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Early fire detection using non-linear multi-temporal prediction of thermal imagery / A. Koltunov in Remote sensing of environment, vol 110 n° 1 (14/09/2007)  

Public [article]  inRemote sensing of environment > vol 110 n° 1 (14/09/2007) . - pp 18 - 28 Titre : Early fire detection using non-linear multi-temporal prediction of thermal imagery Type de document : Article/Communication Auteurs : A. Koltunov, Auteur ; S.L. Ustin, Auteur Année de publication : 2007 Article en page(s) : pp 18 - 28 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] analyse diachronique [Termes IGN] anomalie thermique [Termes IGN] détection de changement [Termes IGN] image multitemporelle [Termes IGN] image Terra-MODIS [Termes IGN] image thermique [Termes IGN] incendie de forêt [Termes IGN] prévention des risques Résumé : (Auteur) This paper presents a sub-pixel thermal anomaly detection method based on predicting background pixel intensities using a non-linear function of a plurality of past images of the inspected scene. At present, the multitemporal approach to thermal anomaly detection is in its early development stage. In case of space-borne surveillance the multitemporal detection is complicated by both spatial and temporal variability of background surface properties, weather influences, viewing geometries, sensor noise, residual misregistration, and other factors. We use the problem of fire detection and the MODIS data to demonstrate that advanced multitemporal detection methods can potentially outperform the operationally used optimized contextual algorithms both under morning and evening conditions. Copyright Elsevier Numéro de notice : A2007-348 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2007.02.010 En ligne : https://doi.org/10.1016/j.rse.2007.02.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28711 [article]