Book description
With GIS technology increasingly available to a wider audience on devices from apps on smartphones to satnavs in cars, many people routinely use spatial data in a way which used to be the preserve of GIS specialists. However spatial data is stored and analyzed on a computer still tends to be described in academic texts and articles which require specialist knowledge or some training in computer science. Developed to introduce computer science literature to geography students, GIS Fundamentals, Second Edition provides an accessible examination of the underlying principles for anyone with no formal training in computer science.
See What’s New in the Second Edition:
- Coverage of the use of spatial data on the Internet
- Chapters on databases and on searching large databases for spatial queries
- Improved coverage on route-finding
- Improved coverage of heuristic approaches to solving real-world spatial problems
- International standards for spatial data
The book begins with a brief but detailed introduction to how computers work and how they are programmed, giving anyone with no previous computer science background a foundation to understand the remainder of the book. As with all parts of the book there are also suggestions for further sources of reading. The book then describes the ways in which vector and raster data can be stored and how algorithms are designed to perform fundamental operations such as detecting where lines intersect. From these simple beginnings the book moves into the more complex structures used for handling surfaces and networks and contains a detailed account of what it takes to determine the shortest route between two places on a network. The final sections of the book review problems, such as the "Travelling Salesman" problem, which are so complex that it is not known whether an optimum solution exists.
Using clear, concise language, but without sacrificing technical rigour, the book gives readers an understanding of what it takes to produce systems which allow them to find out where to make their next purchase and how to drive to the right place to collect it.
Table of contents
- Preliminaries
- Preface
- Acknowledgements
- Author
- Chapter 1 Introduction
- Chapter 2 Databases
-
Chapter 3 Vector Data Structures
- 3.1 Simple Storage of Vector Data
- 3.2 Topological Storage of Vector Data
- 3.3 So What Is Topology?
- 3.4 And How Does It Help? The Example of DIME
- 3.5 More on Topological Data Structures
- 3.6 And a Return to Simple Data Structures
- Further Reading
-
- Figure 3.1
- Figure 3.2
- Figure 3.3
- Figure 3.4
- Figure 3.5
- Figure 3.6
- Figure 3.7
- Figure 3.8
- Figure 3.9
- Figure 3.10
- Figure 3.11
- Figure 3.12
- Figure 3.13
- Figure 3.14
- Figure 3.15
- Figure 3.16
- Figure 3.17
- Figure 3.18
- Figure 3.19
- Figure 3.20
- Figure 3.21
- Figure 3.22
- Figure 3.23
- Figure 3.24
- Figure 3.25
- Figure 3.26
- Figure 3.27
- Figure 3.28
- Figure 3.29
- Figure 3.30
- Figure 3.31
- Chapter 4 Vector Algorithms for Lines
- Chapter 5 Vector Algorithms for Areas
- Chapter 6 The Efficiency of Algorithms
- Chapter 7 Raster Data Structures
- Chapter 8 Raster Algorithms
- Chapter 9 Data Structures for Surfaces
- Chapter 10 Algorithms for Surfaces
-
Chapter 11 Data Structures and Algorithms for Networks
- 11.1 Networks in Vector and Raster
- 11.2 Shortest Path Algorithm
- 11.3 Data Structures for Network Data
- 11.4 Faster Algorithms for Finding the Shortest Route
- Further Reading
-
- Figure 11.1
- Figure 11.2
- Figure 11.3
- Figure 11.4
- Figure 11.5
- Figure 11.6
- Figure 11.7
- Figure 11.8
- Figure 11.9
- Figure 11.10
- Figure 11.11
- Figure 11.12
- Figure 11.13
- Figure 11.14
- Figure 11.15
- Figure 11.16
- Figure 11.17
- Figure 11.18
- Figure 11.19
- Figure 11.20
- Figure 11.21
- Figure 11.22
- Figure 11.23
- Figure 11.24
- Figure 11.25
- Figure 11.26
- Figure 11.27
-
Chapter 12 Strategies for Efficient Data Access
- 12.1 Tree Data Structures
- 12.2 Indexing and Storing 2D Data Using Both Coordinates
- 12.3 Space-Filling Curves for Spatial Data
- 12.4 Spatial Filling Curves and Data Clustering
- 12.5 Space-Filling Curves for Indexing Spatial Data
- 12.6 Caching
- Further Reading
-
- Figure 12.1
- Figure 12.2
- Figure 12.3
- Figure 12.4
- Figure 12.5
- Figure 12.6
- Figure 12.7
- Figure 12.8
- Figure 12.9
- Figure 12.10
- Figure 12.11
- Figure 12.12
- Figure 12.13
- Figure 12.14
- Figure 12.15
- Figure 12.16
- Figure 12.17
- Figure 12.18
- Figure 12.19
- Figure 12.20
- Figure 12.21
- Figure 12.22
- Figure 12.23
- Figure 12.24
- Figure 12.25
- Figure 12.26
- Figure 12.27
- Chapter 13 Heuristics for Spatial Data
- Conclusion
- Glossary
- References
Product information
- Title: GIS Fundamentals, 2nd Edition
- Author(s):
- Release date: September 2018
- Publisher(s): CRC Press
- ISBN: 9781315360607
You might also like
book
Practical Statistics for Data Scientists, 2nd Edition
Statistical methods are a key part of data science, yet few data scientists have formal statistical …
book
Python Data Science Handbook, 2nd Edition
Python is a first-class tool for many researchers, primarily because of its libraries for storing, manipulating, …
book
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition
Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. …
book
Generative Deep Learning, 2nd Edition
Generative AI is the hottest topic in tech. This practical book teaches machine learning engineers and …