Automated extraction of plantations from ikonos satellite imagery using a level set based segmentation method

verfasst von

Karsten Vogt, Björn Scheuermann, Christian Becker, Torsten Büschenfeld, Bodo Rosenhahn, Jörn Ostermann

Abstract

In this article we present a method that extracts plantations from satellite imagery by finding and exploiting appropriate feature space projections. Segmentation is done using an automatic two-region segmentation based on the level set method. The behaviour of this algorithm is defined by a statistical region model that describes the similarity of regions using distances in arbitrary feature spaces. Subsequently different feature spaces will be evaluated regarding their plantation classification quality in an automatic fashion. The segmentation quality of our method is assessed by testing several orthophotos depicting a wide range of landscape types and comparing them with a manual segmentation. We show that a combination of simple texture based features like the structure tensor and the Hessian matrix are sufficient to facilitate an effective plantation segmentation scheme.

Organisationseinheit(en)

Institut für Informationsverarbeitung

Typ

Konferenzaufsatz in Fachzeitschrift

Journal

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

Band

38

Seiten

275-280

Anzahl der Seiten

6

ISSN

1682-1750

Publikationsdatum

2010

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Information systems, Geografie, Planung und Entwicklung

Ziele für nachhaltige Entwicklung

SDG 15 – Lebensraum Land