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A volumetric approach to change in satellite images / T. Pollard in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 7 (July 2010)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 76 n° 7 (July 2010) . - pp 817 - 831 Titre : A volumetric approach to change in satellite images Type de document : Article/Communication Auteurs : T. Pollard, Auteur ; I. Eden, Auteur ; J. Mundy, Auteur ; D. Cooper, Auteur Année de publication : 2010 Article en page(s) : pp 817 - 831 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse de données [Termes IGN] apprentissage automatique [Termes IGN] détection de changement [Termes IGN] données localisées 3D [Termes IGN] image satellite [Termes IGN] modélisation géométrique de prise de vue [Termes IGN] pas d'échantillonnage au sol [Termes IGN] voxel [Termes IGN] zone urbaine dense Résumé : (Auteur) The increasing availability of very high resolution satellite imagery has spurred interest in automatically detecting very fine detailed changes in an area over time, a particularly useful tool for analyzing activity in dense urban areas. However, attempting automated change detection at this resolution is difficult due to the motion parallax of elevated structures. This paper presents a comprehensive solution to change detection in areas of significant 3D relief using a new framework called volumetric appearance modeling (VAM). This approach can manage the complications of unknown and changing world surfaces by maintaining a 3D voxel-based model, where probability distributions for surface occupancy and image appearance are stored in each voxel. These distributions are continuously updated as new images are received using an adaptive learning procedure. This representation is demonstrated to produce accurate change detection results under conditions of variable illumination and viewpoint as well as haze conditions present in satellite imagery. The volumetric representation also supports automatic sensor model correction to align incoming imagery to a common geographic reference. This registration approach is demonstrated to achieve geo-positioning accuracy on the order of the ground sampling distance (GSD) or better. Numéro de notice : A2010-274 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.76.7.817 En ligne : https://doi.org/10.14358/PERS.76.7.817 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30468 [article]

Evaluation of the influence of local fuel homogeneity on fire hazard through Landsat-5 TM texture measures / Cristina Vega-Garcia in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 7 (July 2010)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 76 n° 7 (July 2010) . - pp 853 - 864 Titre : Evaluation of the influence of local fuel homogeneity on fire hazard through Landsat-5 TM texture measures Type de document : Article/Communication Auteurs : Cristina Vega-Garcia, Auteur ; J. Taay-Nieto, Auteur ; R. Blanco, Auteur ; E. Chuvieco, Auteur Année de publication : 2010 Article en page(s) : pp 853 - 864 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse diachronique [Termes IGN] combustible [Termes IGN] image Landsat-TM [Termes IGN] incendie [Termes IGN] rayonnement lumineux [Termes IGN] rayonnement proche infrarouge [Termes IGN] risque naturel [Termes IGN] texture d'image Résumé : (Auteur) This study analyzed the relationship between landscape homogeneity and fire hazard for a certain area and time period (1984 to 1995), by using logit models. Homogeneity was measured though eight texture measurements computed on visible and NIR bands of Landstat-5 TM data with varying kernel sizes. Several significant models could be developed to predict future burning at the pixel level for the study period. The best spectral band for detecting proneness to burn was TM1, the blue band, and best results were achieved with large window sizes and the Homogeneity texture measure. Numéro de notice : A2010-275 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : doi.org/10.14358/PERS.76.7.853 En ligne : https://doi.org/10.14358/PERS.76.7.853 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30469 [article]