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Classification of basic roof types based on VHR optical data and digital elevation model
- 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.
- Subjects :
- Pixel
Contextual image classification
Computer science
business.industry
Frame (networking)
Feature extraction
0211 other engineering and technologies
02 engineering and technology
Sensor fusion
Panchromatic film
[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV]
[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]
11. Sustainability
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Computer vision
Artificial intelligence
Digital elevation model
Scale (map)
business
ComputingMilieux_MISCELLANEOUS
021101 geological & geomatics engineering
Subjects
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