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A new method of equiangular sectorial voxelization of single-scan terrestrial laser scanning data and its applications in forest defoliation estimation / Langning Huo in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 151 (May 2019) . - pp 302 - 312 Titre : A new method of equiangular sectorial voxelization of single-scan terrestrial laser scanning data and its applications in forest defoliation estimation Type de document : Article/Communication Auteurs : Langning Huo, Auteur ; Xiaoli Zhang, Auteur Année de publication : 2019 Article en page(s) : pp 302 - 312 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] canopée [Termes descripteurs IGN] défoliation [Termes descripteurs IGN] densité des points [Termes descripteurs IGN] régression linéaire [Termes descripteurs IGN] télémétrie laser terrestre [Termes descripteurs IGN] voxel Résumé : (Auteur) Voxelization is an efficient and frequently used data process that is applied to terrestrial laser scanning (TLS) data to facilitate data management and reduce storage size. In this study, an innovative method of equiangular sectorial voxelization is presented based on the distinctive point distribution characteristic of single-scan TLS. It has the function of containing the same number of laser beams going through each voxel, which results in metrics that can be applied to delineate forest conditions. To verify the effectiveness of the new voxelization method and to illustrate its application, 48 plots and 1098 individual trees with different degrees of defoliation were scanned using single-scan TLS. Their defoliation could be linearly regressed by using only point density metrics derived from this new shape of voxels. A 0.89 R2 value and a 12 RMSE (% of defoliation) were obtained for individual-tree-scale estimation, and a 0.83 R2 value and a 12 RMSE (% of defoliation) were obtained for plot-scale estimation. We conclude that the new voxelization method was effective, and the point density that was thus calculated was an efficient feature that revealed forest attributes. Numéro de notice : A2019-212 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.03.018 date de publication en ligne : 30/03/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.03.018 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92678 [article]

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Pairwise coarse registration of point clouds in urban scenes using voxel-based 4-planes congruent sets / Yusheng Xu in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 151 (May 2019) . - pp 106 - 123 Titre : Pairwise coarse registration of point clouds in urban scenes using voxel-based 4-planes congruent sets Type de document : Article/Communication Auteurs : Yusheng Xu, Auteur ; Richard Boerner, Auteur ; Wei Yao, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 106 - 123 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] appariement d'images [Termes descripteurs IGN] congruence [Termes descripteurs IGN] données 4D [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données spatiotemporelles [Termes descripteurs IGN] modèle stéréoscopique [Termes descripteurs IGN] octree [Termes descripteurs IGN] Ransac (algorithme) [Termes descripteurs IGN] scène urbaine [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] surface plane [Termes descripteurs IGN] voxel Résumé : (Auteur) To ensure complete coverage when measuring a large-scale urban area, pairwise registration between point clouds acquired via terrestrial laser scanning or stereo image matching is usually necessary when there is insufficient georeferencing information from additional GNSS and INS sensors. In this paper, we propose a semi-automatic and target-less method for coarse registration of point clouds using geometric constraints of voxel-based 4-plane congruent sets (V4PCS). The planar patches are firstly extracted from voxelized point clouds. Then, the transformation invariant, 4-plane congruent sets are constructed from extracted planar surfaces in each point cloud. Initial transformation parameters between point clouds are estimated via corresponding congruent sets having the highest registration scores in the RANSAC process. Finally, a closed-form solution is performed to achieve optimized transformation parameters by finding all corresponding planar patches using the initial transformation parameters. Experimental results reveal that our proposed method can be effective for registering point clouds acquired from various scenes. A success rate of better than 80% was achieved, with average rotation errors of about 0.5 degrees and average translation errors less than approximately 0.6 m. In addition, our proposed method is more efficient than other baseline methods when using the same hardware and software configuration conditions. Numéro de notice : A2019-207 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.02.015 date de publication en ligne : 18/03/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.02.015 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92673 [article]

