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Pan-European forest/non forest mapping with Landsat ETM+ and Corine Land Cover 2000 data / A. Pekkarinen in ISPRS Journal of photogrammetry and remote sensing, vol 64 n° 2 (March - April 2009)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 64 n° 2 (March - April 2009) . - pp 171 - 183 Titre : Pan-European forest/non forest mapping with Landsat ETM+ and Corine Land Cover 2000 data Type de document : Article/Communication Auteurs : A. Pekkarinen, Auteur ; L. Reithmaier, Auteur ; Peter Strobl, Auteur Année de publication : 2009 Article en page(s) : pp 171 - 183 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse comparative [Termes IGN] analyse de groupement [Termes IGN] analyse spectrale [Termes IGN] carte d'occupation du sol [Termes IGN] classification barycentrique [Termes IGN] classification dirigée [Termes IGN] Corine Land Cover [Termes IGN] Europe (géographie politique) [Termes IGN] forêt [Termes IGN] image Landsat-ETM+ [Termes IGN] segmentation d'image Résumé : (Auteur) This paper describes a simple and adaptive methodology for large area forest/non-forest mapping using Landsat ETM+ imagery and CORINE Land Cover 2000. The methodology is based on scene-by-scene analysis and supervised classification. The fully automated processing chain consists of several phases, including image segmentation, clustering, adaptive spectral representativity analysis, training data extraction and nearest-neighbour classification. This method was used to produce a European forest/non-forest map through the processing of 415 Landsat ETM+ scenes. The resulting forest/non-forest map was validated with three independent data sets. The results show that the map’s overall point-level agreement with our validation data generally exceeds 80%, and approaches 90% in central European conditions. Comparison with country-level forest area statistics shows that in most cases the difference between the forest proportion of the derived map and that computed from the published forest area statistics is below 5%. Copyright ISPRS Numéro de notice : A2009-096 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2008.09.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2008.09.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29726 [article]

Exemplaires(2)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-09021	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-09022	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Performance of different spectral and textural photograph features in multi-source forest inventory / Sakari Tuominen in Remote sensing of environment, vol 94 n° 2 (30/01/2005)  

Public [article]  inRemote sensing of environment > vol 94 n° 2 (30/01/2005) . - pp 256 - 268 Titre : Performance of different spectral and textural photograph features in multi-source forest inventory Type de document : Article/Communication Auteurs : Sakari Tuominen, Auteur ; A. Pekkarinen, Auteur Année de publication : 2005 Article en page(s) : pp 256 - 268 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] classification barycentrique [Termes IGN] forêt [Termes IGN] image à moyenne résolution [Termes IGN] image Landsat-TM [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] photographie aérienne [Termes IGN] photographie infrarouge [Termes IGN] photographie numérique [Termes IGN] signature spectrale [Termes IGN] texture d'image Résumé : (Auteur) Most multi-source forest inventory (MSFI) applications have thus far been based on the use of medium resolution satellite imagery, such as Landsat TM. The high plot and stand level estimation errors of these applications have, however, restricted their use in forest management planning. One reason suggested for the high estimation errors has been the coarse spatial resolution of the imagery employed. Therefore, very high spatial resolution (VHR) imagery sources provide interesting data for stand-level inventory applications. However, digital interpretation of VHR imagery, such as aerial photographs, is more complicated than the use of traditional satellite imagery. Pixel-by-pixel analysis is not applicable to VHR imagery because a single pixel is small in relation to the object of interest, i.e. a forest stand, and therefore it does not adequately represent the spectral properties of a stand. Additionally in aerial photographs, the spectral properties of the objects are dependent on their location in the image. Therefore, MSFI applications based on aerial imagery must employ features that are less sensitive to their location in the image and that have been derived using the spatial neighborhood of each pixel, e.g. a square-shaped window of pixels. In this experiment several spectral and textural features were extracted from color-infrared aerial photographs and employed in estimation of forest attributes. The features were extracted from original, normalized difference vegetation index and channel ratio images. The correlations between the extracted image features and forest attributes measured from sample plots were examined. Additionally, the spectral and textural features were used for estimating the forest attributes of sample plots, applying the k nearest neighbor estimation method. The results show that several spectral and textural image features that are moderately or well correlated with the forest attributes. Furthermore, the accuracy of forest attribute estimation can be significantly improved by a careful selection of image features. Numéro de notice : A2005-015 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2004.10.001 En ligne : https://doi.org/10.1016/j.rse.2004.10.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27154 [article]