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Assessment of very high spatial resolution satellite image segmentations / A.P. Carleer in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 11 (November 2005)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 71 n° 11 (November 2005) . - pp 1285 - 1294 Titre : Assessment of very high spatial resolution satellite image segmentations Type de document : Article/Communication Auteurs : A.P. Carleer, Auteur ; O. Debeir, Auteur ; E. Wolff, Auteur Année de publication : 2005 Article en page(s) : pp 1285 - 1294 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse comparative [Termes IGN] bruit (théorie du signal) [Termes IGN] contraste de couleurs [Termes IGN] image à résolution métrique [Termes IGN] image Ikonos [Termes IGN] image panchromatique [Termes IGN] segmentation d'image [Termes IGN] texture d'image Résumé : (Auteur) Since 1999, very high spatial resolution satellite data represent the surface of the Earth with more detail. However, information extraction by per pixel multispectral classification techniques proves to be very complex owing to the internal variability increase in land-cover units and to the weakness of spectral resolution. Image segmentation before classification was proposed as an alternative approach, but a large variety of segmentation algorithms were developed during the last 20 years, and a comparison of their implementation on very high spatial resolution images is necessary. In this study, four algorithms from the two main groups of segmentation algorithms (boundary-based and region-based) were evaluated and compared. In order to compare the algorithms, an evaluation of each algorithm was carried out with empirical discrepancy evaluation methods. This evaluation is carried out with a visual segmentation of Ikonos panchromatic images. The results show that the choice of parameters is very important and has a great influence on the segmentation results. The selected boundary-based algorithms are sensitive to the noise or texture. Better results are obtained with region-based algorithms, but a problem with the transition zones between the contrasted objects can be present. Numéro de notice : A2005-425 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.71.11.1285 En ligne : https://doi.org/10.14358/PERS.71.11.1285 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27561 [article]

Classifying and mapping wildfire severity: a comparison of methods / C.K. Brewer in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 11 (November 2005)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 71 n° 11 (November 2005) . - pp 1311 - 1320 Titre : Classifying and mapping wildfire severity: a comparison of methods Type de document : Article/Communication Auteurs : C.K. Brewer, Auteur ; J.C. Winne, Auteur ; et al., Auteur Année de publication : 2005 Article en page(s) : pp 1311 - 1320 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse comparative [Termes IGN] analyse en composantes principales [Termes IGN] cartographie des risques [Termes IGN] classification par réseau neuronal [Termes IGN] dommage matériel [Termes IGN] Etats-Unis [Termes IGN] image Landsat-TM [Termes IGN] image multitemporelle [Termes IGN] incendie de forêt [Termes IGN] méthode robuste [Termes IGN] réflectance Résumé : (Auteur) This study evaluates six different approaches to classifying and mapping fire severity using multi-temporal Landsat Thematic Mapper data. The six approaches tested include: two based on temporal image differencing and ratioing between pre-fire and post-fire images, two based on principal component analysis of pre- and post-fire imagery, and two based on artificial neural networks, one using just post-fire imagery and the other both pre- and post-fire imagery. Our results demonstrated the potential value for any of these methods to provide quantitative fire severity maps, but one of the image differencing methods (ND4/7) provided a flexible, robust, and analytically simple approach that could be applied anywhere in the Continental U.S. Based on the results of this test, the ND4/7 was implemented operationally to classify and map fire severity over 1.2 million hectares burned in the Northern Rocky Mountains and Northern Great Plains during the 2000 fire season, as well as the 2001 fire season (Gmelin and Brewer, 2002). Approximately the same procedure was adopted in 2001 by the USDA Forest Service, Remote Sensing Applications Center to produce Burned Area Reflectance Classifications for national-level support of Burned Area Emergency Rehabilitation activities (Orlemann, 2002). Numéro de notice : A2005-426 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.71.11.1311 En ligne : https://doi.org/10.14358/PERS.71.11.1311 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27562 [article]