Pub. Date:
Introduction to Geographical Information Systems / Edition 4

Introduction to Geographical Information Systems / Edition 4

by Ian Heywood


View All Available Formats & Editions
Current price is , Original price is $130.75. You
Select a Purchase Option (New Edition)
  • purchase options
    $27.73 $130.75 Save 79% Current price is $27.73, Original price is $130.75. You Save 78.79158699808795%.
    • Free return shipping at the end of the rental period details
    • Textbook Rentals in 3 Easy Steps  details
    Note: Access code and/or supplemental material are not guaranteed to be included with textbook rental or used textbook.
  • purchase options
    $110.50 $130.75 Save 15% Current price is $110.5, Original price is $130.75. You Save 15%.
  • purchase options
    $60.77 $130.75 Save 54% Current price is $60.77, Original price is $130.75. You Save 54%.
    Note: Access code and/or supplemental material are not guaranteed to be included with textbook rental or used textbook.

Product Details

ISBN-13: 2900273722594
Publisher: Pearson
Publication date: 06/22/2012
Edition description: New Edition
Pages: 480
Product dimensions: 7.70(w) x 10.40(h) x 1.00(d)

About the Author

Ian Heywood, previously Director of Director of Growing Business and Skills for Scottish Enterprise Grampian, Director of Open and Distance Learning for RobertGordonUniversity, Aberdeen, and a Senior Lecturer in GIS at ManchesterMetropolitanUniversity, is now a freelance consultant and Director of the Ideas Academy Ltd.

Sarah Cornelius is a Lecturer in the School of Education at the University of Aberdeen, specializing in adult and online learning. She was previously an Associate Lecturer for the Open University and has taught GIS at Manchester Metropolitan University and the Free University of Amsterdam.

Steve Carver is a Senior Lecturer in the Department of Geography at the University of Leeds. He is Director of the MA in GIS and MSc in GIS.

Read an Excerpt

Chapter 2: Spatial Data


all maps, and other sources of spatial data, are generated with a purpose in mind. In most cases that purpose is to turn data into information which will be communicated to a third party. Every year the managers of Happy Valley produce a map of the ski area for use by visitors. The map shows the location of ski trails, car parks, hotels, emergency shelters and ski lifts. Its purpose is to help visitors orient themselves and decide how to spend their time. Naturally, such a map can have a strong influence over the user. For example, visitors are unlikely to dine at a restaurant if they cannot find it on the map. However, there are restaurants in the area that are not shown on the official Happy Valley map. The ski company wishes to encourage visitors to use its facilities, not those owned by competitors. This simple example illustrates how purpose can influence the character and quality of a spatial data set. Clearly, you would not use this map on its own if you were trying to compile a data set of the restaurants in Happy Valley. However, you may not know that the map was incomplete.

In some cases maps may have a single purpose. The propaganda maps produced by the allies during the Second World War were designed to convince the general public that the war effort was going well (Monmonier, 1991). The true geography of Europe was distorted to emphasize the area occupied by the allied forces. This was effective in boosting the morale of the allies, but produced maps of limited use in other circumstances. Other maps, such as the topographic maps produced by national mapping agencies, aim to meet the needs of a wide range of users, ranging from utility companies to outdoor enthusiasts. In this case, the maps will be more geographically accurate than the propaganda maps described above, but they will still contain generalized data to enable them to be of wide generic use. These generalizations will limit their use for certain applications. a utility company is unlikely to use national maps, on their own, to plan the detailed installation of a new set of electricity cables, because these maps do not contain details about the location of the existing cable network.

Whilst not strictly a spatial characteristic in its own right, the purpose for which a spatial data set has been created will influence the quality and spatial detail provided by the data set. an appreciation of the purpose behind the production of a data set is, therefore, an essential prerequisite for judging whether or not the data are appropriate for use in a particular situation. Linked closely to purpose is the idea of scale.


