Paper Info
Title
Mapping land cover types as fuzzy sets
Abstract
Researches have suggested that fuzzy sets form a more appropriate basis for land cover mapping than traditional Boolean classification. However, to give a crisp answer of which land cover types pixels in remote sensing images belong to, fuzzy clustering methods such as FMC always lost some subtle vague information. In this paper, the result of the Boolean classification using a fuzzy clustering method was analyzed and based on the result of the classification, we tried to map land cover types as type 1 fuzzy sets and type 2 fuzzy sets. Results show that type 1 fuzzy sets and type 2 fuzzy sets kept more subtle information that was lost in the processing of converting the fuzzy classification result to a Boolean one. And the structure of the study area can be more explicit represented.
Year
DOI
Venue
2010
10.1109/GEOINFORMATICS.2010.5567577
Geoinformatics
Keywords
Field
DocType
terrain mapping,pattern clustering,type 1 fuzzy sets,land cover mapping,fuzzy clustering methods,type 2 fuzzy sets,fuzzy logic,fuzzy sets,boolean classification,image classification,geophysical image processing,land cover types,remote sensing images,boolean functions,fuzzy classification,fuzzy clustering,classification algorithms,remote sensing,clustering algorithms,fuzzy set,pixel,information science
Data mining,Fuzzy clustering,Defuzzification,Fuzzy classification,Computer science,Fuzzy set operations,Fuzzy set,Type-2 fuzzy sets and systems,Fuzzy number,Membership function
Conference
ISBN
Citations 
PageRank 
978-1-4244-7301-4
0
0.34
References 
Authors
4
5
Name
Order
Citations
PageRank
Chong Chen100.34
Manchun Li221145.40
Qiuhao Huang393.76
Zhenjie Chen4206.33
Kun Mao51275.93