MATEC Web Conf.
Volume 120, 2017International Conference on Advances in Sustainable Construction Materials & Civil Engineering Systems (ASCMCES-17)
|Number of page(s)||8|
|Section||Geographic Information Systems & Remote Sensing|
|Published online||09 August 2017|
Mapping urban impervious surfaces from an airborne hyperspectral imagery using the object-oriented classification approach
1 Laboratoire Image Ville Environnement UMR7362-CNRS, 3 Rue de l’Argonne, 67000 Strasbourg, France
2 Maison de la Télédétection UMR TETIS, 500 Rue Jean-François Breton, 34000 Montpellier, France
* Corresponding author: firstname.lastname@example.org
The objective of this research is to explore the capabilities of the hyperspectral imagery in mapping the urban impervious objects and identifying the surface materials using an object-oriented approach. The application is conducted to Toulouse city (France) within the HYEP research project in charge of using hyperspectral imagery for the environmental urban planning. The method uses the multi-resolution segmentation and classification algorithms. The first results highlight a high potential of the hyperspectral imagery in land cover mapping of the urban environment, especially the extraction of impervious surfaces. They, also, illustrate, that the object-oriented approach by means of the fuzzy logic classifier yields promising results in distinguishing the mean roofing materials based only on the spectral information. Conversely to the red clay tiles and metal roofs, which are easily identified, the concrete, gravel and asphalt roofs are still confused with roads.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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