Fundamentals of Spatial Data Quality,9781905209569

Fundamentals of Spatial Data Quality

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Edition: 1st
ISBN13: 9781905209569
ISBN10: 1905209568
Format: Hardcover
Pub. Date: 2006-05-05
Publisher(s): Wiley-ISTE
List Price: $189.81

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Summary

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; how to communicate it to users; and how to relate it with the decision-making process. Also included is a Foreword written by Professor Michael F. Goodchild.

Author Biography

Rodolphe Devillers is an assistant professor at Memorial University of Newfoundland. He is a member of the Centre for Research in Geomatics and the Canadian Network of Excellence. Robert Jeansoulin is a senior researcher at the Centre National de la Recherche Scientifique and works for the Centre of Mathematics and Computer Sciences at the UniversitT de Provence.

Table of Contents

Foreword 13(4)
Professor Michael F. GOODCHILD
Introduction 17(4)
Rodolphe DEVILLERS and Robert JEANSOULIN
PART 1. Quality and Uncertainty: Introduction to the Problem
Chapter 1. Development in the Treatment of Spatial Data Quality
21(10)
Nicholas CHRISMAN
1.1. Introduction
21(1)
1.2. In the beginning
22(1)
1.3. Changing the scene
23(3)
1.3.1. Accuracy beyond position
23(1)
1.3.2. Topology and logical consistency
24(1)
1.3.3. Fitness for use
24(2)
1.4. Elements of novelty
26(3)
1.5. References
29(2)
Chapter 2. Spatial Data Quality: Concepts
31(12)
Rodolphe DEVILLERS and Robert JEANSOULIN
2.1. Introduction
31(3)
2.2. Sources and types of errors
34(1)
2.3. Definitions of the concept of quality
35(6)
2.3.1. Internal quality
37(2)
2.3.2. External quality
39(2)
2.4. Conclusion
41(1)
2.5. References
41(2)
Chapter 3. Approaches to Uncertainty in Spatial Data
43(18)
Peter FISHER, Alexis COMBER and Richard WADSWORTH
3.1. Introduction
43(2)
3.2. The problem of definition
45(3)
3.2.1. Examples of well-defined geographical objects
46(1)
3.2.2. Examples of poorly defined geographical objects
47(1)
3.3. Error
48(2)
3.4. Vagueness
50(1)
3.5. Ambiguity
51(3)
3.5.1. Discord
52(2)
3.5.2. Non-specificity
54(1)
3.6. Data quality
54(1)
3.7. Precision
55(1)
3.8. Conclusion: uncertainty in practice
56(1)
3.9. References
56(5)
PART 2. Academic Case Studies: Raster, Chloropleth and Land Use
Chapter 4. Quality of Raster Data
61(28)
Serge RIAZANOFF and Richard SANTER
4.1. Introduction
61(1)
4.2. Geometry quality
62(19)
4.2.1. Image reference system and modeling of the viewing geometry
63(1)
4.2.1.1. Image reference system in matrix representation
63(1)
4.2.1.2. Direct and inverse localization
64(1)
4.2.1.3. Geometric transforms of images
65(1)
4.2.1.4. Acquisition models
66(2)
4.2.2. Definitions
68(1)
4.2.2.1. Georeferenced image
68(1)
4.2.2.2. Geocoded image
69(1)
4.2.2.3. Orthorectified image
69(1)
4.2.2.4. Check points
69(1)
4.2.2.5. Tie points
70(1)
4.2.2.6. Localization error
71(1)
4.2.2.7. Mean quadratic error
71(1)
4.2.2.8. Error vector field
71(1)
4.2.2.9. Native projection of a map
72(1)
4.2.3. Some geometry defects
73(1)
4.2.3.1. Absolute localization defect
73(1)
4.2.3.2. Global defects of internal geometry
73(1)
4.2.3.3. Local defects of internal geometry
75(4)
4.2.4. Localization control and global models
79(1)
4.2.5. Internal geometry control
79(2)
4.3. Radiometry quality
81(6)
4.3.1. Radiometry quantities
81(1)
4.3.2. Overview of the radiometric defects
