation
310(1)
17.5 Automated Interpolation for True Point Data
311(10)
17.5.1 Triangulation
312(1)
17.5.2 Inverse-Distance Weighting
313(2)
17.5.3 Ordinary Kriging
315(1)
17.5.3.1 Semivariance and the Semivariogram
315(1)
17.5.3.2 Kriging Computations
316(2)
17.5.4 Thin-Plate Splines
318(1)
17.5.5 Choosing among the Interpolation Methods
319(2)
17.6 Tobler's Pycnophylactic Interpolation
321(2)
17.7 Symbolization
323(2)
17.7.1 Some Basic Symbolization Approaches
323(2)
17.7.2 Color Stereoscopic Effect
325(1)
17.8 Summary
325(2)
17.9 Study Questions
327(2)
References
328(1)
Chapter 18 Proportional Symbol Mapping
329(18)
18.1 Introduction
329(1)
18.2 Learning Objectives
329(1)
18.3 Selecting Appropriate Data
329(1)
18.4 Kinds of Proportional Symbols
330(2)
18.5 Scaling Proportional Symbols
332(5)
18.5.1 Mathematical Scaling
332(2)
18.5.2 Perceptual Scaling
334(1)
18.5.2.1 Formulas for Perceptual Scaling
334(1)
18.5.2.2 Problems in Applying the Formulas
335(2)
18.5.3 Range-Graded Scaling
337(1)
18.6 Legend Design
337(3)
18.6.1 Arranging Symbols
337(3)
18.6.2 Which Symbols to Include
340(1)
18.7 Handling Overlap of Symbols
340(2)
18.7.1 How Much Overlap?
340(2)
18.7.2 Symbolizing Overlap
342(1)
18.8 Necklace Maps
342(1)
18.9 Summary
343(1)
18.10 Study Questions
344(3)
References
344(3)
Chapter 19 Dot Mapping
347(12)
19.1 Introduction
347(1)
19.2 Learning Objectives
347(1)
19.3 Key Issues Involved in Dot Mapping
347(5)
19.3.1 Determining Regions within Which Dots Should Be Placed
347(2)
19.3.2 Selecting Dot Size and Unit Value
349(1)
19.3.3 Placing Dots within Regions
350(1)
19.3.3.1 Placing Dots Manually
350(1)
19.3.3.2 Placing Dots Digitally
350(2)
19.3.4 Designing a Legend
352(1)
19.4 Graduated Dot Mapping
352(2)
19.5 Interactive Dot Mapping on the Web
354(1)
19.6 Summary
355(1)
19.7 Study Questions
356(3)
References
356(3)
Chapter 20 Cartograms
359(18)
20.1 Introduction
359(1)
20.2 Learning Objectives
360(1)
20.3 Methods that Attempt to Preserve the Shape of Enumeration Units
360(4)
20.3.1 Noncontiguous Cartograms
360(1)
20.3.2 Contiguous Cartograms
361(2)
20.3.2.1 Gridded Cartograms
363(1)
20.3.3 Mosaic Cartograms
363(1)
20.4 Methods that Do Not Preserve the Shape of Enumeration Units
364(5)
20.4.1 Rectangular Cartograms
364(2)
20.4.1.1 Rectilinear Cartograms
366(1)
20.4.2 Dorling Cartograms
366(3)
20.4.3 Demers Cartograms
369(1)
20.5 Contrasting Various Cartogram Methods
369(2)
20.5.1 Contrasting Cartogram Methods in Terms of Aspects of Accuracy
369(1)
20.5.2 A User Study of Major Cartogram Methods
370(1)
20.6 Alternatives to Conventional Cartograms
371(3)
20.6.1 Combined Choropleth/Proportional Symbol Maps
371(1)
20.6.2 Value-by-Alpha Maps
372(1)
20.6.3 Balanced Cartograms
373(1)
20.7 Summary
374(1)
20.8 Study Questions
375(2)
References
376(1)
Chapter 21 Flow Mapping
377(16)
21.1 Introduction
377(1)
21.2 Learning Objectives
377(1)
21.3 Basic Types of Flow Maps and Associated Data for Flow Mapping
378(1)
21.4 Issues in Designing Flow Maps
379(1)
21.5 Flow Mapping Prior to Automation
379(2)
21.6 Early Digital Flow Mapping Efforts by Waldo Tobler
381(1)
21.7 Examples of Recent Digital Flow Mapping
382(6)
21.7.1 Stephen and Jenny's Interactive Web-Based Origin-Destination Flow Map
382(2)
21.7.2 Koylu et al.'s Web-Based Software for Designing Origin-Destination Flow Maps
384(1)
