Conjoint analysis for quantification of relative importance of various factors affecting BPANN classification of urban environment

Pathak, Virendra & Dikshit, Onkar (2006) Conjoint analysis for quantification of relative importance of various factors affecting BPANN classification of urban environment. International Journal of Remote Sensing, 27(21), pp. 4769-4789.

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This paper is an attempt to suggest an approach for eliminating the lengthy process of selecting various factors while using Backpropagation artificial neural network (BPANN) and to quantify the relative importance of the factors affecting classification results. A novel approach called conjoint analysis has been used here. The paper also presents the classification results of an Indian urban environment using two BPANN approaches and compares them with conventional Gaussian Maximum Likelihood (GML) classification approach. The study showed that conjoint analysis can be successfully used to select various parameters of BPANN prior to carrying out the classifications using any of the BPANN approach. Factors like size of training samples and first hidden layer come out as some of the most important factors while the second hidden layer has the least affect on classification accuracy. Resilient backpropagation method of BPANN is the best and robust method for urban classification. Results also showed that classification obtained using BPANN approach were similar or numerically better than GML classification though the difference was not statistically significantly different.

Impact and interest:

2 citations in Scopus
2 citations in Web of Science®
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ID Code: 17900
Item Type: Journal Article
Refereed: Yes
Keywords: BPANN, GML, RPROP, Conjoint Analysis, Relative Importance
DOI: 10.1080/01431160600784184
ISSN: 0143-1161
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > GEOMATIC ENGINEERING (090900) > Photogrammetry and Remote Sensing (090905)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Copyright Owner: Copyright 2006 Taylor & Francis
Copyright Statement: Reproduced in accordance with the copyright policy of the publisher
Deposited On: 17 Feb 2009 03:09
Last Modified: 06 Jul 2017 08:01

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