Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 275-280 |
| Seitenumfang | 6 |
| Fachzeitschrift | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives |
| Jahrgang | 38 |
| Publikationsstatus | Veröffentlicht - 2010 |
| Veranstaltung | ISPRS Technical Commission VII Symposium on Advancing Remote Sensing Science - Vienna, Österreich Dauer: 5 Juli 2010 → 7 Juli 2010 |
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.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Information systems
- Sozialwissenschaften (insg.)
- Geografie, Planung und Entwicklung
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in: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, Jahrgang 38, 2010, S. 275-280.
Publikation: Beitrag in Fachzeitschrift › Konferenzaufsatz in Fachzeitschrift › Forschung › Peer-Review
}
TY - JOUR
T1 - Automated extraction of plantations from ikonos satellite imagery using a level set based segmentation method
AU - Vogt, Karsten
AU - Scheuermann, Björn
AU - Becker, Christian
AU - Büschenfeld, Torsten
AU - Rosenhahn, Bodo
AU - Ostermann, Jörn
PY - 2010
Y1 - 2010
N2 - 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.
AB - 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.
KW - Automation
KW - GIS
KW - Land use
KW - Segmentation
KW - Vegetation
UR - http://www.scopus.com/inward/record.url?scp=84923916827&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:84923916827
VL - 38
SP - 275
EP - 280
JO - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
JF - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
SN - 1682-1750
T2 - ISPRS Technical Commission VII Symposium on Advancing Remote Sensing Science
Y2 - 5 July 2010 through 7 July 2010
ER -