The Performance of Fuzzy Operators on Fuzzy Classification of Urban Land Covers

The research discussed in this paper evaluates the performance of selected fuzzy operators (e.g., maximum, minimum, algebraic sum, algebraic product, and gamma operators) for integrating fuzzy membership values associated with multiple spectral bands for mapping the complex spatial mixture that characterises urban land covers. Accordingly, a supervised classification approach based on the fuzzy c-means algorithm was implemented to generate fuzzy memberships of selected

[1]  S. Stehman Estimating the Kappa Coefficient and its Variance under Stratified Random Sampling , 1996 .

[2]  G. Foody,et al.  Sub-pixel land cover composition estimation using a linear mixture model and fuzzy membership functions , 1994 .

[3]  G. Foody,et al.  A fuzzy classification of sub-urban land cover from remotely sensed imagery , 1998 .

[4]  Alex B. McBratney,et al.  Application of fuzzy sets to climatic classification , 1985 .

[5]  R. Congalton A Quantitative Method to Test for Consistency and Correctness in Photointerpretation , 1983 .

[6]  M. Goodchild,et al.  Uncertainty in geographical information , 2002 .

[7]  James C. Bezdek,et al.  Efficient Implementation of the Fuzzy c-Means Clustering Algorithms , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  Wooil M. Moon,et al.  Representation and Integration of Geological, Geophysical and Remote Sensing Data , 1991 .

[9]  Mohan Trivedi,et al.  Segmentation of a Thematic Mapper Image Using the Fuzzy c-Means Clusterng Algorthm , 1986, IEEE Transactions on Geoscience and Remote Sensing.

[10]  L. Zadeh Probability measures of Fuzzy events , 1968 .

[11]  Peter F. Fisher,et al.  The evaluation of fuzzy membership of land cover classes in the suburban zone , 1990 .

[12]  Graciela Metternicht,et al.  Evaluating the information content of JERS-1 SAR and Landsat TM data for discrimination of soil erosion features , 1998 .

[13]  G. H. Rosenfield Analysis of variance of thematic mapping experiment data. , 1981 .

[14]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[15]  B. Madhavan,et al.  Integration of IRS-1A L2 data by fuzzy logic approaches for landuse classification , 2000 .

[16]  Stephen E. Fienberg,et al.  Discrete Multivariate Analysis: Theory and Practice , 1976 .

[17]  J. Bezdek,et al.  FCM: The fuzzy c-means clustering algorithm , 1984 .

[18]  Jacob Cohen A Coefficient of Agreement for Nominal Scales , 1960 .

[19]  B. Forster An examination of some problems and solutions in monitoring urban areas from satellite platforms , 1985 .

[20]  Graciela Metternicht,et al.  Spatial discrimination of salt- and sodium-affected soil surfaces , 1997 .

[21]  Andrew K. Skidmore,et al.  Forest mapping accuracies are improved using a supervised nonparametric classifier with SPOT data , 1988 .

[22]  G. Bonham-Carter Geographic Information Systems for Geoscientists: Modelling with GIS , 1995 .

[23]  John A. Richards,et al.  Remote Sensing Digital Image Analysis: An Introduction , 1999 .

[24]  Hans-Jürgen Zimmermann,et al.  Fuzzy Set Theory - and Its Applications , 1985 .

[25]  Russell G. Congalton,et al.  Assessing the accuracy of remotely sensed data : principles and practices , 1998 .

[26]  N. Campbell,et al.  Derivation and applications of probabilistic measures of class membership from the maximum-likelihood classification , 1992 .

[27]  James C. Bezdek,et al.  Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.

[28]  Graciela Metternicht,et al.  Detecting and monitoring land degradation features and processes in the Cochabamba valleys, Bolivia : a synergistic approach , 1996 .

[29]  Roger G. Barry,et al.  Cloud classification from satellite data using a fuzzy sets algorithm - A polar example , 1989 .

[30]  G. H. Rosenfield,et al.  A coefficient of agreement as a measure of thematic classification accuracy. , 1986 .

[31]  John R. Jensen,et al.  Introductory Digital Image Processing: A Remote Sensing Perspective , 1986 .

[32]  R. Congalton,et al.  Accuracy assessment: a user's perspective , 1986 .