A new framework for effective urban land use and land cover classification: A wavelet approach

Research output: Contribution to journalArticle

17 Scopus citations

Abstract

This study develops a new framework for multi-scale analysis procedures and a new operational wavelet-based algorithm to identify urban classes. For better evaluation of wavelets, traditional classifiers were used: maximum likelihood, Mahalanobis, and minimum distance to identify the same classes. Overall accuracy for maximum likelihood, Mahalanobis, and minimum distance for band-3 and multi-bands were 49%, 43%, 48%, 58%, 56%, and 55%, respectively. However, the wavelet approach with the above measures using Band 3 alone gave much higher accuracies (70%, 80%, and 81 %). It can be concluded that the wavelet-based approaches are far more accurate than the traditional classifiers.

Original languageEnglish (US)
Pages (from-to)155-178
Number of pages24
JournalGIScience and Remote Sensing
Volume43
Issue number2
DOIs
StatePublished - Apr 1 2006

ASJC Scopus subject areas

  • Earth and Planetary Sciences(all)

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