In Chapter 6: “Data Characteristics and Visualization,” you learned the different ways to query, classify, and summarize information in attribute tables. These methods are indispensable for understanding a dataset’s fundamental quantitative and qualitative trends. However, they do not take advantage of the greatest strength of a geographic information system (GIS), notably the direct spatial relationships. Spatial analysis is a fundamental component of a GIS that allows for an in-depth study of a dataset or dataset’s topological and geometric properties. This chapter discusses the basic spatial analysis techniques for vector datasets.

Learning Objectives

• Demonstrate knowledge of how vector data models are implemented in geographic information systems.
• Demonstrate knowledge of concepts and terms related to the variety of single overlay analysis techniques available to analyze and manipulate the spatial attributes of a vector feature dataset.
• Demonstrate knowledge of the concepts and terms of implementing basic multiple-layer operations and methodologies used on vector feature datasets.

Chapter Sections

• 7.1 Introduction
• 7.2 Vector Data Modeling
• 7.3 Single Layer Analysis
• 7.4 Multiple Layer Analysis
• 7.5 Chapter Review
• 7.6 Applied Learning
• 7.7 Creative Commons Attributions and References

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