Table of Contents

Chapter 0 Spatial Learner’s Permit 1


Spatial Terminology 2


Applying Spatial Terms 5


Spatial Cognition 8


Spatial Quantities 10


Spherical Earth 11


Concluding Remarks 13


Terms 14


Practice Exercises 14


References 16


UNIT 1 INTRODUCTION 17


Chapter 1 Introduction to Digital Geography 19


Learning Objectives 19


Geographic Information Systems Defined 19


A Brief History of Geographic Information Systems 23


GIS as a Growth Industry 25


Sample Application Areas of GIS 26


The Study of GIS 29


Terms 31


Review Questions 31


References 31


UNIT 2 DIGITAL GEOGRAPHIC DATA AND MAPS 33


Chapter 2 Basic Geographic Concepts 35


Learning Objectives 36


Developing Spatial Awareness 37


Spatial Measurement Levels 40


Spatial Location and Reference 42


Spatial Patterns 45


Geographic Data Collection 47


Populations and Sampling Schemes 52


Making Inferences from Samples 54


Terms 56


Review Questions 56


References 57


Chapter 3 Map Basics 58


Learning Objectives 59


Abstract Nature of Maps 59


A Paradigm Shift in Cartography 60


Map Scale 61


More Map Characteristics 63


Map Projections 63


Grid Systems for Mapping 66


Map Symbolism 73


Map Abstraction and Cartographic Databases 77


Terms 78


Review Questions 78


References 79


Chapter 4 GIS Computer Structure Basics 81


Learning Objectives 82


A Quick Review of the Map as an Abstraction of Space 82


Some Basic Computer File Structures 84


Simple Lists 84


Ordered Sequential Files 85


Indexed Files 86


Database Management Structures 88


Hierarchical Data Structures 88


Network Systems 90


Relational Database Management Systems 92


Some Basic Computer Terminology 95


Terms 96


Review Questions 97


References 97


Chapter 5 GIS Data Models 99


Learning Objectives 100


Graphic Representation of Entities and Attributes 100


GIS System Data Models 104


Raster Models 105


Raster Surface Models 106


Compact Storing of Raster Data 108


Commercial Raster Compaction Products 110


Vector Models 111


An Object-Oriented Data Model 117


Compacting Vector Data Models 117


A Vector Model to Represent Surfaces 118


Systems Models 119


Terms 123


Review Questions 123


References 124


UNIT 3 INPUT, STORAGE, AND EDITING 127


Chapter 6 GIS Input 129


Learning Objectives 129


Primary Data 130


Input Devices 131


Reference Frameworks and Transformations 134


Map Preparation and the Digitizing Process 137


What to Input 140


How Much to Input 141


Methods of Vector Input 142


Methods of Raster Input 143


Remote Sensing Data Input 146


GPS Data Input 149


Secondary Data 150


Metadata and Metadata Standards 151


Terms 154


Review Questions 154


References 155


Chapter 7 Data Storage and Editing 157


Learning Objectives 158


GIS Database Storage 158


Basic Error Types 160


Consequences of Errors 161


Error Detection and Editing 162


Entity Errors: Vector 162


Attribute Errors: Raster and Vector 168


Dealing with Projection Changes 171


Joining Adjacent Maps: Edge Matching 172


Conflation 173


Templating 174


Terms 175


Review Questions 175


References 176


UNIT 4 SPATIAL ANALYSIS 177


Chapter 8 Query and Description 179


Learning Objectives 180


Model Flowcharting 180


GIS Data Query 181


Locating and Identifying Spatial Objects 184


Defining Spatial Characteristics 185


Point Attributes 186


Line Attributes 187


Area Attributes 189


Working with Higher-Level Objects 192


Higher-Level Point Objects 192


Higher-Level Line Objects 195


Higher-Level Area Objects 198


Terms 199


Review Questions 200


References 200


Chapter 9 Measurement 202


Learning Objectives 202


Measuring Length 203


Measuring Polygons 205


Measuring Polygon Lengths 205


Measuring Perimeters of Polygons 206


Calculating Areas of Polygonal Features 207


Measuring Shape 208


Measuring Sinuosity 209


Measuring Polygon Shape 209


Measuring Distance 213


Euclidean Distance 213


Functional Distance 215


Terms 223


Review Questions 224


References 225


Chapter 10 Classification 227


Learning Objectives 228