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Conditional random field and deep feature learning for hyperspectral image classification / Fahim Irfan Alam in IEEE Transactions on geoscience and remote sensing, vol 57 n° 3 (March 2019)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 57 n° 3 (March 2019) . - pp 1612 - 1628 Titre : Conditional random field and deep feature learning for hyperspectral image classification Type de document : Article/Communication Auteurs : Fahim Irfan Alam, Auteur ; Jun Zhou, Auteur ; Alan Wee-Chung Liew, Auteur ; Xiuping Jia, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 1612 - 1628 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] analyse multibande [Termes descripteurs IGN] champ aléatoire conditionnel [Termes descripteurs IGN] classification par réseau neuronal convolutif [Termes descripteurs IGN] déconvolution [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] voxel Résumé : (Auteur) Image classification is considered to be one of the critical tasks in hyperspectral remote sensing image processing. Recently, a convolutional neural network (CNN) has established itself as a powerful model in classification by demonstrating excellent performances. The use of a graphical model such as a conditional random field (CRF) contributes further in capturing contextual information and thus improving the classification performance. In this paper, we propose a method to classify hyperspectral images by considering both spectral and spatial information via a combined framework consisting of CNN and CRF. We use multiple spectral band groups to learn deep features using CNN, and then formulate deep CRF with CNN-based unary and pairwise potential functions to effectively extract the semantic correlations between patches consisting of 3-D data cubes. Furthermore, we introduce a deep deconvolution network that improves the final classification performance. We also introduced a new data set and experimented our proposed method on it along with several widely adopted benchmark data sets to evaluate the effectiveness of our method. By comparing our results with those from several state-of-the-art models, we show the promising potential of our method. Numéro de notice : A2019-131 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2867679 date de publication en ligne : 20/09/2018 En ligne : https://doi.org/10.1109/TGRS.2018.2867679 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92461 [article]

A time‐geographic approach to quantifying wildlife–road interactions / Rebecca W. Loraamm in Transactions in GIS, vol 23 n° 1 (February 2019)  

Public [article]  inTransactions in GIS > vol 23 n° 1 (February 2019) . - pp 70 - 86 Titre : A time‐geographic approach to quantifying wildlife–road interactions Type de document : Article/Communication Auteurs : Rebecca W. Loraamm, Auteur ; Joni A. Downs, Auteur ; David Lamb, Auteur Année de publication : 2019 Article en page(s) : pp 70 - 86 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] analyse spatio-temporelle [Termes descripteurs IGN] comportement [Termes descripteurs IGN] données GPS [Termes descripteurs IGN] échantillonnage de données [Termes descripteurs IGN] faune locale [Termes descripteurs IGN] gestion de la vie sauvage [Termes descripteurs IGN] interaction spatiale [Termes descripteurs IGN] migration animale [Termes descripteurs IGN] Mustelidae [Termes descripteurs IGN] prisme spatio-temporel [Termes descripteurs IGN] route [Termes descripteurs IGN] Time-geography [Termes descripteurs IGN] voxel Résumé : (auteur) Recent advances in time geography offer new perspectives for studying animal movements and interactions in an environmental context. In particular, the ability to estimate an animal's spatial location probabilistically at temporal sampling intervals between known fix locations allows researchers to quantify how individuals interact with one another and their environment on finer temporal and spatial scales than previously explored. This article extends methods from time geography, specifically probabilistic space–time prisms, to quantify and summarize animal–road interactions toward understanding related diurnal movement behaviors, including road avoidance. The approach is demonstrated using tracking data for fishers (Martes pennanti) in New York State, where the total probability of interaction with roadways is calculated for individuals over the duration tracked. Additionally, a summarization method visualizing daily interaction probabilities at 60 s intervals is developed to assist in the examination of temporal patterns associated with fishers’ movement behavior with respect to roadways. The results identify spatial and temporal patterns of fisher–roadway interaction by time of day. Overall, the methodologies discussed offer an intuitive means to assess moving object location probabilities in the context of environmental factors. Implications for movement ecology and related conservation planning efforts are also discussed. Numéro de notice : A2019-090 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12497 date de publication en ligne : 17/12/2018 En ligne : https://doi.org/10.1111/tgis.12497 Format de la ressource électronique : url Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92237 [article]

