GIS Fundamentals

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.

IntroductionHow Computers Solve ProblemsHow Computers Represent the World: Data ModellingThe Structure of a ComputerPseudocode and Computer ProgrammingFurther ReadingDatabasesWhat Are Databases and Why Are They Important?Relational DatabaseStoring Spatial Data in a Relational DatabaseSolutions to the Problems of Storing Spatial Data in RDBMSFurther ReadingVector Data StructuresSimple Storage of Vector DataTopological Storage of Vector DataSo What Is Topology?And How Does It Help? The Example of DIMEMore on Topological Data StructuresAnd a Return to Simple Data StructuresFurther ReadingVector Algorithms for LinesSimple Line Intersection AlgorithmWhy the Simple Line Intersection Algorithm Would Not Work: A Better AlgorithmDealing with Wiggly LinesCalculations on Lines: How Long Is a Piece of String?Line Intersection: How It Is Really DoneFurther ReadingVector Algorithms for AreasCalculations on Areas: Single PolygonsCalculations on Areas: Multiple PolygonsPoint in Polygon: Simple Algorithm… and Back to Topology for a Better AlgorithmFurther ReadingThe Efficiency of AlgorithmsHow Is Algorithm Efficiency Measured?Efficiency of the Line Intersection AlgorithmMore on Algorithm EfficiencyFurther ReadingRaster Data StructuresRaster Data in DatabasesRaster Data Structures: The ArraySaving Space: Run Length Encoding and QuadtreesData Structures for ImagesFurther ReadingRaster AlgorithmsRaster Algorithms: Attribute Query for RunLength Encoded DataRaster Algorithms: Attribute Query for QuadtreesRaster Algorithms: Area CalculationsFurther ReadingData Structures for SurfacesData Models for SurfacesAlgorithms for Creating Grid Surface ModelsAlgorithms for Creating a Triangulated Irregular NetworkGrid Creation RevisitedFurther ReadingAlgorithms for SurfacesElevation, Slope and AspectHydrological Analysis Using a TINDetermining Flow Direction Using a Gridded DEMUsing the Flow Directions for Hydrological AnalysisFurther ReadingData Structures and Algorithms for NetworksNetworks in Vector and RasterShortest Path AlgorithmData Structures for Network DataFaster Algorithms for Finding the Shortest RouteFurther ReadingStrategies for Efficient Data AccessTree Data StructuresIndexing and Storing D Data Using Both CoordinatesSpace-Filling Curves for Spatial DataSpatial Filling Curves and Data ClusteringSpace-Filling Curves for Indexing Spatial DataCachingFurther ReadingHeuristics for Spatial DataTravelling Salesman ProblemLocation AllocationMetaheuristicsComputability and DecidabilityFurther ReadingConclusionGlossaryReferencesIndex

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.