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GIS, Environmental Modeling and Engineering, Second Edition
ISBN: 9781439808702 | 1439808708
Edition: 2ndFormat: Hardcover
Publisher: CRC Press
Pub. Date: 12/23/2009
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The first edition GIS, Environmental Modeling and Engineering broke new ground by linking GIS, environmental simulation, and engineering solutions. Building on this tradition, the second edition keeps the format and tone that made the first edition a bestseller while updating the content to include a diversity of case studies, better coverage of tool integration, and in-depth treatment of current issues.
| Acknowledgments | p. ix |
| The Author | p. xi |
| Abbreviations | p. xiii |
| Statement on Trade Names and Trademarks | p. xv |
| Introduction | p. 1 |
| Metaphors of Nature | p. 2 |
| A Solution Space? | p. 4 |
| Scope and Plan of This Book | p. 5 |
| From GIS to Geocomputation | p. 11 |
| In the Beginning12 | |
| ... MORE | p. 14 |
| Representing Spatial Phenomena in GIS | p. 19 |
| Putting the Real World onto Media | p. 24 |
| Vector | p. 26 |
| Tessellations | p. 28 |
| Object-Oriented | p. 31 |
| Data Characteristics | p. 32 |
| Data Collection Technologies | p. 37 |
| GPS and Inertial Navigation Systems | p. 38 |
| Remote Sensing | p. 39 |
| Ground Survey | p. 41 |
| Nontraditional Approaches to Data Collection | p. 42 |
| Basic Functionality of GIS | p. 42 |
| A Systems Definition of GIS | p. 44 |
| Limitations of GIS and the Rise of Geocomputation and Geosimulation | p. 46 |
| GIScience and the Rise of Geo-Information Engineering | p. 49 |
| Technology First | p. 49 |
| Science to Follow | p. 52 |
| And Now ... Geo-Information Engineering | p. 59 |
| Approaches to Modeling | p. 63 |
| Model of an x | p. 64 |
| Typology of Models | p. 66 |
| Building Models | p. 69 |
| Modeling Landslides | p. 70 |
| Modeling Topography | p. 75 |
| Spatio-Temporal Dimensions and the Occam-Einstein Dimension | p. 77 |
| Evaluating Models | p. 81 |
| Applying Models | p. 83 |
| A Summary of Model Development | p. 87 |
| The Role and Nature of Environmental Models | p. 91 |
| Context of Environmental Modeling | p. 92 |
| Environmental Impact Assessment | p. 94 |
| An Integrated Approach | p. 97 |
| Sustainable Development | p. 99 |
| Hazard, Vulnerability, and Risk | p. 101 |
| Decision Environment | p. 105 |
| Conceptual Models | p. 107 |
| Empirical Models | p. 110 |
| Models Incorporating Artificial Intelligence | p. 117 |
| Knowledge-Based Systems | p. 117 |
| Heuristics | p. 118 |
| Artificial Neural Networks | p. 119 |
| Agent-Based Models | p. 121 |
| Process Models | p. 124 |
| Lumped Parameter Models | p. 126 |
| Distributed Parameter Models | p. 131 |
| Discretization | p. 131 |
| Routing across a Digital Elevation Model | p. 132 |
| Transport through a Medium | p. 134 |
| Case Studies in GIS, Environmental Modeling, and Engineering | p. 147 |
| Modeling Approaches in GIS and Environmental Modeling | p. 147 |
| Spatial Coexistence | p. 150 |
| Source-Pathway Characterization | p. 157 |
| Basin Management Planning | p. 158 |
| Coastal Oil Spill Modeling | p. 169 |
| Cluster Detection | p. 172 |
| àand Don't Forget the Web | p. 182 |
| Issues of Coupling the Technologies | p. 185 |
| Some Preconditions | p. 186 |
| Initial Conceptualizations | p. 189 |
| Independent | p. 190 |
| Loosely Coupled | p. 190 |
| Tightly Coupled | p. 191 |
| Embedded | p. 191 |
| An Over-Simplification of the Issues | p. 192 |
| Maturing Conceptualizations | p. 197 |
| Integration versus Interoperability | p. 198 |
| Environmental Modeling within-GIS | p. 201 |
| Model Management | p. 203 |
| Maturing Typology of Integration | p. 207 |
| One-Way Data Transfer | p. 207 |
| Loose Coupling | p. 207 |
| Shared Coupling | p. 209 |
| Joined Coupling | p. 209 |
| Tool Coupling | p. 209 |
| De facto Practices | p. 210 |
| Data and Information Quality Issues | p. 213 |
| The Issue Is ... Uncertainty | p. 213 |
| Early Warnings | p. 217 |
| So, How Come...? | p. 219 |
| Imperfect Measurement | p. 219 |
| Digital Representation of Phenomena | p. 220 |
| Natural Variation | p. 221 |
| Subjective Judgment and Context | p. 223 |
| Semantic Confusion | p. 224 |
| Finding a Way Forward | p. 224 |
| Measuring Spatial Data Quality | p. 226 |
| Modeling Error and Uncertainty in GIS | p. 231 |
| Topological Overlay | p. 231 |
| Interpolation | p. 236 |
| Kriging | p. 238 |
| Fuzzy Concepts in GIS | p. 242 |
| Theory of Fuzzy Sets | p. 243 |
| Example of Fuzzy Sets in GIS | p. 244 |
| Sensitivity Analysis | p. 256 |
| Managing Fitness-for-Use | p. 259 |
| Modeling Issues | p. 263 |
| Issues of Scale | p. 264 |
| Issues of Algorithm | p. 277 |
| Issues of Model Structure | p. 285 |
| Issues of Calibration | p. 288 |
| Bringing Data Issues and Modeling Issues Together | p. 293 |
| Decision Making under Uncertainty | p. 297 |
| Exploring the Decision Space: Spatial Decision Support Systems | p. 299 |
| Communication of Spatial Concepts | p. 304 |
| Participatory Planning and the Web-Based GIS | p. 307 |
| All's Well That Ends Well? | p. 311 |
| References | p. 315 |
| Index | p. 341 |
| Table of Contents provided by Ingram. All Rights Reserved. |
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