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Decomposition of laser altimeter waveforms / M.A. Hofton in IEEE Transactions on geoscience and remote sensing, vol 38 n° 4 Tome 2 (july 2000)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 38 n° 4 Tome 2 (july 2000) . - pp 1989 - 1996 Titre : Decomposition of laser altimeter waveforms Type de document : Article/Communication Auteurs : M.A. Hofton, Auteur ; J.B. Minster, Auteur ; J.B. Blair, Auteur Année de publication : 2000 Article en page(s) : pp 1989 - 1996 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] approximation [Termes IGN] Californie (Etats-Unis) [Termes IGN] décomposition de Gauss [Termes IGN] données laser [Termes IGN] données localisées 3D [Termes IGN] forêt [Termes IGN] lasergrammétrie [Termes IGN] onde [Termes IGN] optimisation (mathématiques) Résumé : (Auteur) We develop a method to decompose a laser altimeter return waveform into a series of components assuming that the position of each component within the waveform can be used to calculate the mean elevation of a specific reflecting surface within the laser footprint. For simplicity, they assume each component is Gaussian in nature. They estimate the number of Gaussian components from the number of inflection points of a smoothed copy of the laser waveform and obtain initial estimates of the Gaussian half-widths and positions from the positions of its consecutive inflection points. Initial amplitude estimates are obtained using a nonnegative least-squares method (LSM). To reduce the likelihood of fitting the background noise within the waveform and to minimize the number of Gaussians needed in the approximation, we rank the “importance” of each Gaussian in the decomposition using its initial half-width and amplitude estimates. The initial parameter estimates of all Gaussians ranked “important” are optimized using the Levenburg-Marquardt method. If the sum of the Gaussians does not approximate the return waveform to a prescribed accuracy, then additional Gaussians can be included in the optimization procedure or initial parameters can be recalculated. The Gaussian decomposition method is demonstrated on data collected by the airborne laser vegetation imaging sensor (LVIS) in October 1997 over the Sequoia National Forest, California. Copyright IEEE Numéro de notice : A2000-273 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/36.851780 En ligne : https://doi.org/10.1109/36.851780 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26397 [article]

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