Délimitation d‘aires urbaines à partir d‘une image Landsat ETM+: Comparaison de méthodes de classification

Translated title of the contribution: Delineation of urban areas from a Landsat ETM+ image: comparison of classification methods

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6 Citations (Scopus)

Abstract

In this article, a segmentation and texture-based image classification method is proposed to extract the urban areas of the municipalities of Sintra and Cascais using a Landstat enhanced thematic mapper plus (ETM+) image. This method is compared with other classification methods, among some of the most used in remote sensing: normalized difference built-up index (NDBI), maximum likelihood, clusters, and neural networks. The results obtained by the proposed method, using overall accuracy and kappa indices, are superior to the ones produced by the other methods. The results further indicate that the urban class, of heterogeneous spectral composition, is difficult to classify by purely spectral methods that do not consider the structure of the image.

Translated title of the contributionDelineation of urban areas from a Landsat ETM+ image: comparison of classification methods
Original languageFrench
Pages (from-to)422-430
Number of pages9
JournalCanadian Journal of Remote Sensing
Volume33
Issue number5
DOIs
Publication statusPublished - 2007

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