Title :
Classification of basic roof types based on VHR optical data and digital elevation model
Author :
Valero, Silvia ; Chanussot, Jocelyn ; Gueguen, Philippe
Author_Institution :
GIPSA-Lab., Grenoble Inst. of Technol., Grenoble
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.
Keywords :
digital elevation models; feature extraction; image classification; remote sensing; seismology; sensor fusion; VHR optical data; building roof; data fusion; digital elevation model; feature extraction; flat roofs; remote sensing data; roof types classification; seismic vulnerability assessment; very high resolution panchromatic data; Data mining; Digital elevation models; Feature extraction; Image edge detection; Image resolution; Image segmentation; Optical sensors; Pattern recognition; Skeleton; Urban areas; Classification; Data Fusion; Mathematical Morphology; Seismic Risk Assessment; Skeleton; Urban Areas;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4244-2807-6
Electronic_ISBN :
978-1-4244-2808-3
DOI :
10.1109/IGARSS.2008.4779679