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A historical timber frame model for diagnosis and documentation before building restoration / Mathieu Koehl in International journal of 3-D information modeling, vol 4 n° 4 (October - December 2015)
[article]
Titre : A historical timber frame model for diagnosis and documentation before building restoration Type de document : Article/Communication Auteurs : Mathieu Koehl, Auteur ; Anthony Viale, Auteur ; Sophie Reeb, Auteur Année de publication : 2015 Article en page(s) : pp 34 - 63 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] Bas-Rhin (67)
[Termes IGN] bien immobilier
[Termes IGN] diagnostic
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image terrestre
[Termes IGN] levé topographique
[Termes IGN] maquette numérique
[Termes IGN] patrimoine archéologique
[Termes IGN] restauration de bâtiment
[Termes IGN] seizième siècle
[Termes IGN] SIG 3D
[Termes IGN] système d'information géographique
[Termes IGN] système d'information historiqueRésumé : (Auteur) The aim of the project that is described in this paper was to define a four-level timber frame survey mode of a historical building: the so-called “Andlau's Seigniory”, Alsace, France. This historical building was built in the late XVIth century and was in a stage of renovation in order to become a heritage interpretation centre. The used measurement methods combine Total Station measurements, Photogrammetry and 3D Terrestrial Laser scanner. Different modelling workflows were tested and compared according to the data acquisition method, but also according to the characteristics of the reconstructed model in terms of accuracy and level of detail. 3D geometric modelling of the entire structure was performed including modelling the degree of detail adapted to the needs. The described 3D timber framework exists now in different versions, from a theoretical and geometrical one up to a very detailed one, in which measurements and evaluation of deformation by time are potentially allowed. The virtually generated models involving archaeologists, architects, historians and specialists in historical crafts, are intended to be used during the four stages of the project: (i) knowledge of the current state of needs for diagnosis and understanding of former construction techniques; (ii) preparation and evaluation of restoration steps; (iii) knowledge and documentation concerning the archaeological object; (iv) transmission and dissemination of knowledge through the implementation of museum animations. Among the generated models one can also find a documentation of the site in the form of virtual tours created from panoramic photographs before and during the restoration works. Finally, the timber framework model was structured and integrated into a 3D GIS, where the association of descriptive and complementary digital documents was possible. Both offer tools leading to the diagnosis, the understanding of the structure, knowledge dissemination, documentation and the creation of educational activities. The integration of these measurements in a historical information system will lead to the creation of an interactive model and the creation of a digital visual display unit for consultation. It will be offered to any public to understand interactively the art of constructing a Renaissance structure, with detailed photos, descriptive texts and graphics. The 3D digital model of the framework will be used directly in the interpretation path, within the space dedicated to “Seigniory” of Andlau. An interactive touch-screen will be installed. It will incorporate several levels of playgrounds (playful, evocative and teaching). In a virtual way, it will deal with the different stages of building a wooden framework and clarify the art of construction. Numéro de notice : A2016-430 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.4018/ij3dim.2015100103 En ligne : http://doi.org/10.4018/ij3dim.2015100103 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81324
in International journal of 3-D information modeling > vol 4 n° 4 (October - December 2015) . - pp 34 - 63[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 138-2015041 RAB Revue Centre de documentation En réserve L003 Disponible Lidar Scanning by Helicopter in the USA / Jeff Fagerman in GIM international, vol 29 n° 10 (October 2015)
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Titre : Lidar Scanning by Helicopter in the USA Type de document : Article/Communication Auteurs : Jeff Fagerman, Auteur ; Wolfgang Juchmann, Auteur Année de publication : 2015 Article en page(s) : pp 23 - 25 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] acquisition de données
[Termes IGN] données lidar
[Termes IGN] drone
[Termes IGN] modélisation 3DRésumé : (auteur) In recent years, use of unmanned aerial systems (UASs) has soared as a means for capturing geodata by images and Lidar. However, this does not mean that proven platforms, such as helicopters, have become obsotete. For various applications, Lidar scanning from manned choppers is versatile, quick, cost-effective and free of legal encumbrances. The authors elaborate on its effectiveness for 3D modelling of levees, riparian boundaries and railways. Numéro de notice : A2015-662 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78270
