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Airborne LiDAR and high resolution multispectral data integration in Eucalyptus tree species mapping in an Australian farmscape / Niva Kiran Verma in Geocarto international, vol 37 n° 1 ([01/01/2022])  

Public [article]  inGeocarto international > vol 37 n° 1 [01/01/2022] . - pp 70 - 90 Titre : Airborne LiDAR and high resolution multispectral data integration in Eucalyptus tree species mapping in an Australian farmscape Type de document : Article/Communication Auteurs : Niva Kiran Verma, Auteur ; David Lamb, Auteur ; Priyakant Sinha, Auteur Année de publication : 2022 Article en page(s) : pp 70 - 90 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] Australie [Termes IGN] carte de la végétation [Termes IGN] dépérissement [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] Eucalyptus (genre) [Termes IGN] image à haute résolution [Termes IGN] image multibande [Termes IGN] précision de la classification [Termes IGN] segmentation d'image [Termes IGN] semis de points Résumé : (auteur) Rapid decline and death of rural Eucalypts trees of all ages and species have been reported in the farmscapes of regional Australia due to various environmental and farming management related factors. The identification of existing farm tree species is important for long term management strategies to provide ecosystem stability in the region. This study explored the feasibility of structural attributes of LiDAR and spectral and spatial characteristics of high resolution remote sensing data to identify and map Eucalyptus tree species. An object based image segmentation and rule-based classification algorithm were developed to delineate tree boundaries and species classification. The integration of two datasets improved the classification accuracy (65%) against their separate classification (52% and 41%, respectively). The identification of tree species will help in getting first-hand information on existing farm trees, which may be used in assessing tree condition in time series related to management practices and complex dieback problem. Numéro de notice : A2022-046 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1700555 Date de publication en ligne : 12/12/2019 En ligne : https://doi.org/10.1080/10106049.2019.1700555 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99412 [article]

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