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Estimation of lidar-based gridded DEM uncertainty with varying terrain roughness and point density / Luyen K. Bui in ISPRS Open Journal of Photogrammetry and Remote Sensing, vol 7 (January 2023)  

Public [article]  inISPRS Open Journal of Photogrammetry and Remote Sensing > vol 7 (January 2023) . - n° 100028 Titre : Estimation of lidar-based gridded DEM uncertainty with varying terrain roughness and point density Type de document : Article/Communication Auteurs : Luyen K. Bui, Auteur ; Craig L. Glennie, Auteur Année de publication : 2023 Article en page(s) : n° 100028 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] Alaska (Etats-Unis) [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] Hawaii (Etats-Unis) [Termes IGN] incertitude des données [Termes IGN] interpolation [Termes IGN] modèle numérique de surface [Termes IGN] semis de points [Termes IGN] Triangulated Irregular Network Résumé : (auteur) Light detection and ranging (lidar) scanning systems can be used to provide a point cloud with high quality and point density. Gridded digital elevation models (DEMs) interpolated from laser scanning point clouds are widely used due to their convenience, however, DEM uncertainty is rarely provided. This paper proposes an end-to-end workflow to quantify the uncertainty (i.e., standard deviation) of a gridded lidar-derived DEM. A benefit of the proposed approach is that it does not require independent validation data measured by alternative means. The input point cloud requires per point uncertainty which is derived from lidar system observational uncertainty. The propagated uncertainty caused by interpolation is then derived by the general law of propagation of variances (GLOPOV) with simultaneous consideration of both horizontal and vertical point cloud uncertainties. Finally, the interpolated uncertainty is then scaled by point density and a measure of terrain roughness to arrive at the final gridded DEM uncertainty. The proposed approach is tested with two lidar datasets measured in Waikoloa, Hawaii, and Sitka, Alaska. Triangulated irregular network (TIN) interpolation is chosen as the representative gridding approach. The results indicate estimated terrain roughness/point density scale factors ranging between 1 (in flat areas) and 7.6 (in high roughness areas), with a mean value of 2.3 for the Waikoloa dataset and between 1 and 9.2 with a mean value of 1.2 for the Sitka dataset. As a result, the final gridded DEM uncertainties are estimated between 0.059 m and 0.677 m with a mean value of 0.164 m for the Waikoloa dataset and between 0.059 m and 1.723 m with a mean value of 0.097 m for the Sitka dataset. Numéro de notice : A2023-120 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.ophoto.2022.100028 Date de publication en ligne : 17/12/2023 En ligne : https://doi.org/10.1016/j.ophoto.2022.100028 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102494 [article]

Explanation for the seam line discontinuity in terrestrial laser scanner point clouds / Derek D. Lichti in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 154 (August 2019) . - pp 59 - 69 Titre : Explanation for the seam line discontinuity in terrestrial laser scanner point clouds Type de document : Article/Communication Auteurs : Derek D. Lichti, Auteur ; Craig L. Glennie, Auteur ; Kaleel Al-Durgham, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 59 - 69 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] angle de visée [Termes IGN] discontinuité [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] semis de points [Termes IGN] télémétrie laser terrestre Résumé : (Auteur) The so-called seam line discontinuity is a phenomenon that can be observed in point clouds captured with some panoramic terrestrial laser scanners. It is an angular discontinuity that is most apparent where the lower limit of the instrument’s angular field-of-view intersects the ground. It appears as step discontinuities at the start (0° horizontal direction) and end (180°) of scanning. To the authors’ best knowledge, its cause and its impact, if any, on point cloud accuracy have not yet been reported. This paper presents the results of a rigorous investigation into several hypothesized causes of this phenomenon: differences between the lower and upper elevation angle scanning limits; the presence of a vertical circle index error; and changes in levelling during scanning. New models for the angular observations have been developed and simulations were performed to independently study the impact of each hypothesized cause and to guide the analyses of real datasets. In order to scrutinize each of the hypothesized causes, experiments were conducted with seven real datasets captured with six different instruments: one hybrid-architecture scanner and five panoramic scanners, one of which was also operated as a hybrid instrument. This study concludes that the difference between the elevation angle scanning limits is the source of the seam line discontinuity phenomenon. Accuracy assessment experiments over real data captured in an indoor test facility demonstrate that the seam line discontinuity has no metric impact on the point clouds. Numéro de notice : A2019-264 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.05.012 Date de publication en ligne : 06/06/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.05.012 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93078 [article]

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Fusion of LiDAR orthowaveforms and hyperspectral imagery for shallow river bathymetry and turbidity estimation / Zhigang Pan in IEEE Transactions on geoscience and remote sensing, vol 54 n° 7 (July 2016)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 54 n° 7 (July 2016) . - pp 4165 - 4177 Titre : Fusion of LiDAR orthowaveforms and hyperspectral imagery for shallow river bathymetry and turbidity estimation Type de document : Article/Communication Auteurs : Zhigang Pan, Auteur ; Craig L. Glennie, Auteur ; Juan Carlos Fernandez-Diaz, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 4165 - 4177 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] bathymétrie [Termes IGN] données lidar [Termes IGN] fusion d'images [Termes IGN] image hyperspectrale [Termes IGN] profondeur Résumé : (Auteur) We propose an approach to voxelize bathymetric full-waveform LiDAR (Light Detection and Ranging) to generate orthowaveforms and use them to estimate shallow water bathymetry and turbidity with a nonparametric support vector regression (SVR) method. Two distinct shallow rivers were investigated ranging from clear to turbid water; hyperspectral imagery and traditional full-waveform LiDAR processing were also investigated as a baseline for comparison with the proposed orthowaveform strategy. The orthowaveform showed significant correlation to water depth in both scenarios and outperformed hyperspectral imagery for water depth estimation in more turbid water. The orthowaveforms showed similar performance to full-waveform LiDAR point observations for bathymetry estimation in clear water and outperformed the bathymetry performance of full-waveform processing in turbid water. The orthowaveforms also showed similar performance to hyperspectral imagery for predicting water turbidity in turbid water, with a root mean square error (RMSE) of 1.32 NTU. The fusion of both hyperspectral imagery and orthowaveforms was also investigated and gave superior performance to using either data set alone. The fused data set was able to estimate depth in clear and turbid water with an RMSE of 10 and 21 cm, respectively, and turbidity with an RMSE of 1.16 NTU. Numéro de notice : A2016-880 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2538089 En ligne : https://doi.org/10.1109/TGRS.2016.2538089 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83043 [article]

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]

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Multi-feature based boresight self-calibration of a terrestrial mobile mapping system / Ting On Chan in ISPRS Journal of photogrammetry and remote sensing, vol 82 (August 2013)  

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