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Termes IGN > 1-Candidats > semis de points
semis de points
Commentaire :
- Ensemble de points répartis de façon régulière ou quelconque sur une zone géographique donnée. (Glossaire de cartographie / CFC) Ces points peuvent être issus d'images ou de données lidar ...
Synonyme(s)nuage de pointsVoir aussi |
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Algebraic method to speed up robust algorithms: example of laser-scanned point clouds / B. Palancz in Survey review, vol 49 n° 357 (December 2017)
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[article]
Titre : Algebraic method to speed up robust algorithms: example of laser-scanned point clouds Type de document : Article/Communication Auteurs : B. Palancz, Auteur ; Joseph L. Awange, Auteur ; T. Lovas, Auteur ; R. Lewis, Auteur ; B. Molnar, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 408 - 418 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] bases de Gröbner
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] méthode du maximum de vraisemblance (estimation)
[Termes IGN] Ransac (algorithme)
[Termes IGN] reconstruction d'objet
[Termes IGN] semis de points
[Termes IGN] valeur aberranteRésumé : (auteur) Surface reconstruction from point clouds generated by laser scanning technology has become a fundamental task in many fields of geosciences, such as robotics, computer vision, digital photogrammetry, computational geometry, digital building modelling, forest planning and operational activities. Point clouds produced by laser scanning, however, are limited due to the occurrence of occlusions, multiple reflectance and noise, and off-surface points (outliers), thus necessitating the need for robust fitting techniques. In this contribution, a fast, non-iterative and data invariant algebraic algorithm with constant O(1) complexity that fits planes to point clouds in the total least squares sense using Gaussian-type error distribution is proposed. The maximum likelihood estimator method is used, resulting in a multivariate polynomial system that is solved in an algebraic way. It is shown that for plane fitting when datasets are affected heavily by outliers, the proposed algebraic method can be embedded into the framework of robust methods like the Danish or the RANdom SAmple Consensus methods and computed in parallel to provide rigorous algebraic fitting with significantly reduced running times. Compared to the embedded traditional singular value decomposition and principal component analysis approaches, the performance of the proposed algebraic algorithm demonstrated its efficiency on both synthetic data and real laser-scanned measurements. The evaluation of a symbolic algebraic formula is practically independent of the values of its coefficients; however, the computation of the coefficients depends on the complexity of the data. Since the main advantage of the symbolic solution is its non-requirement of numerical iteration, the data complexity will have weak influence on the speed-up. The novelty of the proposed method is the use of algebraic technique in a robust plane fitting algorithm that could be applied to remote sensing data analysis/delineation/classification. In general, the method could be applied to most plane fitting problems in the geoscience field. Numéro de notice : A2017-755 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/00396265.2016.1183939 En ligne : https://doi.org/10.1080/00396265.2016.1183939 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89109
in Survey review > vol 49 n° 357 (December 2017) . - pp 408 - 418[article]Area-based estimation of growing stock volume in Scots pine stands using ALS and airborne image-based point clouds / Paweł Hawryło in Forestry, an international journal of forest research, vol 90 n° 5 (December 2017)
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Titre : Area-based estimation of growing stock volume in Scots pine stands using ALS and airborne image-based point clouds Type de document : Article/Communication Auteurs : Paweł Hawryło, Auteur ; Piotr Tompalski, Auteur ; Piotr Wezyk, Auteur Année de publication : 2017 Article en page(s) : pp 686 - 696 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse comparative
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image aérienne
[Termes IGN] image infrarouge couleur
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] Pinus sylvestris
[Termes IGN] régression linéaire
[Termes IGN] régression multiple
[Termes IGN] semis de points
[Termes IGN] volume en bois
