Membership grade normalization of GIS uncertainty model and two fuzzy overlay algorithms

Author

Wang, Xiaodong ; Dang, Anrong

Author_Institution

Sch. of Archit., Tsinghua Univ., Beijing, China

Volume

5

fYear

2000

fDate

2000

Firstpage

2131

Abstract

Uncertainty research is an important research focus of GIS. Fuzzy set theories provide a good method for GIS uncertainty model to describe the world more externally. Based on fuzzy set theories, membership grade normalization (MGN) applied to GIS temporal dimension, spatial dimension and thematic dimension is proposed. The intersection operator and union operator of traditional fuzzy set theories could not meet MGN. It is necessary to construct a new fuzzy overlay operator. At last, two fuzzy overlay algorithms meeting MGN are given

Keywords

fuzzy set theory; geographic information systems; geophysics computing; uncertainty handling; GIS; fuzzy overlay algorithm; fuzzy set theory; geographic information system; geophysics computing; membership grade normalization; spatial dimension; temporal dimension; thematic dimension; uncertainty model; Computational Intelligence Society; Data models; Fuzzy set theory; Fuzzy sets; Geographic Information Systems; Humans; Mathematics; Postal services; Probability distribution; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 2000. Proceedings. IGARSS 2000. IEEE 2000 International

Conference_Location

Honolulu, HI

Print_ISBN

0-7803-6359-0

Type

conf

DOI

10.1109/IGARSS.2000.858330

Filename

858330