21.7.2.1 Koylu and Guo's User Study
384(1)
21.7.2.2 Koylu et al.'s FlowMapper Software
385(2)
21.7.3 Flow Mapping in Virtual Environments
387(1)
21.8 Geovisual Analytics and Flow Mapping
388(2)
21.9 Summary
390(1)
21.10 Study Questions
390(3)
References
391(2)
Chapter 22 Multivariate Mapping
393(30)
22.1 Introduction
393(1)
22.2 Learning Objectives
393(1)
22.3 Bivariate Mapping
394(7)
22.3.1 Comparing Maps
394(1)
22.3.1.1 Comparing Choropleth Maps
394(1)
22.3.1.2 Comparing Miscellaneous Thematic Maps
395(1)
22.3.1.3 Comparing Maps for Two Points in Time
395(2)
22.3.2 Combining Two Attributes on the Same Map
397(1)
22.3.2.1 Bivariate Choropleth Maps
397(3)
22.3.2.2 Additional Bivariate Mapping Techniques
400(1)
22.4 Multivariate Mapping Involving Three or More Attributes
401(7)
22.4.1 Comparing Maps
401(1)
22.4.2 Combining Attributes on the Same Map
401(1)
22.4.2.1 Trivariate Choropleth Maps
401(2)
22.4.2.2 Multivariate Dot Maps
403(1)
22.4.2.3 Multivariate Point Symbol Maps
404(2)
22.4.2.4 Acquiring Specific and General Information from Multivariate Maps
406(1)
22.4.2.5 Ring Maps: An Alternative to Conventional Symbolization Approaches
406(2)
22.5 Cluster Analysis
408(7)
22.5.1 Basic Steps in Hierarchical Cluster Analysis
409(5)
22.5.2 Adding a Contiguity Constraint to a Hierarchical Cluster Analysis
414(1)
22.6 Summary
415(1)
22.7 Study Questions
416(7)
References
417(6)
Part III Geovisualization
Chapter 23 Visualizing Terrain
423(24)
23.1 Introduction
423(1)
23.2 Learning Objectives
423(1)
23.3 Nature of the Data
423(1)
23.4 Vertical Views
424(8)
23.4.1 Hachures
424(1)
23.4.2 Contour-Based Methods
425(2)
23.4.2.1 Eynard and Jenny's Work
427(1)
23.4.3 Raisz's Physiographic Method
428(1)
23.4.4 Shaded Relief
428(1)
23.4.5 Morphometric Techniques
429(1)
23.4.5.1 Symbolizing Aspect and Slope: Brewer and Marlow's Approach
429(1)
23.4.5.2 Symbolizing Other Morphometric Parameters
430(2)
23.5 Oblique Views
432(3)
23.5.1 Block Diagrams
432(2)
23.5.2 Panoramas and Related Oblique Views
434(1)
23.5.3 Plan Oblique Relief
434(1)
23.6 Physical Models
435(2)
23.7 Issues in Creating Shaded Relief
437(6)
23.7.1 Generalizing the Terrain
437(2)
23.7.2 Selecting an Azimuth and Sun Elevation for Illumination
439(1)
23.7.3 Other Lighting Model Issues
440(1)
23.7.4 Representation of Swiss-Style Rock Drawing
441(1)
23.7.5 Color Considerations
442(1)
23.8 Summary
443(1)
23.9 Study Questions
444(3)
References
445(2)
Chapter 24 Map Animation
447(20)
24.1 Introduction
447(1)
24.2 Learning Objectives
447(1)
24.3 Early Developments
448(1)
24.4 Visual Variables for Animation
448(1)
24.5 Examples of Temporal Animations
449(4)
24.5.1 Animating Movement and Flows
449(1)
24.5.2 Animating Choropleth Maps
450(1)
24.5.2.1 Some Basic Examples of Choropleth Animation
450(1)
24.5.2.2 Should We Generalize Choropleth Animations?
451(1)
24.5.2.3 Should We Utilize Classed or Unclassed Maps?
451(1)
24.5.3 Animating Proportional Symbol Maps
452(1)
24.5.4 Animating Isarithmic Maps
452(1)
24.5.5 Other Temporal Animations
452(1)
24.6 Examples of Nontemporal Animations
453(3)
24.6.1 Peterson's Early Work
453(2)
24.6.2 Gershon's Early Work
455(1)
24.6.3 Fly-Overs
455(1)
24.6.4 Viegas and Wattenberg's Wind Map
455(1)
24.7 Enhancing the Interactivity in Animations
456(3)
24.7.1 Harrower's Work
456(2)
24.7.2 CoronaViz
458(1)
