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Footprint size design of large-footprint full-waveform LiDAR for forest and topography applications: A theoretical study / Xuebo Yang in IEEE Transactions on geoscience and remote sensing, vol 59 n° 11 (November 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 59 n° 11 (November 2021) . - pp 9745 - 9757 Titre : Footprint size design of large-footprint full-waveform LiDAR for forest and topography applications: A theoretical study Type de document : Article/Communication Auteurs : Xuebo Yang, Auteur ; Cheng Wang, Auteur ; Xiaohuan Xi, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 9745 - 9757 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] empreinte [Termes IGN] extraction de la végétation [Termes IGN] forme d'onde pleine [Termes IGN] hauteur des arbres [Termes IGN] lidar à retour d'onde complète [Termes IGN] onde lidar [Termes IGN] processus gaussien [Termes IGN] signal lidar Résumé : (auteur) LiDAR footprint, defined as the illumination area of LiDAR sensor on the ground, is the fundamental unit that the sensor collects information from. The design of footprint size crucially influences the acquired LiDAR signals. For large-footprint full-waveform LiDAR, a well-designed footprint size is indispensable to acquire accurate and complete vertical profiles of scene targets. The methods that design the footprint size are increasingly needed to satisfy various application requirements. In this study, an analytical method to designing the footprint size is proposed for forest and topography applications. It is established based on a mixture Gaussian model and the designed footprint size ensures the signals of vegetation and ground can be completely extracted. Experiment results with our method show that the footprint size is preferably in the range of 10.6–25.0 m for forest application, while it is less than 32.3 m for topography application. The intersection of the two sets satisfies both applications. Furthermore, a series of sensibility studies were performed to analyze the influence of multiple key parameters to the optimal footprint size, including the scene characteristics, instrumental configurations, and application requirements. This study provides a theoretical basis for the design of future large-footprint full-waveform laser altimeters. Numéro de notice : A2021-812 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2021.3054324 Date de publication en ligne : 08/02/2021 En ligne : https://doi.org/10.1109/TGRS.2021.3054324 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98885 [article]

A wavelet-based echo detector for waveform LiDAR data / Cheng-Kai Wang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 2 (February 2016)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 54 n° 2 (February 2016) . - pp 757 - 769 Titre : A wavelet-based echo detector for waveform LiDAR data Type de document : Article/Communication Auteurs : Cheng-Kai Wang, Auteur ; Yi-Hsing Tseng, Auteur ; Chi-Kuei Wang, Auteur Année de publication : 2016 Article en page(s) : pp 757 - 769 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] forme d'onde [Termes IGN] modèle numérique de surface [Termes IGN] onde lidar [Termes IGN] ondelette [Termes IGN] semis de points [Termes IGN] signal laser Résumé : (Auteur) This paper presents a wavelet-based (WB) echo detector that can recover the echoes missed by a light detection and ranging (LiDAR) system via on-the-fly detection. An on-the-fly detection method normally utilizes a simple threshold (TH) to register a target point. Points that belong to weak and/or overlapping echoes are much complicated and are easily missed by TH approaches. The proposed detector based on wavelet transformation is robust to noise and is capable of resolving overlapping echoes. It is thus expected to be good at handling missing echoes. A simulated waveform data set and a real waveform data set of a forest area were both used in this paper. The simulated waveform data were utilized to compare the proposed detector with zero crossing (ZC) and Gaussian decomposition (GD) detectors in terms of their ability to deal with weak or overlapping echoes. The real waveform data set acquired from Leica ALS60 was used to demonstrate a WB algorithm for exploring the missing echoes. Experiments using the simulated data showed that the WB and GD detectors are superior to the ZC detector in finding overlapping echoes. The WB algorithm performs well when dealing with overlapping echoes with a low signal-to-noise ratio. Experiments using the real waveform data show that 31.5% additional weak or overlapping echoes can be detected by the WB detector compared with the point cloud provided by the system. With such additional points, the mean and root-mean-square errors of the digital elevation model differences can be improved from 0.72 and 0.79 m to 0.16 and 0.59 m, respectively. Numéro de notice : A2016-119 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2465148 En ligne : https://doi.org/10.1109/TGRS.2015.2465148 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79999 [article]

