Exploitation of very high resolution satellite data for tree species identification
Identifieur interne : 000B59 ( Main/Exploration ); précédent : 000B58; suivant : 000B60Exploitation of very high resolution satellite data for tree species identification
Auteurs : A. Carleer [Belgique] ; E. Wolff [Belgique]Source :
- Photogrammetric engineering and remote sensing [ 0099-1112 ] ; 2004.
Descripteurs français
- Pascal (Inist)
- Wicri :
- geographic : Belgique.
- topic : Arbre, Forêt, Classification.
English descriptors
- KwdEn :
Abstract
With the emergence of very high spatial resolution satellite images, the spatial resolution gap which existed between satellite images and aerial photographs has decreased. A study of the potential of these images for tree species in "monoculture stands" identification was conducted. Two Ikonos images were acquired, one in June 2000 and the other in October 2000, for an 11- by 11-km area covering the Sonian Forest in the southeastern part of the Brussels-Capital region (Belgium). The two images were orthorectified using a digital elevation model and 1256 geodetic control points. The identification of the tree species was carried out utilizing a supervised maximum-likelihood classification on a pixel-by-pixel basis. Classifications were performed on the orthorectified data, NDVI transformed data, and principal components imagery. In order to decrease the intraclass variance, a mean filter was applied to all the spectral bands and neo-channels used in the classification process. Training and validation areas were selected and digitized using detailed geographical databases of the tree species. The selection of the relevant bands and neo-channels was carried out by successive addition of information in order to improve the classification results. Seven different tree species of one to two different age classes were identified with an overall accuracy of 86 percent. The seven identified tree species or species groups are Oaks (Quercus sp.), Beech (Fagus sylvatica L.), Purple Beech (Fagus sylvatica purpurea), Douglas Fir (Pseudotsuga menziesii (Mirb.) Franco), Scots Pine (Pinus sylvestris L.), Corsican Pine (Pinus nigra Arn. subsp. laricio (Poir.) Maire var. corsican), and Larch (Larix decidua Mill.).
Affiliations:
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Wolff</name><affiliation wicri:level="4"><inist:fA14 i1="01"><s1>Institut de Gestion de l'Environnement et d'Aménagement du Territoire, Université Libre de Bruxelles, CP 130/02, 50 av. F. 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Carleer</name><affiliation wicri:level="4"><inist:fA14 i1="01"><s1>Institut de Gestion de l'Environnement et d'Aménagement du Territoire, Université Libre de Bruxelles, CP 130/02, 50 av. F. Roosevelt</s1><s2>1050 Brussels</s2><s3>BEL</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ></inist:fA14><country>Belgique</country><placeName><region type="land" nuts="2">Vienne (Autriche)</region><settlement type="city">Vienne (Autriche)</settlement></placeName><orgName type="university">Université libre de Bruxelles</orgName></affiliation></author><author><name sortKey="Wolff, E" sort="Wolff, E" uniqKey="Wolff E" first="E." last="Wolff">E. Wolff</name><affiliation wicri:level="4"><inist:fA14 i1="01"><s1>Institut de Gestion de l'Environnement et d'Aménagement du Territoire, Université Libre de Bruxelles, CP 130/02, 50 av. F. Roosevelt</s1><s2>1050 Brussels</s2><s3>BEL</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ></inist:fA14><country>Belgique</country><placeName><region type="land" nuts="2">Vienne (Autriche)</region><settlement type="city">Vienne (Autriche)</settlement></placeName><orgName type="university">Université libre de Bruxelles</orgName></affiliation></author></analytic><series><title level="j" type="main">Photogrammetric engineering and remote sensing</title><title level="j" type="abbreviated">Photogramm. eng. remote sensing</title><idno type="ISSN">0099-1112</idno><imprint><date when="2004">2004</date></imprint></series></biblStruct></sourceDesc><seriesStmt><title level="j" type="main">Photogrammetric engineering and remote sensing</title><title level="j" type="abbreviated">Photogramm. eng. remote sensing</title><idno type="ISSN">0099-1112</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Belgium</term><term>Fagus</term><term>Larix</term><term>Pinus</term><term>Pixel</term><term>Pseudotsuga</term><term>Quercus</term><term>Space remote sensing</term><term>accuracy</term><term>aerial photography</term><term>channels</term><term>classification</term><term>forests</term><term>identification</term><term>imagery</term><term>maximum likelihood</term><term>models</term><term>spatial resolution</term><term>trees</term><term>vegetation</term><term>very high resolution</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>Belgique</term><term>Télédétection spatiale</term><term>Très haute résolution</term><term>Végétation</term><term>Identification</term><term>Arbre</term><term>Résolution spatiale</term><term>Photographie aérienne</term><term>Forêt</term><term>Modèle</term><term>Maximum vraisemblance</term><term>Classification</term><term>Pixel</term><term>Imagerie</term><term>Chenal</term><term>Précision</term><term>Quercus</term><term>Fagus</term><term>Pseudotsuga</term><term>Pinus</term><term>Larix</term></keywords><keywords scheme="Wicri" type="geographic" xml:lang="fr"><term>Belgique</term></keywords><keywords scheme="Wicri" type="topic" xml:lang="fr"><term>Arbre</term><term>Forêt</term><term>Classification</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">With the emergence of very high spatial resolution satellite images, the spatial resolution gap which existed between satellite images and aerial photographs has decreased. A study of the potential of these images for tree species in "monoculture stands" identification was conducted. Two Ikonos images were acquired, one in June 2000 and the other in October 2000, for an 11- by 11-km area covering the Sonian Forest in the southeastern part of the Brussels-Capital region (Belgium). The two images were orthorectified using a digital elevation model and 1256 geodetic control points. The identification of the tree species was carried out utilizing a supervised maximum-likelihood classification on a pixel-by-pixel basis. Classifications were performed on the orthorectified data, NDVI transformed data, and principal components imagery. In order to decrease the intraclass variance, a mean filter was applied to all the spectral bands and neo-channels used in the classification process. Training and validation areas were selected and digitized using detailed geographical databases of the tree species. The selection of the relevant bands and neo-channels was carried out by successive addition of information in order to improve the classification results. Seven different tree species of one to two different age classes were identified with an overall accuracy of 86 percent. The seven identified tree species or species groups are Oaks (Quercus sp.), Beech (Fagus sylvatica L.), Purple Beech (Fagus sylvatica purpurea), Douglas Fir (Pseudotsuga menziesii (Mirb.) Franco), Scots Pine (Pinus sylvestris L.), Corsican Pine (Pinus nigra Arn. subsp. laricio (Poir.) Maire var. corsican), and Larch (Larix decidua Mill.).</div></front></TEI><affiliations><list><country><li>Belgique</li></country><region><li>Vienne (Autriche)</li></region><settlement><li>Vienne (Autriche)</li></settlement><orgName><li>Université libre de Bruxelles</li></orgName></list><tree><country name="Belgique"><region name="Vienne (Autriche)"><name sortKey="Carleer, A" sort="Carleer, A" uniqKey="Carleer A" first="A." last="Carleer">A. Carleer</name></region><name sortKey="Wolff, E" sort="Wolff, E" uniqKey="Wolff E" first="E." last="Wolff">E. Wolff</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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