24.8 Does Animation Work?
459(2)
24.9 Guidelines for Designing Your Own Animations
461(1)
24.10 Using 3-D Space to Display Temporal Data
462(2)
24.11 Summary
464(1)
24.12 Study Questions
464(3)
References
465(2)
Chapter 25 Data Exploration
467(22)
25.1 Introduction
467(1)
25.2 Learning Objectives
467(1)
25.3 Goals of Data Exploration
467(1)
25.4 Methods of Data Exploration
468(2)
25.4.1 Manipulating Data
468(1)
25.4.2 Varying the Symbolization
468(1)
25.4.3 Manipulating the User's Viewpoint
468(1)
25.4.4 Multiple Map Views
468(1)
25.4.5 Linking Maps with Other Forms of Display
469(1)
25.4.6 Highlighting Portions of a Data Set
469(1)
25.4.7 Probing the Display
469(1)
25.4.8 Toggling Individual Themes On and Off
469(1)
25.4.9 Animation
470(1)
25.4.10 Access to Miscellaneous Resources
470(1)
25.4.11 How Symbols Are Assigned to Attributes
470(1)
25.4.12 Automatic Map Interpretation
470(1)
25.5 Examples of Data Exploration
470(15)
25.5.1 Moellering's 3-D Mapping Software
470(1)
25.5.2 ExploreMap and Map Sequencing
470(1)
25.5.3 Project Argus
471(1)
25.5.4 MapTime
472(2)
25.5.5 CommonGIS
474(2)
25.5.6 GeoDa
476(2)
25.5.7 Micromaps
478(1)
25.5.7.1 Linked Micromaps Plot
478(2)
25.5.7.2 Conditioned Micromaps
480(1)
25.5.8 ViewExposed
480(2)
25.5.9 Using Tableau to Create Interactive Data Visualizations
482(3)
25.6 Summary
485(1)
25.7 Study Questions
485(4)
References
486(3)
Chapter 26 Geovisual Analytics
489(20)
26.1 Introduction
489(1)
26.2 Learning Objectives
489(1)
26.3 Characteristics and Limitations of Big Data
489(1)
26.4 What Is Geovisual Analytics?
490(1)
26.5 The Self-Organizing Map (SOM)
491(2)
26.6 Examples of Geovisual Analytics
493(12)
26.6.1 TaxiVis: A System for Visualizing Taxi Trips in NYC
494(2)
26.6.2 Mosaic Diagrams: A Technique for Visualizing Spatiotemporal Data
496(1)
26.6.3 CarSenToGram: An Approach for Visualizing Twitter Data
497(3)
26.6.4 Crowd Lens: A Tool for Visualizing OpenStreetMap Contributions
500(2)
26.6.5 Use of a SOM for Sense-of-Place Analysis
502(3)
26.7 Summary
505(1)
26.8 Study Questions
505(4)
References
506(3)
Chapter 27 Visualizing Uncertainty
509(20)
27.1 Introduction
509(1)
27.2 Learning Objectives
509(1)
27.3 Basic Elements of Uncertainty
509(2)
27.4 General Methods for Depicting Uncertainty
511(1)
27.5 Visual Variables for Depicting Uncertainty
511(2)
27.5.1 Some Examples of Intrinsic Visual Variables
511(1)
27.5.2 Some Examples of Extrinsic Visual Variables
512(1)
27.6 Applications of Visualizing Uncertainty
513(10)
27.6.1 Handling the Uncertainty in Choropleth Maps
513(1)
27.6.1.1 Using Confidence Levels (CLs) to Create Class Breaks
514(1)
27.6.1.2 Using Maximum Likelihood Estimation to Create Class Breaks
515(1)
27.6.1.3 Using the SAAR Software to Visualize Uncertainty
516(1)
27.6.2 Visualizing Climate Change Uncertainty
516(3)
27.6.3 Visualizing Uncertainty in Decision-Making
519(1)
27.6.3.1 Visualizing the Uncertainty of Water Balance Models
519(1)
27.6.3.2 Visualizing the Uncertainty of Forecasted Hurricane Paths
520(1)
27.6.4 Examples of Interactivity and Animation
521(2)
27.7 Using Sound to Represent Data Uncertainty
523(2)
27.8 Summary
525(1)
27.9 Study Questions
525(4)
References
526(3)
Chapter 28 Virtual Environments and Augmented Reality
529(22)
28.1 Introduction
529(1)
28.2 Learning Objectives
529(1)
28.3 Defining VEs and AR
529(2)
28.4 Technologies for Creating VEs
531(4)
28.4.1 Personalized Displays
531(1)
28.4.2 Wall-Size Displays
531(3)
28.4.3 Head-Mounted Displays
534(1)
28.4.4 Room-Format and Drafting-Table Format Displays
534(1)
28.5 The Four "I" Factors of VEs
535(2)
28.5.1 Immersion
535(1)
28.5.2 Interactivity
536(1)
28.5.3 Information Intensity
536(1)
28.5.4 Intelligence of Objects
537(1)
28.6 Some Key Questions Regarding VEs
537(6)