82(1)
4.3.2.1. Diffraction and defocalization
83(1)
4.3.2.2. Polarization of the instrument
83(1)
4.3.2.3. Stray light
83(1)
4.3.2.4. Aerial photos
83(1)
4.3.3. Calibration of the radiometric data
84(1)
4.3.3.1. Radiometric calibration
84(1)
4.3.3.2. Spectral calibration
85(1)
4.3.4. Atmospheric correction
86(1)
4.4. References
87(2)
Chapter 5. Understanding the Nature and Magnitude of Uncertainty in Geopolitical and Interpretive Choropleth Maps
89(18)
Kim LOWELL
5.1. Introduction
89(2)
5.2. Uncertainty in geopolitical maps
91(3)
5.2.1. Locational uncertainty in geopolitical maps
91(2)
5.2.2. Attribute uncertainty in geopolitical maps
93(1)
5.3. Uncertainty in interpretive maps
94(6)
5.3.1. Construction of interpretive polygonal maps
94(2)
5.3.2. Uncertainty in boundaries of interpretive polygonal maps
96(2)
5.3.3. Uncertainty in attributes of interpretive polygonal maps
98(2)
5.4. Interpretive map case studies
100(3)
5.5. Conclusion
103(1)
5.6. References
104(3)
Chapter 6. The Impact of Positional Accuracy on the Computation of Cost Functions
107(16)
Alfred STEIN and Pepijn VAN OORT
6.1. Introduction
107(1)
6.2. Spatial data quality
108(7)
6.2.1. Positional accuracy
109(1)
6.2.2. The meta-model for spatial data quality
110(1)
6.2.3. Error model
110(1)
6.2.4. Error propagation
111(2)
6.2.5. The variance-covariance equation
113(2)
6.3. Application
115(5)
6.3.1. Background
115(3)
6.3.2. Results
118(2)
6.4. Conclusions
120(1)
6.5. References
121(2)
Chapter 7. Reasoning Methods for Handling Uncertain Information in Land Cover Mapping
123(18)
Alexis COMBER, Richard WADSWORTH and Peter FISHER
7.1. Introduction
123(1)
7.2. Uncertainty
124(1)
7.3. Well-defined objects: error, probability, and Bayes
125(2)
7.4. Poorly-defined objects: spatial extent, vagueness, and fuzzy-set theory
127(3)
7.5. Poorly defined specification: ambiguity, discord, non-specificity and expert knowledge
130(7)
7.5.1. Ambiguity
130(1)
7.5.2. Using expert knowledge to reason with uncertainty
130(1)
7.5.3. Formalisms for managing ambiguity
131(1)
7.5.3.1. Discord, experts and Dempster-Shafer theory of evidence
131(1)
7.5.3.2. Non-specificity, experts, and qualitative reasoning formalisms
134(3)
7.6. Conclusion
137(1)
7.7. References
138(3)
PART 3. Internal Quality of Vector Data: Production, Evaluation and Documentation
Chapter 8. Vector Data Quality: A Data Provider's Perspective
141(20)
Jenny HARDING
8.1. Introduction
141(1)
8.2. Providing vector geographical data
142(1)
8.2.1. Data quality and usability
142(1)
8.2.2. Aims of a national mapping agency
142(1)
8.2.3. Vector geographical data
143(1)
8.3. Data quality needs of the end user
143(2)
8.3.1. Users' understanding of their needs
143(1)
8.3.2. Data providers' understanding of user needs
144(1)
8.4. Recognizing quality elements in vector data
145(6)
8.4.1. Lineage
145(1)
8.4.2. Currency
146(1)
8.4.3. Positional accuracy
147(2)
8.4.4. Attribute accuracy
149(1)
8.4.5. Logical consistency
149(1)
8.4.5.1. Connectivity in vector data
149(1)
8.4.6. Completeness
150(1)
8.5. Quality in the capture, storage, and supply of vector data
151(5)
8.5.1. Overview of the data capture to supply process
151(1)
8.5.1.1. Capture specifications
152(1)
8.5.1.2. Quality control of vector data
152(1)
8.5.1.3. Quality assurance of vector data
152(1)
8.5.2. Quality in data capture
153(1)
8.5.2.1. Field capture of vector data
153(1)
