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Quantifying indicators of riparian condition in Australian tropical savannas: integrating high spatial resolution imagery and field survey data / K. Johansen in International Journal of Remote Sensing IJRS, vol 29 n°23 - 24 (December 2008)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 29 n°23 - 24 (December 2008) . - pp 7003 - 7028 Titre : Quantifying indicators of riparian condition in Australian tropical savannas: integrating high spatial resolution imagery and field survey data Type de document : Article/Communication Auteurs : K. Johansen, Auteur ; S. Phinn, Auteur ; J. Lowry, Auteur ; M. Douglas, Auteur Année de publication : 2008 Article en page(s) : pp 7003 - 7028 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse diachronique [Termes IGN] Australie [Termes IGN] carte d'occupation du sol [Termes IGN] carte de la végétation [Termes IGN] classification barycentrique [Termes IGN] classification dirigée [Termes IGN] classification orientée objet [Termes IGN] déchet organique [Termes IGN] détection de changement [Termes IGN] données de terrain [Termes IGN] image à très haute résolution [Termes IGN] image Quickbird [Termes IGN] indice de végétation [Termes IGN] rivière [Termes IGN] savane [Termes IGN] surveillance de la végétation Résumé : (Auteur) The objectives of this research were: (1) to quantify indicators of riparian condition; and (2) to assess these indicators for detecting change in riparian condition. Two multi-spectral QuickBird images were acquired in 2004 and 2005 for a section of the Daly River in north Australia. These data were collected coincidently with vegetation and geomorphic field data. Indicators of riparian condition, including percentage canopy cover, organic litter, canopy continuity, bank stability, flood damage, riparian zone width and vegetation overhang, were then mapped. Field measurements and vegetation indices were empirically related using regression analysis to develop algorithms for mapping organic litter and canopy cover (R 2 = 0.59-0.78). Using a standard nearest-neighbour algorithm, object-oriented supervised image classification provided thematic information (overall accuracies 81-90%) for mapping riparian zone width and vegetation overhang. Bank stability and flood damage were mapped empirically from a combination of canopy cover information and the image classification products (R 2 = 0.70-0.81). Multi-temporal image analysis of riparian condition indicators (RCIs) demonstrated the advantages of using continuous and discrete data values as opposed to categorical data. This research demonstrates how remote sensing can be used for mapping and monitoring riparian zones in remote tropical savannas and other riparian environments at scales from 1 km to 100s km of stream length. Copyright Taylor & Francis Numéro de notice : A2008-544 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160802220201 En ligne : https://doi.org/10.1080/01431160802220201 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29614 [article]

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Code-barres	Cote	Support	Localisation	Section	Disponibilité
080-08151	RAB	Revue	Centre de documentation	En réserve L003	Disponible