Virtually all sources of spatial data, including maps, are smaller than the reality they represent (Monmonier, 1991; Keates, 1982). Scale gives an indication of how much smaller than reality a map is. Scale can be defined as the ratio of a distance on the map to the corresponding distance on the ground (Martin, 1996). an alternative definition is offered by Laurini and Thompson (1992) as the order of magnitude or level of generalization at which phenomena exist or are perceived or observed. Scale can be expressed in one of three ways: as a ratio scale, a verbal scale or a graphical scale (Figure 2.1).

Examples of ratio scales are 1:5000 and 1:5,000,000. at a scale of 1:5000 a 1 mm line on the map represents a 5000 mm line on the ground. In the same fashion a line of 1 m on the map represents a line of 5000 m on the ground; the units do not matter as long as they are the same. a verbal scale would express the scale in words, for example `1 cm represents 50 m'. Finally, a graphic scale (or scale bar) is usually drawn on the map to illustrate the distances represented visually. Graphic scales are frequently used on computer maps. They are useful where changes to the scale are implemented quickly and interactively by the user. In such cases, recalculating scale could be time-consuming, and the ratios produced (which may not be whole numbers) may be difficult to interpret. Redrawing a graphic scale in proportion to the map is relatively straightforward and simple to understand. However, it is often possible in GIS to specify the scale at which you require your maps using a ratio representation.

Standard topographic maps contain examples of verbal, ratio and graphical scales. It should be remembered that small-scale maps (for example, 1:250,000 or 1:1,000,000) are those which cover large areas. Conversely, large-scale maps (for example, 1:10,000 or 1:25,000) cover small areas and contain large amounts of detail. With some data used in GIS, such as aerial photographs or satellite imagery, the scale is not immediately obvious and may have to be calculated by the user. Scale is also important when using spatial entities (points, lines and areas) to represent generalized two-dimensional versions of real-world features.

Spatial Entities

Traditionally, maps have used symbols to represent real-world features. Examination of a map will reveal three basic symbol types: points, lines and areas (Monmonier, 1991). These were introduced in Chapter 1 (Figure. 1.4) and are the basic spatial entities. Each is a simple two-dimensional model that can be used to represent a feature in the real world. These simple models have been developed by cartographers to allow them to portray three-dimensional features in two dimensions on a piece of paper (Laurini and Thompson, 1992; Martin, 1996). Box 2.2 provides more details on the types of features that points, lines and areas can be used to represent.

The representation of real-world features using the point, line and area entity types appears relatively straightforward. However, the method chosen to represent a spatial feature will depend on the scale used. Consider the way cities are represented on maps of different scales. On a world map a point would be the most appropriate method of representation, given the number of cities to be included. However, at national and regional scales a point could provide an oversimplified view of the extent of the geographical area covered by a city. a point used here would tell us nothing about the relative size of cities, so it is more likely that the cartographer would choose to represent the cities using areas. at the local scale even the area spatial entity may be considered too simplistic and the cartographer may choose to build up a representation of the city using a mixture of point, line and area entities. Points may be used for the representation 'of features such as telephone boxes, areas for residential blocks and parks, and lines for road networks. Choosing the appropriate entity to represent real-world features is often difficult.


all spatial data are a generalization or simplification of real-world features. In some instances generalization is needed because data are required at a particular scale. In other cases generalization is introduced by the limitations of the technical procedures used to produce data. The grain size of photographic film, or the resolution of a remote sensing device, will determine the level of detail discernible in the resulting air photo or satellite image. Generalization may also be introduced directly by human intervention in order to improve the clarity of an image or to enhance its major theme.

all the data sources used in GIS - aerial photographs, satellite images, census data and particularly maps contain inherent generalization. This simplification of detail is necessary in order to maintain clarity...

Table of Contents


1. What is GIS.
2. Spatial Data.
3. Spatial Data Modeling.
4. Attribute Data Management
5. Data Input and Editing.
6. Data Analysis.
7. Analytical Modeling in GIS.
8. Output: From New Maps to Enhanced Decisions.


9. The Development of Computer Methods for Spatial Data.
10. Data Quality Issues.
11. Human and Organizational Issues.
12. GIS Project Design and Management.
13. The Future of GIS.

Customer Reviews

Most Helpful Customer Reviews

See All Customer Reviews