8.5.2.2. Photogrammetric capture of vector data
154(1)
8.5.2.3. External sources for vector data
154(1)
8.5.3. Quality in the storage and post-capture processing of vector data
155(1)
8.5.4. Quality in vector data product creation and supply
155(1)
8.6. Communication of vector data quality information to the user
156(1)
8.7. Conclusions and future directions
157(1)
8.8. References
158(3)
Chapter 9. Spatial Integrity Constraints: A Tool for Improving the Internal Quality of Spatial Data
161(18)
Sylvain VALLIERES, Jean BRODEUR and Daniel PILON
9.1. Introduction
161(2)
9.2. Existing work
163(3)
9.3. Topological relations and international geomatics standards
166(2)
9.4. Definitions and concepts: the components of integrity constraints
168(5)
9.4.1. Spatial operators
168(1)
9.4.1.1. The extension tangent
169(1)
9.4.1.2. The extension borders
169(1)
9.4.1.3. The extension strict
170(1)
9.4.2. Cardinality associated with predicates
171(1)
9.4.3. Buffer
171(2)
9.5. Documentation and use of integrity constraints
173(2)
9.5.1. Documenting spatial integrity constraints
173(1)
9.5.2. Validation of integrity constraints (inconsistency)
174(1)
9.6. Production and validation of geographic data
175(1)
9.6.1. Validating the spatial integrity of geographic data
175(1)
9.6.2. Available tools
176(1)
9.7. Conclusion
176(1)
9.8. References
177(2)
Chapter 10. Quality Components, Standards, and Metadata
179(32)
Sylvie SERVIGNE, Nicolas LESAGE and Thérèse LIBOUREL
10.1. Introduction
179(2)
10.2. Concepts of quality
181(5)
10.2.1. Quality reference bases
181(1)
10.2.2. Quality criteria
181(1)
10.2.2.1. Qualitative criterion
182(1)
10.2.2.2. Quantitative criterion
182(1)
10.2.3. Expression of the quality
183(1)
10.2.4. Precision and accuracy
184(1)
10.2.5. Appraisal and use of quality
185(1)
10.2.6. Meta-quality
185(1)
10.3. Detailed description of quality criteria
186(11)
10.3.1. Lineage
186(1)
10.3.2. Positional accuracy or geometric accuracy
187(1)
10.3.3. Attribute accuracy or semantic accuracy
188(1)
10.3.4. Completeness
189(2)
10.3.5. Logical consistency
191(1)
10.3.6. Semantic consistency
192(2)
10.3.7. Timeliness
194(1)
10.3.8. Temporal consistency
194(2)
10.3.9. Quality criteria: difficulties and limitations
196(1)
10.4. Quality and metadata as seen by standards
197(10)
10.4.1. Introduction to standardization
197(1)
10.4.2. Background of geographic information standards
198(3)
10.4.3. Standards relating to metadata and quality
201(1)
10.4.4. Theoretical analysis of ISO/TC 211 standards
202(1)
10.4.4.1. The ISO 19113 standard
202(1)
10.4.4.2. The ISO 19114 standard
203(1)
10.4.4.3. The ISO 19115 standard
204(1)
10.4.4.4. ISO 19138 preliminary draft technical specification
205(1)
10.4.5. Standardized implementation of metadata and quality
205(1)
10.4.5.1. Preamble
205(1)
10.4.5.2. The model for exchange by transmission
206(1)
10.4.5.3. Data transfer
206(1)
10.4.5.4. Metadata of geographic objects
207(1)
10.5. Conclusion
207(1)
10.6. References
208(3)
PART 4. External Quality: Communication and Usage
Chapter 11. Spatial Data Quality Assessment and Documentation
211(26)
Jean-François HANGOUËT
11.1. Introduction
211(2)
11.1.1. Quality in its context
211(1)
11.1.2. Outline of chapter
212(1)
11.2. Denotation as a radical quality aspect of geographical data
213(1)
11.3. Sources for the fluctuations in denotation
214(6)
11.3.1. The modeling of the world
214(1)
11.3.2. The modeling of operations
215(1)