Analyzing the role of pulse density and voxelization parameters on full-waveform LiDAR-derived metrics / Pablo Crespo-Peremarch in ISPRS Journal of photogrammetry and remote sensing, vol 146 (December 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 146 (December 2018) . - pp 453 - 464 Titre : Analyzing the role of pulse density and voxelization parameters on full-waveform LiDAR-derived metrics Type de document : Article/Communication Auteurs : Pablo Crespo-Peremarch, Auteur ; Luis Ángel Ruiz, Auteur ; Angel Balaguer-Beser, Auteur ; Javier Estornell, Auteur Année de publication : 2018 Article en page(s) : pp 453 - 464 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] Abies grandis [Termes descripteurs IGN] Acer macrophyllum [Termes descripteurs IGN] amplitude [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] étalonnage en vol [Termes descripteurs IGN] filtrage du bruit [Termes descripteurs IGN] forme d'onde pleine [Termes descripteurs IGN] impulsion laser [Termes descripteurs IGN] lidar à retour d'onde complète [Termes descripteurs IGN] Oregon (Etats-Unis) [Termes descripteurs IGN] prétraitement du signal [Termes descripteurs IGN] pseudotsuga menziesii [Termes descripteurs IGN] Thuja plicata [Termes descripteurs IGN] tsuga heterophylla [Termes descripteurs IGN] voxel Résumé : (auteur) LiDAR full-waveform (LFW) pulse density is not homogeneous along study areas due to overlap between contiguous flight stripes and, to a lesser extent, variations in height, velocity and altitude of the platform. As a result, LFW-derived metrics extracted at the same spot but at different pulse densities differ, which is called “side-lap effect”. Moreover, this effect is reflected in forest stand estimates, since they are predicted from LFW-derived metrics. This study was undertaken to analyze LFW-derived metric variations according to pulse density, voxel size and value assignation method in order to reduce the side-lap effect. Thirty LiDAR samples with a minimum density of 16 pulses.m−2 were selected from the testing area and randomly reduced to 2 pulses.m−2 with an interval of 1 pulse.m−2, then metrics were extracted and compared for each sample and pulse density at different voxel sizes and assignation values. Results show that LFW-derived metric variations as a function of pulse density follow a negative exponential model similar to the exponential semivariogram curve, increasing sharply until they reach a certain pulse density, where they become stable. This value represents the minimum pulse density (MPD) in the study area to optimally minimize the side-lap effect. This effect can also be reduced with pulse densities lower than the MPD modifying LFW parameters (i.e. voxel size and assignation value). Results show that LFW-derived metrics are not equally influenced by pulse density, such as number of peaks (NP) and ROUGHness of the outermost canopy (ROUGH) that may be discarded for further analyses at large voxel sizes, given that they are highly influenced by pulse density. In addition, side-lap effect can be reduced by either increasing pulse density or voxel size, or modifying the assignation value. In practice, this leads to a proper estimate of forest stand variables using LFW data. Numéro de notice : A2018-543 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.10.012 date de publication en ligne : 05/11/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.10.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91569 [article]

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A greyscale voxel model for airborne lidar data applied to building detection / Liying Wang in Photogrammetric record, vol 33 n° 164 (December 2018)  

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Analyzing the vertical distribution of crown material in mixed stand composed of two temperate tree species / Olivier Martin-Ducup in Forests, vol 9 n° 11 (November 2018)  

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SDF-2-SDF registration for real-time 3D reconstruction from RGB-D data / Miroslava Slavcheva in International journal of computer vision, vol 126 n° 6 (June 2018)  

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A voxel- and graph-based strategy for segmenting man-made infrastructures using perceptual grouping laws: comparison and evaluation / Yusheng Xu in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 6 (juin 2018)  

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3D visibility analysis indicating quantitative and qualitative aspects of the visible space / D. Golub in Survey review, vol 50 n° 359 (March 2018)  

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Smart fusion of terrestrial and UAV data / Michaël Gaudin (2018) 

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Tubelets : Unsupervised action proposals from spatiotemporal super-voxels / Mihir Jain in International journal of computer vision, vol 124 n° 3 (15 September 2017)  

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A TV prior for high-quality scalable multi-view stereo reconstruction / Andreas Kuhn in International journal of computer vision, vol 124 n° 1 (August 2017)  

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Robust point cloud classification based on multi-level semantic relationships for urban scenes / Qing Zhu in ISPRS Journal of photogrammetry and remote sensing, vol 129 (July 2017)  

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Ionospheric tomography based on GNSS observations of the CMONOC: performance in the topside ionosphere / Zhe Yang in GPS solutions, vol 21 n° 2 (April 2017)  

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