Using semantic similarity metrics to uncover category and land cover change

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3799 LNCS, Issue , 2005, Pages 107-119

  Ahlqvist, Ola ^a  

^a OHIO STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTER SCIENCE; COMPUTER SIMULATION; GEOGRAPHIC INFORMATION SYSTEMS; SEMANTICS;

CLASSIFICATION SYSTEM; LAND COVER CHANGE; LANDSCAPE; SEMANTIC SIMILARITY METRICS;

MEASUREMENT THEORY;

EID: 33646826691     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11586180_8     Document Type: Conference Paper

References (25)

1. Ahlqvist, O. A parameterized representation of uncertain conceptual spaces, Transactions in GIS, 8(4): 493-514, 2004.
2. Ahlqvist, O. Using uncertain conceptual spaces to translate between land cover categories, International journal of geographical information science, 19(7): 831-857, 2005.
3. Ahlqvist, O and Gahegan, M. Photogrammetric Engineering and Remote Sensing, Probing the relationship between classification error and class similarity, in press
4. Ahlqvist, O., Keukelaar, J., and Oukbir, K. Rough and fuzzy geographical data integration, International journal of geographic information science, 17(3): 223-234, 2003.
5. Bishr, Y. Overcoming the semantic and other barriers to GIS interoperability, International Journal of Geographic Information Science, 12(4): 299-314, 1998.
6. Bouchon-Meunier, B., Rifqi, M., Bothorel, S. Towards general measures of comparison of objects, Fuzzy Sets and Systems, 84:143-153, 1996.
7. Comber, A., Fisher, P., and Wadsworth, R. Assessment of a semantic statistical approach to detecting land cover change using inconsistent data sets. Photogrammetric Engineering and Remote Sensing, 70: 931-938., 2004.
8. Di Gregorio, A., and Jansen, L.J.M. Land Cover Classification System: Classification Concepts And User Manual, FAO, Rome, 1998.
9. Dubois, D., and Prade, H. Rough fuzzy sets and fuzzy rough sets, Int.J. General Systems, 17:191-209, 1990.
10. Fonseca, F.T., Egenhofer, M.J., Agouris, P., and Câmara, G. Using ontologies for integrated geographic information systems, Transactions in GIS, 6(3): 231-257, 2002.
11. Gärdenfors, P. Conceptual spaces : the geometry of thought, MIT Press, Cambridge, Mass., 307pp., 2000.
12. Hahn, U., and Chater, N. Concepts and Similarity, Knowledge, Concepts and Categories, (Lamberts, K., and Shanks, D., editors), East Sussex, Psychology Press, pp. 43-92, 1997.
13. Jones, C.B., Alani, H., and Tudhope, D. Geographical Terminology Servers - Closing the Semantic Divide, in: Duckham et al. (Eds.) Foundations of geographic information science, Taylor & Francis, London, 257 p, pp. 205-222, 2003.
14. Kaufman, A., and Gupta, M.M. Introduction to fuzzy arithmetic, Van Nostrand Reinhold Company, New York, 351pp., 1985.
15. Livingstone D., and Raper J. Modelling environmental systems with GIS: theoretical barriers to progress, in: Worboys, M.F. (Ed), Innovations in GIS 1, Taylor & Francis, London, pp. 229-240, 1994.
16. Mennis, J.L. Derivation and implementation of a semantic GIS data model informed by principles of cognition, Computers, Environment and Urban Sytems, 27, pp.455-479, 2003.
17. Nosofsky, R.M. Attention, similarity,and the identification- categorization relationship, Journal of Experimental Psychology: General, 115: 39-57, 1986.
18. Nyerges, T.L. Geographic information abstractions: conceptual clarity for geographical modeling, Environment and Planning A, 23: 1483-1499, 1991.
19. Openshaw, S., Commentary: Fuzzy logic as a new scientific paradigm for doing geography, Environment and Planning A, 28:761-768, 1999.
20. Power et al. Describe a hierarchical fuzzy pattern matching based on ad hoc rules for combinations of crisp landcover classes, 2001.
21. Rodríguez, M.A., and Egenhofer, M.J. Comparing geospatial entity classes: an asymmetric and context-dependent similarity measure. International Journal of Geographical Information Science, 18: 229-256, 2004.
22. Saaty T. L. The analytic hierarchy process: planning, priority setting, resource allocation. Pittsburgh, PA, RWS Publications, 1990.
23. Tversky, A. Features of similarity, Psychological review, 84: 327-352, 1977.
24. Usery, E.L. A conceptual framework and fuzzy set implementation for geographic features, in: in: P.A. Burrough and A.U. Frank (Eds), Geographic, Objects, With Indeterminate Boundaries, Taylor & Francis, London, 345 pp., pp. 71-85, 1996.
25. Visser U., Stuckenschmidt H., Schuster G., Vogele T. Ontologies for geographic information processing. Computers and Geosciences, 28(1): 103-117, 2002.