(Article of periodic en Anglais - 2009)

Document title

An object extraction approach for impervious surface classification with very-high-resolution imagery

Authors(s) and Affiliation(s)

MILLER J.E. (1) ; NELSON S.A.C. (2) ; HESS G.R. (2) ;
(1) Univ. Texas, ETATS-UNIS
(2) North Carolina State Univ., ETATS-UNIS


Widespread availability of aerial photography provides increased accessibility of high-resolution imagery and the potential to produce high-accuracy land cover classifications. However, these classifications often require expert knowledge and are time consuming. The aim of this study was to develop an efficient, acurate technique for classifying impervious surface in urbanizing Wake County, North Carolina. Using an iterative technique, the AA. classified 111 nonmosaicked, very-high-resolution images using the Feature Analyst software developed by Visual Learning Systems. Feature Analyst provides object extraction classifications by analyzing spatial context in relation to spectral data to classify high-resolution imagery. Using this method, users with relatively limited geographic information system (GIS) training and modest budgets can produce highly acurate object-extracted classifications of impervious and pervious surface that are easily manipulated in a GIS


Article of periodic

published at : The Professional geographer / ISSN 0033-0124

Editor : Blackwell, Cambridge, MA - ETATS-UNIS (1946)

Millesime : 2009, vol. 61, no2 [pp. 250-264]

Bibliographic references : 2 p.

Collation : 4 fig., 3 tabl.




Tous droits réservés © Prodig - Bibliographie Géographique Internationale (BGI), 2009
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