Volume XL-3/W3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3/W3, 433-438, 2015
https://doi.org/10.5194/isprsarchives-XL-3-W3-433-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3/W3, 433-438, 2015
https://doi.org/10.5194/isprsarchives-XL-3-W3-433-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

  19 Aug 2015

19 Aug 2015

MORPHO-SPECTRAL RECOGNITION OF DENSE URBAN OBJECTS BY HYPERSPECTRAL IMAGERY

S. Gadal and W. Ouerghemmi S. Gadal and W. Ouerghemmi
  • Aix-Marseille Université, CNRS ESPACE UMR 7300, Aix-en-Provence, France

Keywords: Morpho-spectral database, Feature Extraction, mophometry, morphological attributes, spectral attributes, vector mapping, build-up, hyperspectral remote sensing

Abstract. This paper presents a methodology for recognizing, identifying and classifying built objects in dense urban areas, using a morphospectral approach applied to VNIR/SWIR hyperspectral image (HySpex). This methodology contains several image processing steps: Principal Components Analysis and Laplacian enhancement, Feature Extraction of segmented build-up objects, and supervised classification from a morpho-spectral database (i.e. spectral and morphometric attributes). The Feature Extraction toolbox automatically generates a vector map of segmented buildings and an urban object-oriented morphometric database which is merged with an independent spectral database of urban objects. Each build-up object is spectrally identified and morphologically characterized thanks to the built-in morpho-spectral database.