28.6.1 Are Specialized Symbols Necessary for Thematic Maps Created in VEs?
537(2)
28.6.2 Are Stereoscopic Maps More Effective than Non-Stereoscopic Maps?
539(1)
28.6.3 What Are Some Examples of VEs That Make Use of Caves and Wall-Size Displays?
540(1)
28.6.3.1 Using a CAVE to Create Soils Maps
540(1)
28.6.3.2 Using a Wall-Size Display to Obtain Public Input on Climate Change Scenarios
540(2)
28.6.3.3 HMDs as a Potential Cost-Effective Solution for Collaborative Efforts
542(1)
28.6.4 What Progress Has Been Made Toward Developing a Digital Earth?
542(1)
28.7 Some Recent Examples of the Utilization of AR
543(2)
28.7.1 The Augmented Reality Sandbox
543(1)
28.7.2 Using AR to Enhance an Understanding of Topographic Maps
544(1)
28.7.3 Developing Novel Methods for Interacting with AR Environments
544(1)
28.7.4 Holograms
545(1)
28.8 Health, Safety, and Social Issues
545(1)
28.9 Summary
546(1)
28.10 Study Questions
546(5)
References
547(4)
Glossary 551(22)
Index 573
Terry Slocum is an Emeritus Professor with the University of Kansas where he taught cartography and statistics for 35 years, and chaired the Department of Geography for 8 years. His research interests have included data exploration, map animation, visualizing uncertainty, stereoscopic displays, history of thematic mapping, and color usage on maps. He has published in numerous refereed journals, including Cartography and Geographic Information Science, Cartographica, The Cartographic Journal, Annals of the American Association of Geographers, Journal of Geoscience Education, and Journal of Geography. Professor Slocum has been affiliated with six grants from the U.S. National Science Foundation, and received two Teacher Appreciation Awards from the Center for Teaching Excellence at the University of Kansas. He has chaired 14 dissertation and thesis committees and served on more than 75 dissertation and thesis committees.

Robert B. McMaster is Vice Provost and Dean of Undergraduate Education, and Professor of Geography, at the University of MinnesotaTwin Cities. His research interests include automated generalization, environmental risk assessment, Geographic Information Science and society, and the history of U.S. academic cartography. He has authored or edited seven books on cartography and GIS, and his papers have been published in The American Cartographer, Cartographica, The International Yearbook of Cartography, Geographical Analysis, Cartography and GIS, and the International Journal of GIS. He served as editor of the journal Cartography and Geographic Information Systems from 1990-1996. He has served as President of the United States Cartography and Geographic Information Society, President of UCGIS, and Vice President of the International Cartographic Association. Robert served a three-year term on the National Research Councils Mapping Science Committee (2005-2008). In 2010, he was named GIS Educator of the Year by the University Consortium on Geographic Information Science. In 2013 he was named Fellow of UCGIS.

Fritz Kessler is a Teaching Professor with Penn State. His teaching interests span cartography, statistics, and geography of health. His research focus spans several topics in cartography that include map projections, geometric and geopotential datums, history of thematic mapping, and data exploration. He has published in numerous refereed journals, including Cartography and Geographic Information Science, Cartographica, Cartographic Perspectives, Annals of the American Association of Geographers, Journal of Geography, and GeoJournal. He also coauthored a book with Dr. Sarah Battersby (at Tableau) titled Working with Map Projections: A Guide to their Selection. He is a former President of the North American Cartographic Information Society (NACIS) and a board member to the Cartography and Geographic Information Society (CaGIS). His cartographic background is not limited to academia but has evolved through a several professional positions including Ohio Universitys Cartographic Center, USGS Water Resource Division, Intergraph Corporation, R. R. Donnelley and Sons, and the University of Kansas T. R. Smith Map Library.

Hugh Howard is a professor of GIS at American River College in Sacramento, California, which hosts one of the largest GIS programs in the nation. He is the GIS Coordinator, Geosciences Department Chair, and currently teaches five GIS courses, including Cartographic Design for GIS. Hugh earned his Ph.D. in Geography from the University of Kansas specializing in cartographic design, and developed an expert system software application to aid students in designing better maps. In 2019, he won an Excellence in Education award from the California Geographic Information Association (CGIA), and a Lifetime Achievement in Geospatial Two-Year College Education award from the GeoTech Center (an NSF-funded National Geospatial Technology Center of Excellence). Hugh has worked as a cartographer for the U.S. Forest Service, the City of San Francisco, CB Richard Ellis, and Cartographics. He also taught GIS and managed GIS labs at Stanford University and San Francisco State University.