Statistical classification methodology of SHOALS 3000 backscatter to mapping coastal benthic habitats.

Collin, Antoine; Long, Bernard; Archambault, Phillippe; Kuus, Pim; Clarke, John Hughes; Sohn, Gunbo; Miller, John (2007). Statistical classification methodology of SHOALS 3000 backscatter to mapping coastal benthic habitats. In: IEEE International Geoscience and Remote Sensing Symposium - IGARSS'07, 23-28 juillet 2007, Barcelone, Espagne.

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Résumé

The Scanning Hydrographic Operational Airborne LiDAR Survey (SHOALS) consists of a bathymetric LiDAR system which provides high precision measurements of water depth. Even though the acquisition is focused on depth accuracy, the return signal, i.e. waveform, contains other relevant information because of integration signatures from the water surface, the water column and the sea-bed. This paper highlights the benthic characterization in extracting statistical parameters derived from the bottom backscatter. In applying multivariate analysis (K-means), it is significantly proven that signals derived from habitat, described as statistically homogeneous throughout ground-truth analysis, are (1) similar within an intra-habitat view, while they are (2) different between themselves.

Type de document:	Document issu d'une conférence ou d'un atelier
Mots-clés libres:	bathymetric LiDAR; waveform; multivariate analysis; habitat classification
Centre:	Centre Eau Terre Environnement
Date de dépôt:	09 déc. 2019 21:09
Dernière modification:	09 déc. 2019 21:09
URI:	http://espace.inrs.ca/id/eprint/4761

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