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  • Formaat: 338 pages
  • Ilmumisaeg: 03-Sep-2018
  • Kirjastus: CRC Press Inc
  • ISBN-13: 9781498785655

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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 how 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 InternetChapters on databases and on searching large databases for spatial queriesImproved coverage on route-findingImproved coverage of heuristic approaches to solving real-world spatial problems International standards for spatial dataThe 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.

Arvustused

"Steve Wise has produced a book that is a marvelous complement to GIS courses, taking the reader on an excursion back to the fundamentals of spatial representation. Vectors, rasters, surfaces and networks are explained in depth and enrich the study of GIS to the point where students can progress their knowledge of the field to practical and professional applications." Michael Batty, Centre for Advanced Spatial Analysis, University College London, UK

"After having had the pleasure of being reviewer of the first edition of the book, it is great to see the success continued in the second version. Given the transition from stand-alone GIS to a crucial component in the information infrastructure of todays society, the extended coverage of data management in the new version is an important improvement. the book gives clear insight into the Geo-ICT machinery to a much wider audience than just computer scientists." Peter van Oosterom, Delft University of Technology, South Holland, Netherlands

Clearly and engagingly written, and importantly free from unnecessary jargon, this text provides a helpful and well-considered overview of the inside workings of GIS. This is a book for students and other GI users wishing to develop more than just good software skills by strengthening their knowledge and understanding of the science and technology that underpins GIS. Graham Smith, UNIGIS UK, Manchester Metropolitan University

Preface ix
Acknowledgements xiii
Author xv
1 Introduction
1(22)
1.1 How Computers Solve Problems
2(3)
1.2 How Computers Represent the World: Data Modelling
5(5)
1.3 The Structure of a Computer
10(5)
1.4 Pseudocode and Computer Programming
15(8)
Further Reading
21(2)
2 Databases
23(16)
2.1 What Are Databases and Why Are They Important?
23(6)
2.2 Relational Database
29(3)
2.3 Storing Spatial Data in a Relational Database
32(3)
2.4 Solutions to the Problems of Storing Spatial Data in RDBMS
35(4)
Further Reading
37(2)
3 Vector Data Structures
39(30)
3.1 Simple Storage of Vector Data
39(10)
3.2 Topological Storage of Vector Data
49(5)
3.3 So What Is Topology?
54(3)
3.4 And How Does It Help? The Example of DIME
57(3)
3.5 More on Topological Data Structures
60(4)
3.6 And a Return to Simple Data Structures
64(5)
Further Reading
67(2)
4 Vector Algorithms for Lines
69(26)
4.1 Simple Line Intersection Algorithm
69(5)
4.2 Why the Simple Line Intersection Algorithm Would Not Work: A Better Algorithm
74(4)
4.3 Dealing with Wiggly Lines
78(3)
4.4 Calculations on Lines: How Long Is a Piece of String?
81(3)
4.5 Line Intersection: How It Is Really Done
84(11)
Further Reading
93(2)
5 Vector Algorithms for Areas
95(14)
5.1 Calculations on Areas: Single Polygons
95(3)
5.2 Calculations on Areas: Multiple Polygons
98(3)
5.3 Point in Polygon: Simple Algorithm
101(4)
5.4 ... and Back to Topology for a Better Algorithm
105(4)
Further Reading
108(1)
6 The Efficiency of Algorithms
109(10)
6.1 How Is Algorithm Efficiency Measured?
109(3)
6.2 Efficiency of the Line Intersection Algorithm
112(2)
6.3 More on Algorithm Efficiency
114(5)
Further Reading
116(3)
7 Raster Data Structures
119(22)
7.1 Raster Data in Databases
120(3)
7.2 Raster Data Structures: The Array
123(4)
7.3 Saving Space: Run Length Encoding and Quadtrees
127(5)
7.4 Data Structures for Images
132(9)
Further Reading
139(2)
8 Raster Algorithms
141(20)
8.1 Raster Algorithms: Attribute Query for Run Length Encoded Data
141(3)
8.2 Raster Algorithms: Attribute Query for Quadtrees
144(9)
8.3 Raster Algorithms: Area Calculations
153(8)
Further Reading
159(2)
9 Data Structures for Surfaces
161(24)
9.1 Data Models for Surfaces
162(4)
9.2 Algorithms for Creating Grid Surface Models
166(8)
9.3 Algorithms for Creating a Triangulated Irregular Network
174(6)
9.4 Grid Creation Revisited
180(5)
Further Reading
183(2)
10 Algorithms for Surfaces
185(22)
10.1 Elevation, Slope and Aspect
185(7)
10.2 Hydrological Analysis Using a TIN
192(3)
10.3 Determining Flow Direction Using a Gridded DEM
195(4)
10.4 Using the Flow Directions for Hydrological Analysis
199(8)
Further Reading
205(2)
11 Data Structures and Algorithms for Networks
207(28)
11.1 Networks in Vector and Raster
207(2)
11.2 Shortest Path Algorithm
209(7)
11.3 Data Structures for Network Data
216(9)
11.4 Faster Algorithms for Finding the Shortest Route
225(10)
Further Reading
234(1)
12 Strategies for Efficient Data Access
235(36)
12.1 Tree Data Structures
238(6)
12.2 Indexing and Storing 2D Data Using Both Coordinates
244(6)
12.3 Space-Filling Curves for Spatial Data
250(2)
12.4 Spatial Filling Curves and Data Clustering
252(3)
12.5 Space-Filling Curves for Indexing Spatial Data
255(10)
12.6 Caching
265(6)
Further Reading
269(2)
13 Heuristics for Spatial Data
271(24)
13.1 Travelling Salesman Problem
272(5)
13.2 Location Allocation
277(6)
13.3 Metaheuristics
283(5)
13.4 Computability and Decidability
288(7)
Further Reading
293(2)
Conclusion 295(2)
Glossary 297(8)
References 305(8)
Index 313
Stephen Mark Wise is a senior lecturer in the Department of Geography at the University of Sheffield, UK. His teaching and research is mostly concerned with GIS.