Supervised classification of types of glaciated landscapes using digital elevation data
published at : Special issue. Application of remote sensing and GIS in geomorphology
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
published at : Geomorphology / ISSN 0169-555X
Editor : Elsevier, Amsterdam - PAYS-BAS (1987)
Millesime : 1998, vol. 21, no 3-4 [pp. 233-250]
Bibliographic references : 2 p.
INIST-CNRS, Cote INIST : 21151