Intelligent positioning - GIS-GPS unification GIS-GPS Unification

GIS and GPS integration is happening in research and commercial activities worldwide, however this is the first GIS-GPS integration book to look at applications that combine GIS and GPS to provide one solution. It begins by providing readers with technical overviews of GPS and GIS and their integration, and then focuses on a selection of R&D activities in applications ranging from intelligent transport systems to real time location based tourist information systems. Provides overview chapters on GIS, GPS and GIS-GPS integration for readers who are less familiar with either system Based on the authors own research and development activities in both the UK and the US Includes case studies in each chapter to illustrate the end-product/commercial activities that research can lead to

1 Introduction. 1.1 Do you really know where you are? 1.2 How active is your map? 1.3 Levels of GPS-GIS integration. 2 GIS: An Overview. 2.1 Introduction. 2.2 GIS. 2.3 Functionality. 2.4 Fundamental concepts. 2.5 Spatial and geographical data. 2.6 Spatial data modelling. 2.7 Spatial data visualisation. 2.8 GIS and the internet. 2.9 The application of GIS. 2.10 Conclusions. 3 GPS: An Introduction. 3.1 GPS description. 3.2 The Pseudorange Observable. 3.3 Point positioning using pseudorange. 3.4 The Carrier Phase Observable. 3.5 Relative positioning using carrier phase. 3.6 Introducing high precision GPS geodesy. 3.7 Conclusions. 4 Datum Transformations and Projections. 4.1 Integration requirements. 4.2 Global reference systems. 4.3 Regional reference system. 4.4 Conclusions. 5 Commercial Applications That Integrate GIS and GPS. 5.1 Introduction. 5.2 National GIS/GPS integration team. 5.3 GIS and GPS deformation monitoring. 5.4 Location Bases Services. 5.5 Intelligent transport systems. 5.6 Accessible rural public transport (Case Study). 5.7 Realtime passenger information and bus priority system. 5.8 Precision farming. 5.9 Conclusions. 6 GPS-GIS Map Matching: Combined Positioning Solution. 6.1 Introduction. 6.2 Map matching methodologies. 6.3 Road Reduction Filter (RRF) map matching algorithm. 6.4 Testing VDGPS. 6.5 Conclusions. 7 Intelligent Map Matching Using (MDOP). 7.1 Introduction. 7.2 Least squares estimation of position error vector. 7.3 Quantifying road geometry: Mapping Dilution of Precision (MDOP). 7.4 MDOP for basic road shapes. 7.5 Testing MDOP. 7.6 RRF map matching enhancement. 7.7 Conclusions. 8 The Use of Digital Terrain Models to Augment GPS Vehicle Navigation. 8.1 Introduction. 8.2 Digital terrain models. 8.3 Spatial interpolation of elevation data. 8.4 Map matching and the Road Reduction Filter. 8.5 Data collection and processing. 8.6 Results. 8.7 Results from test2 data with a subset of satellites. 8.8 Conclusions. 9 GPS Accuracy Estimation Using Map Matching Techniques: Applied to Vehicle Positioning and Odometer Calibration. 9.1 Introduction. 9.2 Methodology. 9.3 Map matching. 9.4 Distance correction factor. 9.5 Estimating C. 9.6 Calibration if GPS data recently online. 9.7 Putting it all together. 9.8 Alterations to the correction factor algorithm. 9.9 Height aiding. 9.10 Implementation. 9.11 Data processing and results. 9.12 Conclusions. 9.13 Outline of algorithms. Index.

George Taylor is the author of Intelligent Positioning: GIS-GPS Unification, published by Wiley.

Geoff Blewitt is the author of Intelligent Positioning: GIS-GPS Unification, published by Wiley.