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Code-barres	Cote	Support	Localisation	Section	Disponibilité
065-2016021	SL	Revue	Centre de documentation	Revues en salle	Disponible

Fusion of waveform LiDAR data and hyperspectral imagery for land cover classification / Hongzhou Wang in ISPRS Journal of photogrammetry and remote sensing, vol 108 (October 2015)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 108 (October 2015) . - pp 1 - 11 Titre : Fusion of waveform LiDAR data and hyperspectral imagery for land cover classification Type de document : Article/Communication Auteurs : Hongzhou Wang, Auteur ; Craig L. Glennie, Auteur Année de publication : 2015 Article en page(s) : pp 1 - 11 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] classification par maximum de vraisemblance [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] données lidar [Termes IGN] extraction de traits caractéristiques [Termes IGN] forme d'onde pleine [Termes IGN] fusion d'images [Termes IGN] fusion de données [Termes IGN] image hyperspectrale [Termes IGN] occupation du sol [Termes IGN] onde lidar [Termes IGN] semis de points [Termes IGN] superposition d'images [Termes IGN] voxel Résumé : (auteur) Current research into the fusion of hyperspectral imagery (HI) and full waveform LiDAR (Light Detection And Ranging) has relied on first processing the full waveform LiDAR (FWL) data to a set of discrete returns before merging because the data structure and sampling interval of HI and FWL are distinctly different. However, additional information about target properties can potentially be recovered if the waveform shape is preserved in the fusion process. This paper proposes a “voxelization” method to register FWL data to HI by dividing the waveform data into voxels, and then synthesizing all waveforms which intersect a voxel column into one three-dimensional superposition waveform: the synthesized waveform (SWF). A vertical energy distribution coefficients (VEDC) feature is proposed for extracting features from SWF, and then the SWF and HI are fused to form a complete feature space for classification. A pairwise classifier was adapted and completed using both Maximum Likelihood and Support Vector Machine classifiers for the combined SWF/HI features. Results show that this method of generating SWF from FWL data can effectively preserve information from the original waveforms, and the fusion of SWF and HI enhanced land cover classification compared to both using either data set alone or the merging of HI with a discrete LiDAR return point cloud. Numéro de notice : A2015-848 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.05.012 Date de publication en ligne : 23/06/2015 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2015.05.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79218 [article]

Empirical waveform decomposition and radiometric calibration of a terrestrial full-waveform laser scanner / Preston J. Hartzell in IEEE Transactions on geoscience and remote sensing, vol 53 n° 1 (January 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 1 (January 2015) . - pp 162 - 172 Titre : Empirical waveform decomposition and radiometric calibration of a terrestrial full-waveform laser scanner Type de document : Article/Communication Auteurs : Preston J. Hartzell, Auteur ; Craig L. Glennie, Auteur ; David C. Finnegan, Auteur Année de publication : 2015 Article en page(s) : pp 162 - 172 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] décomposition [Termes IGN] données lidar [Termes IGN] étalonnage de capteur (imagerie) [Termes IGN] étalonnage radiométrique [Termes IGN] forme d'onde pleine [Termes IGN] instrumentation Riegl [Termes IGN] Lidar [Termes IGN] méthode des moindres carrés [Termes IGN] modèle empirique [Termes IGN] onde lidar [Termes IGN] télémètre laser terrestre Résumé : (Auteur) The parametric models used in Light Detection And Ranging (LiDAR) waveform decomposition routines are inherently estimates of the sensor's system response to backscattered laser pulse power. This estimation can be improved with an empirical system response model, yielding reduced waveform decomposition residuals and more precise echo ranging. We develop an empirical system response model for a Riegl VZ-400 terrestrial laser scanner, from a series of observations to calibrated reflectance targets, and present a numerical least squares method for decomposing waveforms with the model. The target observations are also used to create an empirical radiometric calibration model that accommodates a nonlinear relationship between received optical power and echo peak amplitude, and to examine the temporal stability of the instrument. We find that the least squares waveform decomposition based on the empirical system response model decreases decomposition fitting errors by an order of magnitude for high-amplitude returns and reduces range estimation errors on planar surfaces by 17% over a Gaussian model. The empirical radiometric calibration produces reflectance values self-consistent to within 5% for several materials observed at multiple ranges, and analysis of multiple calibration data sets collected over a one-year period indicates that echo peak amplitude values are stable to within ±3% for target ranges up to 125 m. Numéro de notice : A2015-040 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2320134 En ligne : https://doi.org/10.1109/TGRS.2014.2320134 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75122 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
065-2015011	RAB	Revue	Centre de documentation	En réserve L003	Disponible

