Introduction to Data Analysis Using
Geographic Information Systems

Copyright ©  2002  Regents of the University of Minnesota. All rights reserved.

Table of Contents

• Introduction
  
  
• Capabilities of a GIS
  
  
• Analytical and Operational Functions
  
  
• Conclusions and Recommendations
  
  

Introduction

Figure 1. Logical flow chart of analytical operations within a GIS framework. This figure diagrams the logical structure of GIS operation. An initial geographic question drives the data collection. Commonly data collection is done by either manually digitizing data from appropriate maps or by importing tabular data which is referenced with georeferenced coordinates that define the geographic position of the tabular (attribute) data. The data is then converted to a digital format and is entered into a database where it is stored as integrated map and attribute data. The analytical process then manipulates both map and attribute data through the linkages that GIS establishes between them. Two types of output are common: tabular (summary data, statistics, reports) and cartographic (maps, map files, and map overlays). Figure 2. Schematic representation of map data and associated attribute data. Examples are shown for typical natural resource and urban GIS applications. Data are geographically referenced on map layers, each with a primary theme. Specific details or attributes can then be identified for each feature of interest on the map. These attribute data or map key information are then stored in the GIS database.

A Geographic Information System (GIS) is an automated information system that is able to compile, store, retrieve, analyze, and display mapped data. Only a decade ago this technology was limited to a relatively small number of colleges, universities, and local, state, and federal agencies. The two general types of users are systems users (who have hands-on use of the technology) and end users (who are users of the information generated by a GIS). Today, it is used by government officials, natural resource and social analysts, and many others. Its applications include environmental research and model building, urban demographic studies, and transportation analysis to mention only a few. While its use is expanding almost daily, its most important applications include those that support decision making.

Map data used by GIS are collected from existing maps, aerial photos, satellites, and other sources. A digitizer or similar device is used to convert compiled map data to a digital form in order to make it computer compatible. This transformation allows the storage, retrieval, and analysis of the mapped data to be performed by the computer. Maps produced by a GIS are typically displayed on computer monitors or are printed on paper. Unlike many other forms of computer graphics, such as computer-aided drafting (CAD) systems, a GIS displays actual geographic or mapped objects. GIS, however, is more than a mapping system. What sets it apart from even the most sophisticated mapping system is its power to analyze data and to present the results of that analysis as useful information to assist decision makers.

For a GIS to accurately represent occurrences on the earth's surface, data must be reliable, accurate, and pertinent. Because the success of the GIS and all decisions that are based on it ultimately rest on the integrity of the data, the GIS must be capable of compiling, updating, and maintaining its data. No matter how sophisticated the analytical tools, misused or questionable data will make the final output doubtful. The adage "garbage in - garbage out" certainly holds true in the world of GIS.

Use of GIS is driven by the need to answer geographical or spatial questions. The ensuing data collection, database analysis, and output are in response to those questions (Figure 1). The purpose of collecting data for a GIS is (a) to inventory a geographically defined area (for example, to locate all state-owned parcels within a particular area) or (b) to test hypotheses and build models. Though the data is initially collected for one of these reasons, data collected to answer one set of questions is frequently used in subsequent analyses to answer questions that were not anticipated at the time the data was collected. For example, after capturing detailed soils data to determine what crops can be grown, the data may be useful for answering questions about septic tank suitability.

The GIS database contains both map data (depicting location of geographical objects) and attribute data (describing physical characteristics of each object). Physical characteristics (such as timber species and tree diameter) and/or non-physical characteristics (such as estimated market value and management codes) are examples of attribute data that could be contained in a GIS used to analyze forestry problems. During a GIS analysis, site (map) data is linked with situation (attribute) data for each mapped timber stand. It is this link, which is automatically performed by the GIS software, that gives GIS its analytical power. The relationship between map data and its associated attribute data are shown in Figure 2 for typical natural resource and urban maps.

In GIS terminology, the individual spatial phenomena or map themes are referred to as map layers. One layer can contain roads, another soils, and another can indicate land ownership. Each layer comprises all of the pertinent map and attribute data. Though other, non-layered approaches to GIS exist, the layered map model will be used throughout this paper to give examples of GIS analysis and use.

The next section of this publication, Capabilities of a GIS, examines spatial questions that drive a GIS and the basic requirements for the database. The final section, Analytical and Operational Functions, examines how GIS software links map and attribute data in order to analyze spatial problems.

Daniel L. Falbo is a former graduate research assistant.

Lloyd P. Queen is a research associate (Remote Sensing Laboratory).

Charles R. Blinn is an extension specialist and associate professor.

All are in the Department of Forest Resources, University of Minnesota, St. Paul, MN 55108.

This contribution was supported by the College of Natural Resources and the University of Minnesota Agricultural Experiment Station under Projects MN 42-40 and MN 40-16 and the Minnesota Extension Service (including funds from the Renewable Resources Extension Act).

Editor: Richard Sherman

Graphic Designer: Michael Mechavich

Produced by Communication and Educational Technology Services, University of Minnesota Extension.

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