Economics / Daniel R. Fusfeld

• Record Nr.: UNISA990002175210203316
• Autore: FUSFELD, Daniel Roland
• Pubbl/distr/stampa: Lexington, Mass. : B. C. Heath and Co., 1972
• Descrizione fisica: XVI, 536 p. : ill. ; 25 cm
• Collocazione: 330 FUS 1 (IEP VIII 559)
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia

Fundamentals of spatial data quality [[electronic resource] /] / edited by Rodolphe Devillers, Robert Jeansoulin

• Record Nr.: UNISA996200193903316
• Pubbl/distr/stampa: London ; ; Newport Beach, CA, : ISTE, c2006
• ISBN: 1-280-60349-6; 9786610603497; 1-84704-506-5; 0-470-61215-0; 0-470-39481-1; 1-84704-606-1
• Descrizione fisica: 1 online resource (311 p.)
• Collana: Geographical information systems series
• Altri autori (Persone): DevillersRodolphe; JeansoulinRobert
• Disciplina: 526.0285
• Soggetti: Geographic information systems - Data processing - Quality control
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: "Part of this book adapted from "Qualite de l'information geographique" published in France by Hermes Science/Lavoisier in 2005."
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: 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 quality2.4. 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 geometry4.2.1.1. 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 geometry4.2.3.3. 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 Maps5.1. 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
• Sommario/riassunto: This book explains the concept of spatial data quality, a key theory for minimizing the risks of data misuse in a specific decision-making context. Drawing together chapters written by authors who are specialists in their particular field, it provides both the data producer and the data user perspectives on how to evaluate the quality of vector or raster data which are both produced and used. It also covers the key concepts in this field, such as: how to describe the quality of vector or raster data; how to enhance this quality; how to evaluate and document it, using methods such as metadata