e The drawbacks of standard logic adopted in GIS oper-
ations are highlighted.
e The advantages of fuzzy set theory over classical set
theory and the necessity of incorporating fuzzy logic
methodologies into GIS operations are presented.
Future research includes:
e The design of a prototype spatial decision support sys-
tem based on fuzzy logic methodologies.
e The selection of appropriate transformation functions
and overall measures (information metrics) for the set
of constraints posed by decision-makers and problem
specific features in a real-world situation (e.g., residen-
tial site selection).
REFERENCES
[Aronoff, 1989] Aronoff, S., 1989. Geographic Information
Systems: A Management Perspective. WDL Publications.
[Aubert et al., 1994] Aubert, E., Edwards, G., and Low-
ell., K.E., 1994. Quantification des erreurs de frontières
en photo-interprétation forestière pour le suivie spatio-
temporel des peuplements. Proceedings of the 6th Cana-
dian Conference on GIS, Ottawa, Canada, pp. 195-205.
[Berry, 1987] Berry, J.K., 1987. Fundamental operations in
computer-assisted map analysis. International Journal of
Geographical Information Systems, 1(2), pp. 119-136.
[Burrough, 1989] Burrough, P.A., 1989. Fuzzy mathematical
methods for soil survey and land evaluation. Journal of Soil
Science, 40, pp. 477-492.
[Davidson et al., 1994] Davidson, D.A., Theocharopoulos,
S.P., and Bloksma, R.J., 1994. A land evaluation project
in greece using gis and based on boolean and fuzzy set
methodologies. International Journal of Geographical In-
formation Systems, 8(4), pp. 369-384.
[Fischer, 1994] Fischer, M.M., 1994. Expert systems and ar-
tificial neural networks for spatial analysis and modelling.
Geographical Systems, 1(1), pp. 221-235.
[Gupta et al., 1988] Gupta, M.M., Knopf, G.K., and Niki-
foruk, P.N., 1988. Sinusoidal-based cognititive mapping
functions. In Gupta, M.M., and Yamakawa, T., (ed's)
Fuzzy Logic in Knowledge Based Systems, Decision and
Control, North-Holland, pp. 69-92.
[Kollias et al., 1991] Kollias, V.J., and Voliotis, A., 1991.
Fuzzy reasoning in the development of geographical in-
formation systems. International Journal of Geographical
Information Systems, 5, pp. 209-223.
[Leung et al., 1993] Leung, Y., and Leung, K.S., 1993. An
intelligent expert system shell for knowledge-based geo-
graphical information system: 1. the tools, 2. some appli-
cations. International Journal of Geographical Information
Systems, 7(3), pp. 189-213.
[Maguire et al., 1991] Maguire, D.J., Goodchild, M.F., and
Rhind, D.W., 1991. Geographical Information Systems:
Principles and Applications. Longman Scientific and Tech-
nical.
[Samet et al., 1995] Samet, H., and Aref, W.G., 1995. Spa-
tial data models and query processing. In Kim, W., (ed.),
Modern Database Systems, ACM Press, pp. 339-360.
[Tomlin, 1990] Tomlin, C.D., 1990. Geographic Information
Systems and Cartographic Modeling. Prentice Hall.
[Vazirgiannis et al., 1994] Vazirgiannis, M., Petrou, K,
Tsompanidis, A., and Hatzopoulos, M., 1994. An object-
oriented framework for knowledge representation based on
fuzzy sets. Intelligent and Fuzzy Systems, 1, pp. 265-278.
[Zadeh, 1968] Zadeh, L.A., 1968. Probability measures of
fuzzy events. Math. Anal. Applications, 23, pp. 421-427.
[Zadeh, 1988] Zadeh, L.A., 1988. Fuzzy logic. IEEE Com-
puter, 21(4), pp. 83-93.
International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B4. Vienna 1996
t E
OE Diag >On iad a + IN D