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) Recent research has shown that image-derived point clouds (IPCs) are a highly competitive alternative to airborne laser scanning (ALS) data in the context of selected forest inventory activities. However, there is still a need for investigating different kinds of aerial images used for point cloud generation. This study compares the effectiveness of IPCs derived from true colour (RGB) and colour infrared (CIR) aerial images with ALS data for growing stock volume estimation of single canopy layer Scots pine stands. A multiple linear regression method was used to create predictive models. All models predicted growing stock volume with low root mean square errors – ALS: 15.2%, IPC-CIR: 17.0% and IPC-RGB: 17.5%. The following variables for each data type were found to be the most robust: ALS – mean height of points, percentage of all returns above mean height of points, interquartile range of point heights; IPC-CIR – mean height of points, percentage of all returns above mode height of points, canopy relief ratio; IPC-RGB – mean height of points and canopy relief ratio. Our results show that for single canopy layer Scots pine dominated stands it is possible to predict growing stock volume using IPCs with a comparable accuracy as using ALS data. The comparable performance of IPC-RGB and IPC-CIR based models suggests that a mixed usage of RGB and CIR data in retrospective studies could be possible. Numéro de notice : A2017-904 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1093/forestry/cpx026 En ligne : https://doi.org/10.1093/forestry/cpx026 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93205
in Forestry, an international journal of forest research > vol 90 n° 5 (December 2017) . - pp 686 - 696[article]Digital aerial photogrammetry can efficiently support large-area forest inventories in Norway / Lars Johannes in Forestry, an international journal of forest research, vol 90 n° 5 (December 2017)
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Titre : Digital aerial photogrammetry can efficiently support large-area forest inventories in Norway Type de document : Article/Communication Auteurs : Lars Johannes, Auteur ; Johannes Breidenbach, Auteur ; Svein Solberg, Auteur ; Erik Naesset, Auteur ; Rasmus Astrup, Auteur Année de publication : 2017 Article en page(s) : pp 710 - 718 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] biomasse forestière
[Termes IGN] hauteur des arbres
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] Norvège
[Termes IGN] photogrammétrie aérienne
[Termes IGN] semis de points
[Termes IGN] surface terrière
[Termes IGN] volume en boisRésumé : (Auteur) The use of digital aerial photogrammetry (DAP) for forest inventory purposes has been widely studied and can produce comparable accuracy compared with airborne laser scanning (ALS) in small, homogeneous areas. However, the accuracy of DAP for large scale applications with heterogeneous terrain and forest vegetation has not yet been reported. In this study we examined the accuracy of timber volume, biomass and basal area prediction models based on DAP and national forest inventory (NFI) data on a large area in central Norway. Two separate point clouds were derived from aerial image acquisitions of 2010 and 2013. Vegetation heights were extracted by subtracting terrain elevation derived from ALS. A large number of NFI sample plots (483) measured between 2010 and 2014 were used as reference data to fit linear models for timber volume, biomass and basal area with height metrics derived from the DAP data as explanatory variables. Variables describing the heterogeneous environmental and image acquisition conditions were calculated and their influence on the model accuracy was tested. The results showed that forest parameter prediction using DAP works well when applied to a large area. The model fits of the timber volume, biomass and basal area models were good with R2 of 0.80, 0.81, 0.81 and RMSEs of 41.43 m3 ha−1 (55% of the mean observed value), 32.49 t ha−1 (47%), 5.19 m2 ha−1 (41%), respectively. Only a small proportion of the variation could be attributed to the heterogeneous conditions. The inclusion of the relative sun inclination led to an improvement of the model RMSEs by 2% of the mean observed values. The relatively low cost and stability across large areas make DAP an attractive source of auxiliary information for large scale forest inventories. Numéro de notice : A2017-905 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1093/forestry/cpx027 En ligne : https://doi.org/10.1093/forestry/cpx027 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93207
in Forestry, an international journal of forest research > vol 90 n° 5 (December 2017) . - pp 710 - 718[article]Modélisation d'un oppidum sous couvert végétal dense, en Eure-et-Loir, par un LiDAR aéroporté par drone / Isabelle Heitz in XYZ, n° 153 (décembre 2017 - février 2018)
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[article]
Titre : Modélisation d'un oppidum sous couvert végétal dense, en Eure-et-Loir, par un LiDAR aéroporté par drone Type de document : Article/Communication Auteurs : Isabelle Heitz, Auteur ; Dominique Jagu, Auteur Année de publication : 2017 Article en page(s) : pp 45 - 50 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] drone
[Termes IGN] Eure-et-Loir (28)
[Termes IGN] modèle numérique de terrain
[Termes IGN] modélisation 3D
[Termes IGN] oppidum
[Termes IGN] semis de points
[Termes IGN] site archéologique
