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Seeing the trees in the forest: Using Lidar and multispectral data fusion with local filtering and variable window size for estimating tree height / S.C. Pospecu in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 5 (May 2004)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 70 n° 5 (May 2004) . - pp 589 - 604 Titre : Seeing the trees in the forest: Using Lidar and multispectral data fusion with local filtering and variable window size for estimating tree height Type de document : Article/Communication Auteurs : S.C. Pospecu, Auteur ; R. Wynne, Auteur Année de publication : 2004 Article en page(s) : pp 589 - 604 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] couvert forestier [Termes IGN] données lidar [Termes IGN] estimation statistique [Termes IGN] feuillu [Termes IGN] fusion d'images [Termes IGN] hauteur des arbres [Termes IGN] identification automatique [Termes IGN] image multibande [Termes IGN] modèle de régression [Termes IGN] Pinus (genre) Résumé : (Auteur) The main study objective was to develop robust processing and analysis techniques to facilitate the use of small-footprint lidar data for estimating plot-level tree height by measuring individual trees identifiable on the three-dimensional lidar surface. Lidar processing techniques included data fusion with multispectral optical data and local filtering with both square and circular windows of variable size. The lidar system used for this study produced an average footprint of 0.65 m and an average distance between laser shots of 0.7 m. The lidar data set was acquired over deciduous and coniferous stands with settings typical of the southeastern United States. The lidar-derived tree measurements were used with regression models and cross-validation to estimate tree height on 0.017-ha plots. For the pine plots, lidar measurements explained 97 percent of the variance associated with the mean height of dominant trees. For deciduous plots, regression models explained 79 percent of the mean height variance for dominant trees. Filtering for local maximum with circular windows gave better fitting models for pines, while for deciduous trees, filtering with square windows provided a slightly better model fit. Using lidar and optical data fusion to differentiate between forest types provided better results for estimating average plot height for pines. Estimating tree height for deciduous plots gave superior results without calibrating the search window size based on forest type. Numéro de notice : A2004-181 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.70.5.589 En ligne : https://doi.org/10.14358/PERS.70.5.589 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26708 [article]