Full text: XVIIIth Congress (Part B4)

  
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
	        
Waiting...

Note to user

Dear user,

In response to current developments in the web technology used by the Goobi viewer, the software no longer supports your browser.

Please use one of the following browsers to display this page correctly.

Thank you.