Classification Principles 228


Elements of Reclassification 230


Neighborhood Functions 231


Roving Windows: Filters 232


Static Neighborhood Functions 235


Buffers 239


Terms 244


Review Questions 244


References 245


Chapter 11 Statistical Surfaces 247


Learning Objectives 248


What are Surfaces? 249


Surface Mapping 250


Nontopographical Surfaces 252


Sampling the Statistical Surface 253


The DEM 254


Interpolation 255


Linear Interpolation 256


Methods of Nonlinear Interpolation 257


Problems of Interpolation 262


Terms 266


Review Questions 267


References 268


Chapter 12 Terrain Analysis 269


Learning Objectives 270


Terrain Reclassification 270


Elevation Zones 270


Slope Analysis 272


Aspect Analysis 273


Shape or Form 275


Viewshed Analysis 279


Soundshed Analysis 282


Cut and Fill 283


Terms 284


Review Questions 284


References 286


Chapter 13 Spatial Arrangement 288


Learning Objectives 289


Point, Area, and Line Arrangements 290


Point Patterns 290


Nearest Neighbor Analysis 291


Thiessen Polygons 293


Area Patterns 295


Distance and Adjacency 296


Other Polygonal Arrangement Measures 297


Linear Patterns 297


Line Densities 298


Nearest Neighbors and Line Intercepts 298


Direction and Circular Statistics 300


Connectivity of Linear Objects 303


Gravity Model 306


Routing and Allocation 307


Terms 309


Review Questions 310


References 311


Chapter 14 Map Overlay 313


Learning Objectives 313


The Cartographic Overlay 314


Point-In-Polygon and Line-In-Polygon Overlay 316


Polygon Overlays 318


Why Perform an Overlay? 318


Types of Map Overlay 319


Types of Vector Overlays 323


Graphical Overlay 324


Topological Vector Overlay 326


A Note about Error in Overlay 326


Dasymetric Mapping 328


Terms 330


Review Questions 331


References 331


Chapter 15 Cartographic Modeling 333


Learning Objectives 334


Model Components 334


The Cartographic Model 335


Types of Cartographic Models 337


Inductive and Deductive Modeling 339


Factor Selection 339


Model Flowcharting 340


Working Through the Model 342


Conflict Resolution 347


Sample Cartographic Models 348


Model Implementation 351


Model Verification 352


Terms 356


Review Questions 356


References 357


UNIT 5 GIS OUTPUT AND DESIGN 359


Chapter 16 Cartography and Visualization 361


Learning Objectives 361


Output: The Display of Analysis 362


Cartographic Output 363


Thematic Maps and Cartograms 364


Multivariate Display 369


Dynamic and Interactive Display 371


Web Mapping and Visualization 372


Virtual and Immersion Environments 374


Mapping the Temporal Dimension 374


Noncartographic Output 375


Tables and Charts 376


Design Considerations 377


Terms 380


Review Questions 380


References 381


Chapter 17 GIS Design 383


Learning Objectives 384


Application Design 385


Some General Systems Characteristics 387


Project Definition 388


Analytical Model Design 389


Components and Procedures 389


GIS Tools for Solving Problems 390


Selecting the Software 390


Scientific Models and GIS 390


Database Design 391


Modeling Tools 391


Establishing the Effective Spatial Domain of the Model 392


Study Area 393


Scale, Resolution, and Level of Detail 393


Classification 394


Coordinate System and Projection 394


Conceptual, Logical, and Physical Models 395


Institutional/System Design 395


GIS Information Products 396


How Information Products Drive the GIS 396


Organizing the Local Views 397


Avoiding Design Creep 398


View Integration 399


System Implementation 399


The Institutional Setting for GIS Operations 400


The System and the Outside World 400


Internal Players 401


External Players 402


Terms 403


Review Questions 403


References 404


Appendix A Software and Data Sources 405


Appendix B Using the World Wide Web to Find Data and GIS Examples 411


Glossary 413


Index 435


Photo Credits 443

About the Author

Michael N. DeMers is an Associate Professor of Geography at
New Mexico State University.  He holds a BS and MS from
University of North Dakota, and a Ph.D from University of Kansas.