An accurate and computationally efficient algorithm for ground peak identification in large footprint waveform LiDAR data / Wei Zhuang in ISPRS Journal of photogrammetry and remote sensing, vol 95 (September 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 95 (September 2014) . - pp 81 – 92 Titre : An accurate and computationally efficient algorithm for ground peak identification in large footprint waveform LiDAR data Type de document : Article/Communication Auteurs : Wei Zhuang, Auteur ; Giorgos Mountrakis, Auteur Année de publication : 2014 Article en page(s) : pp 81 – 92 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] empreinte [Termes IGN] filtrage numérique d'image [Termes IGN] forêt [Termes IGN] forme d'onde [Termes IGN] groupe [Termes IGN] identification automatique [Termes IGN] onde lidar [Termes IGN] surface du sol [Termes IGN] télémétrie laser aéroporté [Termes IGN] traitement de données Résumé : (Auteur) Large footprint waveform LiDAR sensors have been widely used for numerous airborne studies. Ground peak identification in a large footprint waveform is a significant bottleneck in exploring full usage of the waveform datasets. In the current study, an accurate and computationally efficient algorithm was developed for ground peak identification, called Filtering and Clustering Algorithm (FICA). The method was evaluated on Land, Vegetation, and Ice Sensor (LVIS) waveform datasets acquired over Central NY. FICA incorporates a set of multi-scale second derivative filters and a k-means clustering algorithm in order to avoid detecting false ground peaks. FICA was tested in five different land cover types (deciduous trees, coniferous trees, shrub, grass and developed area) and showed more accurate results when compared to existing algorithms. More specifically, compared with Gaussian decomposition, the RMSE ground peak identification by FICA was 2.82 m (5.29 m for GD) in deciduous plots, 3.25 m (4.57 m for GD) in coniferous plots, 2.63 m (2.83 m for GD) in shrub plots, 0.82 m (0.93 m for GD) in grass plots, and 0.70 m (0.51 m for GD) in plots of developed areas. FICA performance was also relatively consistent under various slope and canopy coverage (CC) conditions. In addition, FICA showed better computational efficiency compared to existing methods. FICA’s major computational and accuracy advantage is a result of the adopted multi-scale signal processing procedures that concentrate on local portions of the signal as opposed to the Gaussian decomposition that uses a curve-fitting strategy applied in the entire signal. The FICA algorithm is a good candidate for large-scale implementation on future space-borne waveform LiDAR sensors. Numéro de notice : A2014-474 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.06.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.06.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74051 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2014091	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Etude des couverts forestiers par inversion de formes d'onde Lidar à l'aide du modèle de transfert radiatif DART développé par le CESBIO / A. Ueberschlag in XYZ, n° 126 (mars - mai 2011) 

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Utilisation conjointe de trains d'onde Lidar vert et infrarouge pour la bathymétrie des eaux de très faibles profondeurs / Tristan Allouis in Revue Française de Photogrammétrie et de Télédétection, n° 191 (Mai 2010)

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Analyse de données lidar à retour d'onde complète pour la classification en milieu urbain = Analysis of Full-Waveform lidar data for urban area mapping / Clément Mallet (2010)  

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