in GIM international > vol 29 n° 10 (October 2015) . - pp 23 - 25[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 061-2015101 RAB Revue Centre de documentation En réserve L003 Disponible Linear models for airborne-laser-scanning-based operational forest inventory with small field sample size and highly correlated LiDAR data / Virpi Junttila in IEEE Transactions on geoscience and remote sensing, vol 53 n° 10 (October 2015)
[article]
Titre : Linear models for airborne-laser-scanning-based operational forest inventory with small field sample size and highly correlated LiDAR data Type de document : Article/Communication Auteurs : Virpi Junttila, Auteur ; Tuomo Kauranne, Auteur ; Andrew O. Finley, Auteur ; John B. Bradford, Auteur Année de publication : 2015 Article en page(s) : pp 5600 - 5612 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] appariement d'images
[Termes IGN] décomposition d'image
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modèle linéaire
[Termes IGN] placette d'échantillonnage
[Termes IGN] précision des données
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) Modern operational forest inventory often uses remotely sensed data that cover the whole inventory area to produce spatially explicit estimates of forest properties through statistical models. The data obtained by airborne light detection and ranging (LiDAR) correlate well with many forest inventory variables, such as the tree height, the timber volume, and the biomass. To construct an accurate model over thousands of hectares, LiDAR data must be supplemented with several hundred field sample measurements of forest inventory variables. This can be costly and time consuming. Different LiDAR-data-based and spatial-data-based sampling designs can reduce the number of field sample plots needed. However, problems arising from the features of the LiDAR data, such as a large number of predictors compared with the sample size (overfitting) or a strong correlation among predictors (multicollinearity), may decrease the accuracy and precision of the estimates and predictions. To overcome these problems, a Bayesian linear model with the singular value decomposition of predictors, combined with regularization, is proposed. The model performance in predicting different forest inventory variables is verified in ten inventory areas from two continents, where the number of field sample plots is reduced using different sampling designs. The results show that, with an appropriate field plot selection strategy and the proposed linear model, the total relative error of the predicted forest inventory variables is only 5%-15% larger using 50 field sample plots than the error of a linear model estimated with several hundred field sample plots when we sum up the error due to both the model noise variance and the model's lack of fit. Numéro de notice : A2015-748 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2425916 Date de publication en ligne : 14/05/2015 En ligne : https://doi.org/10.1109/TGRS.2015.2425916 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78757
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 10 (October 2015) . - pp 5600 - 5612[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015101 SL Revue Centre de documentation Revues en salle Disponible A novel MKL model of integrating LiDAR data and MSI for urban area classification / Yanfeng Gu in IEEE Transactions on geoscience and remote sensing, vol 53 n° 10 (October 2015)
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Titre : A novel MKL model of integrating LiDAR data and MSI for urban area classification Type de document : Article/Communication Auteurs : Yanfeng Gu, Auteur ; Qingwang Wang, Auteur ; Xiuping Jia, Auteur ; Jón Alti, Auteur Année de publication : 2015 Article en page(s) : pp 5312 - 5326 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] apprentissage automatique
[Termes IGN] classificateur
[Termes IGN] classification à base de connaissances
[Termes IGN] classification automatique
[Termes IGN] données lidar
[Termes IGN] image multibande
[Termes IGN] image spectrale
[Termes IGN] milieu urbainRésumé : (Auteur) A novel multiple-kernel learning (MKL) model is proposed for urban classification to integrate heterogeneous features (HF-MKL) from two data sources, i.e., spectral images and LiDAR data. The features include spectral, spatial, and elevation attributes of urban objects from the two data sources. With these heterogeneous features (HFs), the new MKL model is designed to carry out feature fusion that is embedded in classification. First, Gaussian kernels with different bandwidths are used to measure the similarity of samples on each feature at different scales. Then, these multiscale kernels with different features are integrated using a linear combination. In the combination, the weights of the kernels with different features are determined by finding a projection based on the maximum variance. This way, the discriminative ability of the HFs is exploited at different scales and is also integrated to generate an optimal combined kernel. Finally, the optimization of the conventional support vector machine with this kernel is performed to construct a more effective classifier. Experiments are conducted on two real data sets, and the experimental results show that the HF-MKL model achieves the best performance in terms of classification accuracies in integrating the HFs for classification when compared with several state-of-the-art algorithms. Numéro de notice : A2015-752 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2421051 Date de publication en ligne : 07/05/2015 En ligne : https://doi.org/10.1109/TGRS.2015.2421051 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78742
