Mapping urban impervious surfaces from an airborne hyperspectral imagery using the object- oriented classification approach - Archive ouverte HAL
Communication Dans Un Congrès Année : 2017

Mapping urban impervious surfaces from an airborne hyperspectral imagery using the object- oriented classification approach

Résumé

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.
Fichier principal
Vignette du fichier
Aguedjad 2017 MATEC.pdf (10.03 Mo) Télécharger le fichier
Origine Fichiers éditeurs autorisés sur une archive ouverte
Loading...

Dates et versions

hal-01854890 , version 1 (07-08-2018)

Identifiants

  • HAL Id : hal-01854890 , version 1

Citer

Rahim Aguejdad, Aziz Serradj, Christiane Weber. Mapping urban impervious surfaces from an airborne hyperspectral imagery using the object- oriented classification approach. International Conference on Advances in Sustainable Construction Materials & Civil Engineering Systems (ASCMCES-17) , 2017, SHARJAH, Saudi Arabia. ⟨hal-01854890⟩
179 Consultations
82 Téléchargements

Partager

More