Note: Intro -- Fundamentals of Spatial Data Quality -- Table of Contents -- Foreword -- Introduction -- PART 1. Quality and Uncertainty: Introduction to the Problem -- Chapter 1. Development in the Treatment of Spatial Data Quality -- 1.1. Introduction -- 1.2. In the beginning -- 1.3. Changing the scene -- 1.3.1. Accuracy beyond position -- 1.3.2. Topology and logical consistency -- 1.3.3. Fitness for use -- 1.4. Elements of novelty -- 1.5. References -- Chapter 2. Spatial Data Quality: Concepts -- 2.1. Introduction -- 2.2. Sources and types of errors -- 2.3. Definitions of the concept of quality -- 2.3.1. Internal quality -- 2.3.2. External quality -- 2.4. Conclusion -- 2.5. References -- Chapter 3. Approaches to Uncertainty in Spatial Data -- 3.1. Introduction -- 3.2. The problem of definition -- 3.2.1. Examples of well-defined geographical objects -- 3.2.2. Examples of poorly defined geographical objects -- 3.3. Error -- 3.4. Vagueness -- 3.5. Ambiguity -- 3.5.1. Discord -- 3.5.2. Non-specificity -- 3.6. Data quality -- 3.7. Precision -- 3.8. Conclusion: uncertainty in practice -- 3.9. References -- PART 2. Academic Case Studies: Raster, Chloropleth and Land Use -- Chapter 4. Quality of Raster Data -- 4.1. Introduction -- 4.2. Geometry quality -- 4.2.1. Image reference system and modeling of the viewing geometry -- 4.2.1.1. Image reference system in matrix representation -- 4.2.1.2. Direct and inverse localization -- 4.2.1.3. Geometric transforms of images -- 4.2.1.4. Acquisition models -- 4.2.2. Definitions -- 4.2.2.1. Georeferenced image -- 4.2.2.2. Geocoded image -- 4.2.2.3. Orthorectified image -- 4.2.2.4. Check points -- 4.2.2.5. Tie points -- 4.2.2.6. Localization error -- 4.2.2.7. Mean quadratic error -- 4.2.2.8. Error vector field -- 4.2.2.9. Native projection of a map -- 4.2.3. Some geometry defects -- 4.2.3.1. Absolute localization defect. , 4.2.3.2. Global defects of internal geometry -- 4.2.3.3. Local defects of internal geometry -- 4.2.4. Localization control and global models -- 4.2.5. Internal geometry control -- 4.3. Radiometry quality -- 4.3.1. Radiometry quantities -- 4.3.2. Overview of the radiometric defects -- 4.3.2.1. Diffraction and defocalization -- 4.3.2.2. Polarization of the instrument -- 4.3.2.3. Stray light -- 4.3.2.4. Aerial photos -- 4.3.3. Calibration of the radiometric data -- 4.3.3.1. Radiometric calibration -- 4.3.3.2. Spectral calibration -- 4.3.4. Atmospheric correction -- 4.4. References -- Chapter 5. Understanding the Nature and Magnitude of Uncertainty in Geopolitical and Interpretive Choropleth Maps -- 5.1. Introduction -- 5.2. Uncertainty in geopolitical maps -- 5.2.1. Locational uncertainty in geopolitical maps -- 5.2.2. Attribute uncertainty in geopolitical maps -- 5.3. Uncertainty in interpretive maps -- 5.3.1. Construction of interpretive polygonal maps -- 5.3.2. Uncertainty in boundaries of interpretive polygonal maps -- 5.3.3. Uncertainty in attributes of interpretive polygonal maps -- 5.4. Interpretive map case studies -- 5.5. Conclusion -- 5.6. References -- Chapter 6. The Impact of Positional Accuracy on the Computation of Cost Functions -- 6.1. Introduction -- 6.2. Spatial data quality -- 6.2.1. Positional accuracy -- 6.2.2. The meta-model for spatial data quality -- 6.2.3. Error model -- 6.2.4. Error propagation -- 6.2.5. The variance-covariance equation -- 6.3. Application -- 6.3.1. Background -- 6.3.2. Results -- 6.4. Conclusions -- 6.5. References -- Chapter 7. Reasoning Methods for Handling Uncertain Information in Land Cover Mapping -- 7.1. Introduction -- 7.2. Uncertainty -- 7.3. Well-defined objects: error, probability, and Bayes -- 7.4. Poorly-defined objects: spatial extent, vagueness, and fuzzy-set theory. , 7.5. Poorly defined specification: ambiguity, discord, non-specificity and expert knowledge -- 7.5.1. Ambiguity -- 7.5.2. Using expert knowledge to reason with uncertainty -- 7.5.3. Formalisms for managing ambiguity -- 7.5.3.1. Discord, experts and Dempster-Shafer theory of evidence -- 7.5.3.2. Non-specificity, experts, and qualitative reasoning formalisms -- 7.6. Conclusion -- 7.7. References -- PART 3. Internal Quality of Vector Data: Production, Evaluation and Documentation -- Chapter 8. Vector Data Quality: A Data Provider's Perspective -- 8.1. Introduction -- 8.2. Providing vector geographical data -- 8.2.1. Data quality and usability -- 8.2.2. Aims of a national mapping agency -- 8.2.3. Vector geographical data -- 8.3. Data quality needs of the end user -- 8.3.1. Users' understanding of their needs -- 8.3.2. Data providers' understanding of user needs -- 8.4. Recognizing quality elements in vector