| Preface |
|
xi | |
|
Part 1 Bases and Concepts |
|
|
1 | (72) |
|
Chapter 1 Imperfection and Geographic Information |
|
|
3 | (8) |
|
|
|
|
|
|
|
|
|
3 | (2) |
|
1.2 Concepts, representation, reasoning system, and data processing |
|
|
5 | (3) |
|
1.2.1 Foundations and concepts |
|
|
5 | (1) |
|
1.2.2 Representations of imperfection |
|
|
6 | (1) |
|
1.2.3 Reasoning systems and data processing |
|
|
7 | (1) |
|
1.3 Some conclusive remarks |
|
|
8 | (1) |
|
|
|
9 | (2) |
|
Chapter 2 Imperfection of Geographic Information: Concepts and Terminologies |
|
|
11 | (14) |
|
|
|
|
|
|
|
|
|
11 | (2) |
|
2.2 Semantics according to Humpty Dumpty |
|
|
13 | (4) |
|
2.3 Taxonomies of GI and its related uncertainty |
|
|
17 | (2) |
|
2.4 A theoretical framework of the nature of uncertainty and quality |
|
|
19 | (2) |
|
|
|
21 | (1) |
|
|
|
22 | (3) |
|
Chapter 3 The Origins of Imperfection in Geographic Data |
|
|
25 | (20) |
|
|
|
|
|
Ana-Maria Olteanu-Raimond |
|
|
|
|
|
|
25 | (2) |
|
3.2 Imperfection during the life cycle of geographic data |
|
|
27 | (1) |
|
3.3 The sources of the imperfections in a process |
|
|
28 | (8) |
|
3.3.1 The target model: toward what? |
|
|
28 | (2) |
|
3.3.2 The initial source: from what? |
|
|
30 | (1) |
|
3.3.3 The instrument: with what? |
|
|
31 | (2) |
|
3.3.4 The procedure: how? |
|
|
33 | (2) |
|
3.3.5 The operator: by whom? |
|
|
35 | (1) |
|
3.4 Examples of sources of imperfection in different processes |
|
|
36 | (5) |
|
|
|
41 | (1) |
|
|
|
42 | (3) |
|
Chapter 4 Integrity and Trust of Geographic Information |
|
|
45 | (28) |
|
|
|
|
|
|
|
|
|
|
|
|
|
45 | (1) |
|
4.2 The notions of quality |
|
|
46 | (2) |
|
4.2.1 Data quality and its dimensions |
|
|
46 | (1) |
|
4.2.2 Assessing data quality |
|
|
47 | (1) |
|
4.2.3 Problems linked to data of poor quality |
|
|
48 | (1) |
|
4.3 Internal quality and integrity |
|
|
48 | (4) |
|
4.3.1 The concept of integrity |
|
|
49 | (1) |
|
4.3.2 Analyzing data integrity |
|
|
50 | (2) |
|
4.4 External quality and trust |
|
|
52 | (6) |
|
4.4.1 Definitions of trust |
|
|
53 | (1) |
|
|
|
54 | (4) |
|
4.5 Applying these notions to maritime geolocation data |
|
|
58 | (11) |
|
4.5.1 The Automatic Identification System |
|
|
59 | (1) |
|
4.5.2 Integrity and trust issues linked to the AIS |
|
|
59 | (2) |
|
4.5.3 A suitable system for a range of analyses |
|
|
61 | (1) |
|
4.5.4 A suitable system for assessing integrity |
|
|
62 | (4) |
|
4.5.5 A suitable system for measuring trust |
|
|
66 | (3) |
|
|
|
69 | (1) |
|
|
|
70 | (3) |
|
|
|
73 | (40) |
|
Chapter 5 Formalisms and Representations of Imperfect Geographic Objects |
|
|
75 | (30) |
|
|
|
|
|
5.1 Theories about the representation of an imperfect geographic object |
|
|
75 | (1) |
|
5.2 Where and when do we refer to imperfection in geographic information? |
|
|
76 | (3) |
|
|
|
79 | (17) |