[Termes IGN] télémétrie laser aéroportéRésumé : (Auteur) L'archéologie fait appel depuis longtemps aux disciplines géophysiques au sol, aux photos aériennes prises depuis un avion ou d'un ULM. Des observations aériennes permettent aussi bien un repérage des vestiges non visibles du sol, qu'une localisation de sondages de reconnaissance ou de fouilles, au plus juste sur un site repéré. Dans certains cas, les observations aériennes sont un moyen non destructif d'étudier un site dans son ensemble, que l'on n'a pas l'intention de fouiller, en tout cas dans un premier temps. C'est bien cette raison qui a amené le CAEL (Comité Archéologique d'Eure-et-Loir) à demander à la société AIRD'ECO-drone de prospecter le site dit "du Camp de César", sur la commune de Changé - Saint-Piat (28), à 2 km au sud de Maintenon. Numéro de notice : A2017-796 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89106
in XYZ > n° 153 (décembre 2017 - février 2018) . - pp 45 - 50[article]Réservation
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Modélisation d'un oppidum ... - pdf éditeurURLPairwise registration of TLS point clouds using covariance descriptors and a non-cooperative game / Dawei Zai in ISPRS Journal of photogrammetry and remote sensing, vol 134 (December 2017)
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Titre : Pairwise registration of TLS point clouds using covariance descriptors and a non-cooperative game Type de document : Article/Communication Auteurs : Dawei Zai, Auteur ; Jonathan Li, Auteur ; Yulan Guo, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 15 - 29 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] enregistrement de données
[Termes IGN] matrice de covariance
[Termes IGN] semis de points
[Termes IGN] télémétrie laser terrestre
[Termes IGN] théorie des jeuxRésumé : (Auteur) It is challenging to automatically register TLS point clouds with noise, outliers and varying overlap. In this paper, we propose a new method for pairwise registration of TLS point clouds. We first generate covariance matrix descriptors with an adaptive neighborhood size from point clouds to find candidate correspondences, we then construct a non-cooperative game to isolate mutual compatible correspondences, which are considered as true positives. The method was tested on three models acquired by two different TLS systems. Experimental results demonstrate that our proposed adaptive covariance (ACOV) descriptor is invariant to rigid transformation and robust to noise and varying resolutions. The average registration errors achieved on three models are 0.46 cm, 0.32 cm and 1.73 cm, respectively. The computational times cost on these models are about 288 s, 184 s and 903 s, respectively. Besides, our registration framework using ACOV descriptors and a game theoretic method is superior to the state-of-the-art methods in terms of both registration error and computational time. The experiment on a large outdoor scene further demonstrates the feasibility and effectiveness of our proposed pairwise registration framework. Numéro de notice : A2017-729 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.10.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.10.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88426
in ISPRS Journal of photogrammetry and remote sensing > vol 134 (December 2017) . - pp 15 - 29[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2017121 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017122 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt 081-2017123 DEP-EXM Revue Saint-Mandé Dépôt en unité Exclu du prêt SNCF Réseau : de l'acquisition 3D à la diffusion de la donnée / Mathieu Regul in XYZ, n° 153 (décembre 2017 - février 2018)
PermalinkStand-level wind damage can be assessed using diachronic photogrammetric canopy height models / Jean-Pierre Renaud in Annals of Forest Science, vol 74 n° 4 (December 2017)
PermalinkBayesian graph-cut optimization for wall surfaces reconstruction in indoor environments / Georgios-Tsampikos Michailidis in The Visual Computer, vol 33 n° 10 (October 2017)
PermalinkA structured regularization framework for spatially smoothing semantic labelings of 3D point clouds / Loïc Landrieu in ISPRS Journal of photogrammetry and remote sensing, vol 132 (October 2017)
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PermalinkOccupancy modelling for moving object detection from Lidar point clouds: A comparative study / Wen Xiao in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol IV-2/W4 (September 2017)
PermalinkFacet segmentation-based line segment extraction for large-scale point clouds / Yangbin Lin in IEEE Transactions on geoscience and remote sensing, vol 55 n° 9 (September 2017)
PermalinkPoint cloud refinement with self-calibration of a mobile multibeam lidar sensor / Houssem Nouira in Photogrammetric record, vol 32 n° 159 (September 2017)
PermalinkPrecision estimation of the angular resolution of terrestrial laser scanners / Xijiang Chen in Photogrammetric record, vol 32 n° 159 (September 2017)
PermalinkUrban building reconstruction from raw LiDAR point data / Cheng Yi in Computer-Aided Design, vol 9x (2017)
Permalink3D local feature BKD to extract road information from mobile laser scanning point clouds / Yang Bisheng in ISPRS Journal of photogrammetry and remote sensing, vol 130 (August 2017)
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