data -- 8.4.1. Lineage -- 8.4.2. Currency -- 8.4.3. Positional accuracy -- 8.4.4. Attribute accuracy -- 8.4.5. Logical consistency -- 8.4.5.1. Connectivity in vector data -- 8.4.6. Completeness -- 8.5. Quality in the capture, storage, and supply of vector data -- 8.5.1. Overview of the data capture to supply process -- 8.5.1.1. Capture specifications -- 8.5.1.2. Quality control of vector data -- 8.5.1.3. Quality assurance of vector data -- 8.5.2. Quality in data capture -- 8.5.2.1. Field capture of vector data -- 8.5.2.2. Photogrammetric capture of vector data -- 8.5.2.3. External sources for vector data -- 8.5.3. Quality in the storage and post-capture processing of vector data -- 8.5.4. Quality in vector data product creation and supply -- 8.6. Communication of vector data quality information to the user -- 8.7. Conclusions and future directions -- 8.8. References. , Chapter 9. Spatial Integrity Constraints: A Tool for Improving the Internal Quality of Spatial Data -- 9.1. Introduction -- 9.2. Existing work -- 9.3. Topological relations and international geomatics standards -- 9.4. Definitions and concepts: the components of integrity constraints -- 9.4.1. Spatial operators -- 9.4.1.1. The extension tangent -- 9.4.1.2. The extension borders -- 9.4.1.3. The extension strict -- 9.4.2. Cardinality associated with predicates -- 9.4.3. Buffer -- 9.5. Documentation and use of integrity constraints -- 9.5.1. Documenting spatial integrity constraints -- 9.5.2. Validation of integrity constraints (inconsistency) -- 9.6. Production and validation of geographic data -- 9.6.1. Validating the spatial integrity of geographic data -- 9.6.2. Available tools -- 9.7. Conclusion -- 9.8. References -- Chapter 10. Quality Components, Standards, and Metadata -- 10.1. Introduction -- 10.2. Concepts of quality -- 10.2.1. Quality reference bases -- 10.2.2. Quality criteria -- 10.2.2.1. Qualitative criterion -- 10.2.2.2. Quantitative criterion -- 10.2.3. Expression of the quality -- 10.2.4. Precision and accuracy -- 10.2.5. Appraisal and use of quality -- 10.2.6. Meta-quality -- 10.3. Detailed description of quality criteria -- 10.3.1. Lineage -- 10.3.2. Positional accuracy or geometric accuracy -- 10.3.3. Attribute accuracy or semantic accuracy -- 10.3.4. Completeness -- 10.3.5. Logical consistency -- 10.3.6. Semantic consistency -- 10.3.7. Timeliness -- 10.3.8. Temporal consistency -- 10.3.9. Quality criteria: difficulties and limitations -- 10.4. Quality and metadata as seen by standards -- 10.4.1. Introduction to standardization -- 10.4.2. Background of geographic information standards -- 10.4.3. Standards relating to metadata and quality -- 10.4.4. Theoretical analysis of ISO/TC 211 standards -- 10.4.4.1. The ISO 19113 standard. , 10.4.4.2. The ISO 19114 standard -- 10.4.4.3. The ISO 19115 standard -- 10.4.4.4. ISO 19138 preliminary draft technical specification -- 10.4.5. Standardized implementation of metadata and quality -- 10.4.5.1. Preamble -- 10.4.5.2. The model for exchange by transmission -- 10.4.5.3. Data transfer -- 10.4.5.4. Metadata of geographic objects -- 10.5. Conclusion -- 10.6. References -- PART 4. External Quality: Communication and Usage -- Chapter 11. Spatial Data Quality Assessment and Documentation -- 11.1. Introduction -- 11.1.1. Quality in its context -- 11.1.2. Outline of chapter -- 11.2. Denotation as a radical quality aspect of geographical data -- 11.3. Sources for the fluctuations in denotation -- 11.3.1. The modeling of the world -- 11.3.2. The modeling of operations -- 11.3.3. Realization of the model of operations -- 11.3.4. Realization of the model of the world -- 11.3.5. Synthesis -- 11.4. How to express denotation quality -- 11.4.1. General principles for the assessment of denotation quality -- 11.4.1.1. Comparison -- 11.4.1.2. Measure for measure -- 11.4.1.3. Statistics -- 11.4.1.4. Validity intervals -- 11.4.1.5. Reporting -- 11.4.2. Toward a few measures -- 11.4.3. Geometry measures -- 11.4.3.1. Punctual objects -- 11.4.3.2. Linear objects -- 11.4.3.3. Surface objects -- 11.4.3.4. Topology -- 11.4.4. Time measures -- 11.4.4.1. Dates -- 11.4.4.2. Chronology -- 11.4.5. Value measures -- 11.4.5.1. Semantics -- 11.4.5.2. Semiology -- 11.4.6. Indirect measures -- 11.4.7. Measures on modeling -- 11.5. Conclusion -- 11.6. References -- Chapter 12. Communication and Use of Spatial Data Quality Information in GIS -- 12.1. Introduction -- 12.2. Data quality information management -- 12.3. Communication of data quality information -- 12.3.1. Metadata -- 12.3.2. Data quality visualization -- 12.4. Use of quality information. , 12.4.1. Warnings and illogical operators.