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Auteur Mary Pyott Freeman |
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Object-based image mapping of conifer tree mortality in San Diego county based on multitemporal aerial ortho-imagery / Mary Pyott Freeman in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 7 (juillet 2016)
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Titre : Object-based image mapping of conifer tree mortality in San Diego county based on multitemporal aerial ortho-imagery Type de document : Article/Communication Auteurs : Mary Pyott Freeman, Auteur ; Douglas A. Stow, Auteur ; Dar A. Roberts, Auteur Année de publication : 2016 Article en page(s) : pp 571 - 580 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] arbre mort
[Termes IGN] carte de la végétation
[Termes IGN] classification dirigée
[Termes IGN] classification par réseau neuronal
[Termes IGN] image aérienne
[Termes IGN] image multitemporelle
[Termes IGN] orthoimage
[Termes IGN] Pinophyta
[Termes IGN] San DiegoRésumé : (Auteur) Two GEOBIA approaches are compared for their effectiveness in mapping dead trees within island montane forests of Southern California: a spatial contextual approach using an artificial neural network classifier, and a segmentation and multi-pixel classification approach. Both approaches are tested with multitemporal aerial orthoimagery having varying spatial resolutions. Spectral transformation inputs are also tested. An object-based accuracy assessment is conducted. Accuracies range between 30 percent to 90 percent for the dead tree class and are significantly higher for the spatial-contextual approach. Inclusion of spectral transforms increased accuracies by 5 percent for the true object-based approach, up to 13 percent for the spatial contextual approach, and reduced commission error up to 10 percent for both approaches. Masking techniques increased accuracies of the spatial contextual approach by 20 percent. With manual editing, the most accurate maps of individual live and dead trees from the spatial contextual approach are suitable for studying spatio-temporal trends in montane conifer mortality. Numéro de notice : A2016-518 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.82.7.571 En ligne : http://dx.doi.org/10.14358/PERS.82.7.571 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81589
in Photogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 7 (juillet 2016) . - pp 571 - 580[article]