11.3.3. Realization of the model of operations
216(1)
11.3.4. Realization of the model of the world
216(3)
11.3.5. Synthesis
219(1)
11.4. How to express denotation quality
220(13)
11.4.1. General principles for the assessment of denotation quality
220(1)
11.4.1.1. Comparison
220(1)
11.4.1.2. Measure for measure
222(1)
11.4.1.3. Statistics
222(1)
11.4.1.4. Validity intervals
223(1)
11.4.1.5. Reporting
224(1)
11.4.2. Toward a few measures
225(1)
11.4.3. Geometry measures
225(1)
11.4.3.1. Punctual objects
225(1)
11.4.3.2. Linear objects
226(1)
11.4.3.3. Surface objects
228(1)
11.4.3.4. Topology
228(1)
11.4.4. Time measures
229(1)
11.4.4.1. Dates
229(1)
11.4.4.2. Chronology
229(1)
11.4.5. Value measures
229(1)
11.4.5.1. Semantics
229(1)
11.4.5.2. Semiology
231(1)
11.4.6. Indirect measures
232(1)
11.4.7. Measures on modeling
232(1)
11.5. Conclusion
233(1)
11.6. References
233(4)
Chapter 12. Communication and Use of Spatial Data Quality Information in GIS
237(18)
Rodolphe DEVILLERS and Kate BEARD
12.1. Introduction
237(1)
12.2. Data quality information management
238(2)
12.3. Communication of data quality information
240(4)
12.3.1. Metadata
240(1)
12.3.2. Data quality visualization
241(3)
12.4. Use of quality information
244(3)
12.4.1. Warnings and illogical operators
245(1)
12.4.2. Quality-Aware GIS
246(1)
12.5. Example: multidimensional user manual prototype
247(2)
12.6. Conclusion
249(1)
12.7. References
250(5)
Chapter 13. External Quality Evaluation of Geographical Applications: An Ontological Approach
255(16)
Bérengère VASSEUR, Robert JEANSOULIN, Rodolphe DEVILLERS and Andrew FRANK
13.1. Introduction
255(1)
13.2. Quality and ontology
256(3)
13.2.1. Quality definition and external quality
256(2)
13.2.2. Complexity of external quality evaluation
258(1)
13.2.3. Concept of ontology
258(1)
13.3. Representation of external quality
259(7)
13.3.1. Improvement of quality process
259(1)
13.3.2. Geosemantical integration
260(1)
13.3.3. Stages allowing external quality evaluation
261(1)
13.3.3.1. Conceptualization and initial formalization (Stage 1)
262(1)
13.3.3.2. Expected and internal quality matrices (Stage 2)
262(1)
13.3.3.3. Comparison and utility: example of an application in transportation (Stage 3)
264(2)
13.4. Discussion and conclusion
266(1)
13.5. References
267(4)
Chapter 14. A Case Study in the Use of Risk Management to Assess Decision Quality
271(12)
Gary J. HUNTER and Sytze DE BRUIN
14.1. Introduction
271(1)
14.1.1. Information quality and decision-making
271(1)
14.1.2. Chapter outline
272(1)
14.2. Determining the required decision quality
272(2)
14.3. Using risk management to assess decision quality
274(1)
14.4. Dealing with risk in the decision
275(2)
14.5. Case study: determining the volume of sand for a construction site
277(4)
14.5.1 Case study description
277(1)
14.5.2. Description of the data and model to be used
278(2)
14.5.3. Results
280(1)
14.6. Conclusions
281(501)
14.7. References
782
Chapter 15. On the Importance of External Data Quality in Civil Law
283(18)
Marc GERVAIS
15.1. Introduction
283(2)
15.2. Applicable general civil liability regimes
285(12)
15.2.1. Liability regime of an act or fault of another
286(5)
15.2.2. Liability regime of an act of a thing
291(6)
15.3. Conclusion
297(1)
15.4. References
297(4)
Appendix. Quality, and Poem Alike 301(4)
Jean-François HANGOUËT
List of Authors 305(2)
Index 307

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