inscription
PORTAIL D'INFORMATION GÉOGRAPHIQUE

Supervised classification of types of glaciated landscapes using digital elevation data

Special issue. Application of remote sensing and GIS in geomorphology

Auteurs :
BROWN, D.G.
LUSCH, D.P.
DUDA, K.A.
BUTLER, D.R.

Description :
Automated approaches for identifying different types of glaciated landscapes using digitally processed elevation data were evaluated. The AA. tested the ability of geomorphic measures (elevation, relative relief, roughness, and slope gradient) derived from digital elevation models (DEMs) to differentiate glaciated landscapes using maximum likelihood classification and artificial neural networks (ANN). The automated methods were trained and validated using an existing Quaternary geology map and a manual interpretation of the contour data portrayed on topographic quadrangles. The need for such methods arises from efforts to classify types of landscapes (e.g. ecoregions) in Michigan.


Type de document :
Article de monographie

Source :
Geomorphology (Amsterdam), issn : 0169-555X, 1998, vol. 21, n°. 3-4, p. 233-250, Collation : Illustration, Références bibliographiques : 2 p.

Date :
1998

Editeur :
Pays édition : Pays-Bas, Amsterdam, Elsevier

Langue :
Anglais
Droits :
Tous droits réservés © Prodig - Bibliographie Géographique Internationale (BGI)