|
5.3.1 The notion of event |
|
|
79 | (3) |
|
5.3.2 Confidence and certainty (pre-measure and confidence measure) |
|
|
82 | (3) |
|
5.3.3 Non-additive measures and associated distributions |
|
|
85 | (5) |
|
5.3.4 Tools used to manipulate fuzzy measures and sets |
|
|
90 | (6) |
|
|
|
96 | (3) |
|
5.4.1 Broad boundary objects |
|
|
96 | (2) |
|
|
|
98 | (1) |
|
5.5 Reconsidering the introductory examples |
|
|
99 | (3) |
|
|
|
102 | (3) |
|
Chapter 6 Representing Diagrams of Imperfect Geographic Objects |
|
|
105 | (8) |
|
|
|
|
|
|
|
105 | (1) |
|
6.2 Describing the theoretical models of geographic objects |
|
|
105 | (3) |
|
6.3 Describing the theoretical models of imperfect geographic objects |
|
|
108 | (3) |
|
6.4 Toward massive databases |
|
|
111 | (1) |
|
|
|
111 | (2) |
|
Part 3 Reasoning and Treatment |
|
|
113 | (78) |
|
Chapter 7 Algebraic Reasoning for Uncertain Data |
|
|
115 | (18) |
|
|
|
|
|
115 | (1) |
|
7.2 Algebras used for spatial reasoning |
|
|
116 | (7) |
|
7.2.1 The definition and properties of algebras, relational algebras |
|
|
116 | (2) |
|
7.2.2 Relational algebras used for time and space |
|
|
118 | (5) |
|
|
|
123 | (3) |
|
7.4 Extending these models to fuzzy regions |
|
|
126 | (2) |
|
|
|
128 | (5) |
|
Chapter 8 Reasoning in Modal Logic for Uncertain Data |
|
|
133 | (18) |
|
|
|
|
|
|
|
133 | (1) |
|
8.2 Reasoning in first-order predicate calculus |
|
|
134 | (6) |
|
8.3 Reasoning in modal logic |
|
|
140 | (9) |
|
|
|
149 | (2) |
|
Chapter 9 Reviewing the Qualifiers of Imperfection in Geographic Information |
|
|
151 | (24) |
|
|
|
|
|
|
|
151 | (1) |
|
9.2 Belief revision and update in knowledge engineering |
|
|
152 | (1) |
|
9.3 The limitations faced by GIS when representing a set of beliefs |
|
|
153 | (1) |
|
9.4 Revision in a set of binary beliefs |
|
|
154 | (2) |
|
9.5 The case of uncertain beliefs |
|
|
156 | (4) |
|
9.6 Bayesian probabilistic conditioning |
|
|
160 | (3) |
|
9.7 Revision in evidence theory |
|
|
163 | (2) |
|
9.8 Possibilistic conditioning |
|
|
165 | (6) |
|
|
|
171 | (2) |
|
|
|
173 | (2) |
|
Chapter 10 The Features of Decision Aid and Analysis Processes in Geography: How to Grasp Complexity, Uncertainty, and Risks? |
|
|
175 | (16) |
|
|
|
10.1 The decision-making context |
|
|
175 | (1) |
|
10.2 Geographers, decision-makers, actors, and the territory |
|
|
176 | (2) |
|
10.3 The objects, stakes, and issues involved in a decision |
|
|
178 | (2) |
|
10.4 Information, data, knowledge, uncertainties, and bias |
|
|
180 | (2) |
|
10.5 Supporting the structuring and resolution of ranking, choice, or sorting problems (issues) |
|
|
182 | (3) |
|
10.6 A decision-analysis method for risk analysis and management |
|
|
185 | (3) |
|
|
|
188 | (1) |
|
|
|
189 | (2) |
| List of Authors |
|
191 | (2) |
| Index |
|
193 | |
Biežāk uzdotie jautājumi par e-grāmatām