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Matching disparate geospatial datasets and validating matches using spatial logic / Heshan Du (2015)
Titre : Matching disparate geospatial datasets and validating matches using spatial logic Type de document : Thèse/HDR Auteurs : Heshan Du, Auteur ; Natasha Alechina, Directeur de thèse ; M.J. Jackson, Directeur de thèse Editeur : Nottingham : University of Nottingham Année de publication : 2015 Importance : 211 p. Note générale : Bibliographie
Thesis submitted to the University of Nottingham for the degree of Doctor of PhilosophyLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] appariement de données localisées
[Termes IGN] appariement géométrique
[Termes IGN] cartographie collaborative
[Termes IGN] cohérence des données
[Termes IGN] données localisées de référence
[Termes IGN] données localisées des bénévoles
[Termes IGN] données vectorielles
[Termes IGN] intégration de données
[Termes IGN] jeu de données localisées
[Termes IGN] ontologie
[Termes IGN] OpenStreetMap
[Termes IGN] Ordnance Survey (UK)
[Termes IGN] relation topologique
[Termes IGN] zone tamponRésumé : (auteur) In recent years, the emergence and development of crowd-sourced geospatial data has provided challenges and opportunities to national mapping agencies as well as commercial mapping organisations. Crowd-sourced data involves non-specialists in data collection, sharing and maintenance. Compared to authoritative geospatial data, which is collected by surveyors or other geodata professionals, crowd-sourced data is less accurate and less structured, but often provides richer user-based information and reflects real world changes more quickly at a much lower cost. In order to maximize the synergistic use of authoritative and crowd-sourced geospatial data, this research investigates the problem of how to establish and validate correspondences (matches) between spatial features from disparate geospatial datasets. To reason about and validate matches between spatial features, a series of new qualitative spatial logics was developed. Their soundness, completeness, decidability and complexity theorems were proved for models based on a metric space. A software tool `MatchMaps' was developed, which generates matches using location and lexical information, and verifies consistency of matches using reasoning in description logic and qualitative spatial logic. MatchMaps was evaluated by the author and experts from Ordnance Survey, the national mapping agency of Great Britain. In experiments, it achieved high precision and recall, as well as reduced human effort. The methodology developed and implemented in MatchMaps has a wider application than matching authoritative and crowd-sourced data and could be applied wherever it is necessary to match two geospatial datasets of vector data. Note de contenu : 1. Introduction
1.1. Research Question
1.2. Research Aim and Objectives
1.3. Contributions and Structure of the Thesis
2. Context of Research
2.1. Development of Crowd-sourced Geospatial Data
2.2. Quality of OpenStreetMap Data
2.3. Usability of OpenStreetMap Data
3. Litterature Review
3.1. Geospatial Data Matching
3.2. Ontology Matching
3.3. Spatial Logic
4. A Framework for Integrating Geospatial Datasets
4.1. Building up the Framework
4.2. Rationale of the Framework
4.3. MatchMaps: an Implemented System
5. Matching Spatial Features
5.1. Theoretical Basis for Matching Geometries
5.2. Matching Geometries
5.3. Matching Spatial Objects
6. Validating Matches using Description Logic
6.1. Description Logic ALCO
6.2. Validationg Terminology Matches using Description Logic
6.3. Validating Object Matches using Description Logic
7. A Logic of NEAR and FAR for Buffered Points
7.1. Syntax, Semantics and Axioms of LNF
7.2. Soundness and Completeness of LNF
7.3. Decidability and Complexity of LNF
7.4. Interpreting L(LNF) in R²
8. A Logic of NEAR and FAR for Buffered Geometries
8.1. Syntax, Semantics and Axioms of LNFS
8.2. Soundness and Completeness of LNFS
8.3. Decidability and Complexity of LNFS
8.4. Interpreting L(LNFS) in R²
9. A Logic of Part and Whole for Buffered Geometries
9.1. Syntax, Semantics and Axioms of LBPT
9.2. Soundness and Completeness of LBPT
9.3. Decidability and Complexity of LBPT
9.4. Interpreting L(LBPT) in R²
10. Validating Matches using Qualitative spatial Logic
10.1. Validating Matches using LNF, LNFS ans LBPT
10.2. Actions for Retracting Problematic Matches
11. Evaluation and Discussion
11.1. Developer Evaluation of MatchMaps
11.2. User Evaluation of MatchMaps
11.3. Discussion
12. Conclusion and Future Work
12.1. Conclusion
12.2. Future WorkNuméro de notice : 19794 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Thèse étrangère Note de thèse : PhD thesis : : Nottingham : 2015 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85041