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Classification of basic roof types based on VHR optical data and digital elevation model

Authors :
Jocelyn Chanussot
S. Valero
Philippe Guéguen
GIPSA - Signal Images Physique (GIPSA-SIGMAPHY)
Département Images et Signal (GIPSA-DIS)
Grenoble Images Parole Signal Automatique (GIPSA-lab)
Université Stendhal - Grenoble 3-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Stendhal - Grenoble 3-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Grenoble Images Parole Signal Automatique (GIPSA-lab)
Université Stendhal - Grenoble 3-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Stendhal - Grenoble 3-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)
Chanussot, Jocelyn
Source :
Proceedings of the IEEE International Geoscience And Remote Sensing Symposium 2008, IGARSS 2008, IGARSS 2008-IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2008-IEEE International Geoscience and Remote Sensing Symposium, Jul 2008, Boston, MA, United States. pp.2008, IGARSS (4)
Publication Year :
2008
Publisher :
HAL CCSD, 2008.

Abstract

In the frame of seismic vulnerability assessment in urban areas, it is very important to estimate the nature of the roof of every building and, in particular, to make the difference between flat roofs and gable ones. In order to perform this tedious task automatically on a large scale, remote sensing data provide a useful solution. In this study, we use simultaneously very high resolution panchromatic data, and an accurate digital elevation model. The fusion of these two modalities enables the extraction of two mixed features. Based on these features the classification between the two considered classes becomes a simple linearly separable problem.

Details

Language :
English
Database :
OpenAIRE
Journal :
Proceedings of the IEEE International Geoscience And Remote Sensing Symposium 2008, IGARSS 2008, IGARSS 2008-IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2008-IEEE International Geoscience and Remote Sensing Symposium, Jul 2008, Boston, MA, United States. pp.2008, IGARSS (4)
Accession number :
edsair.doi.dedup.....19d59d893040852c8639d79cfda2055f