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Cartographie des zones urbaines a l'aide des images aeroportees MEIS-II

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Abstract:

The aim of this study is to evaluate the contribution of texture information to high spatial and spectral resolution for zonal mapping in urban areas. The airborne data used were acquired over the Montreal Urban Community (Montreal, Canada) by the Multi-detector Electro-optical Imaging Scanner (MEIS-II) of the Canada Centre for Remote Sensing. Spectral analysis of the divergence between classes has shown that bands 3 (847-901 nm), 4 (622-659nm), and 7 (433-463mm) offer the optimal combination for discriminating between the urban classes we have defined. Textural features derived from three different order histograms were calculated from band 4 and evaluated in terms of their ability to discriminate between urban classes. We then extracted the best feature from each of the histograms. The integration of these three textural features with the three spectral bands has shown that textural information permits an improvement in class separability resulting in an increase in the rate of correct classification in the order of 12%. This increase is however dependent on the type of class and varies from 4.5% for forest and parks to 16.8% for urban areas with low vegetation density. Classification by maximum likelihood of these spectral-textural data and the visual analysis of results also show that textural information, in conjunction with high spatial and spectral resolution, provides appropriate zonal mapping of urban areas. L'objectif de cette etude est d'evaluer l'apport de la texture en terme d'information additionnelle a la resolution spatiale et spectrale pour la cartographie des zones urbaines. Les donnees aeroportees utilisees ont ete acquises au dessus de la Communaute-urbaine de Montreal (Montreal, Canada) a l'aide du detecteur Multi-detector Electro-optical Imaging Scanner (MEIS-II) du Centre canadien de teledetection. L'analyse spectrale du point de vue de la divergence entre classes a montre que les bandes 3 (847-901nm), 4 (622-659nm) et 7 (433-463nm) offrent la combinaison optimale pour la discrimination entre les classes urbaines qu'on s'est definies. Des parametres de texture issues de trois differents ordres d'histogrammes ont ete calcules sur la bande 4 et evalues du point de vue de leur discrimination entre les classes urbaines. On a ensuite extrait le meilleur parametre de chacun de ces trois histogrammes. L'integration de ces trois parametres texturaux avec les trois bandes spectrales a montre que l'information texturale permet une amelioration de la separabilite des classes entrainant une augmentation du taux de classification correcte de l'ordre de 12%. Cette augmentation est cependant dependante du type de classes et varie de 4,5% pour la foret et parcs a 16,8% pour l'urbain possedant une faible densite vegetale. La classification par maximum de vraisemblance de ces donnees spectro-texturales et l'analyse visuelle des resultats montrent aussi que l'information texturale, de concert avec la haute resolution spatiale et spectrale, permet une cartographie zonale appropriee du milieu urbain.

Document Type: Research Article

DOI: http://dx.doi.org/10.1080/014311698215775

Publication date: March 20, 1998

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tandf/tres/1998/00000019/00000005/art00006
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