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 10 (October 2015) . - pp 5312 - 5326[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015101 SL Revue Centre de documentation Revues en salle Disponible Tropical forest canopy cover estimation using satellite imagery and airborne lidar reference data / Lauri Korhonen in Silva fennica, vol 49 n° 5 ([01/10/2015])
[article]
Titre : Tropical forest canopy cover estimation using satellite imagery and airborne lidar reference data Type de document : Article/Communication Auteurs : Lauri Korhonen, Auteur ; Daniela Ali-Sisto, Auteur ; Timo Tokola, Auteur Année de publication : 2015 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] canopée
[Termes IGN] couvert forestier
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt tropicale
[Termes IGN] image ALOS-AVNIR2
[Termes IGN] image optique
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] Laos
[Termes IGN] placette d'échantillonnage
[Termes IGN] régression logistique
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) The fusion of optical satellite imagery, strips of lidar data and field plots is a promising approach for the inventory of tropical forests. Airborne lidars also enable an accurate direct estimation of the forest canopy cover (CC), and thus a sample of lidar strips can be used as reference data for creating CC maps which are based on satellite images. In this study, our objective was to validate CC maps obtained from an ALOS AVNIR-2 satellite image wall-to-wall, against a lidar-based CC map of a tropical forest area located in Laos. The reference CC values which were needed for model training were obtained from a sample of four lidar strips. Zero-and-one inflated beta regression (ZOINBR) models were applied to link the spectral vegetation indices derived from the ALOS image with the lidar-based CC estimates. In addition, we compared ZOINBR and logistic regression models in the forest area estimation by using >20% CC as a forest definition. Using a total of 409 217 30 × 30 m population units as validation, our model showed a strong correlation between lidar-based CC and spectral satellite features (root mean square error = 12.8%, R2 = 0.82). In the forest area estimation, a direct classification using logistic regression provided better accuracy than the estimation of CC values as an intermediate step (kappa = 0.61 vs. 0.53). It is important to obtain sufficient training data from both ends of the CC range. The forest area estimation should be done before the CC estimation, rather than vice versa. Numéro de notice : A2015-673 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.14214/sf.1405 En ligne : http://www.silvafennica.fi/article/1405 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78293
in Silva fennica > vol 49 n° 5 [01/10/2015][article]3D model construction in an urban environment from sparse LiDAR points and aerial photos : a statistical approach / Xuebin Wei in Geomatica, vol 69 n° 3 (september 2015)PermalinkAnalysis of different methods for 3D reconstruction of natural surfaces from parallel-axes UAV images / Annette Eltner in Photogrammetric record, vol 30 n° 151 (September - November 2015)PermalinkLe contrôle de la végétation dans les emprises ferroviaires : une approche multi-scalaire / Flavien Viguier in XYZ, n° 144 (septembre - novembre 2015)PermalinkEtude de l'homogénéité d'une surface non régulière / Claire Blondeau in XYZ, n° 144 (septembre - novembre 2015)PermalinkNumerical and experimental evaluation of terrestrial LiDAR for parameterizing centimeter-scale sea ice surface roughness / Jack C. Landy in IEEE Transactions on geoscience and remote sensing, vol 53 n° 9 (September 2015)PermalinkRegistration of aerial imagery and lidar data in desert areas using sand ridges / Na Li in Photogrammetric record, vol 30 n° 151 (September - November 2015)PermalinkStreet environment change detection from mobile laser scanning point clouds / Wen Xiao in ISPRS Journal of photogrammetry and remote sensing, vol 107 (September 2015)PermalinkPoint cloud server (PCS) : point clouds in-base management and processing / Rémi Cura in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 W5 (October 2015)PermalinkRoad orthophoto/DTM generation from mobile laser scanning / Bruno Vallet in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 W5 (October 2015)PermalinkAboveground-biomass estimation of a complex tropical forest in India using Lidar / Cédric Vega in Remote sensing, vol 7 n° 8 (August 2015)Permalink