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Mapping forest attributes using data from stereophotogrammetry of aerial images and field data from the national forest inventory / Jonas Bohlin in Silva fennica, vol 51 n° 2 (2017)
[article]
Titre : Mapping forest attributes using data from stereophotogrammetry of aerial images and field data from the national forest inventory Type de document : Article/Communication Auteurs : Jonas Bohlin, Auteur ; Inka Bohlin, Auteur ; Jonas Jonzén, Auteur ; Mats Nilsson, Auteur Année de publication : 2017 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Betula (genre)
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image aérienne
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] Picea abies
[Termes IGN] Pinus sylvestris
[Termes IGN] régression linéaire
[Termes IGN] semis de points
[Termes IGN] Suède
[Termes IGN] surface terrière
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Exploring the possibility to produce nation-wide forest attribute maps using stereophotogrammetry of aerial images, the national terrain model and data from the National Forest Inventory (NFI). The study areas are four image acquisition blocks in mid- and south Sweden. Regression models were developed and applied to 12.5 m × 12.5 m raster cells for each block and validation was done with an independent dataset of forest stands. Model performance was compared for eight different forest types separately and the accuracies between forest types clearly differs for both image- and LiDAR methods, but between methods the difference in accuracy is small at plot level. At stand level, the root mean square error in percent of the mean (RMSE%) were ranging: from 7.7% to 10.5% for mean height; from 12.0% to 17.8% for mean diameter; from 21.8% to 22.8% for stem volume; and from 17.7% to 21.1% for basal area. This study clearly shows that aerial images from the national image program together with field sample plots from the NFI can be used for large area forest attribute mapping. Numéro de notice : A2017-648 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.14214/sf.2021 En ligne : https://doi.org/10.14214/sf.2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=87007
in Silva fennica > vol 51 n° 2 (2017)[article]Semantic segmentation of forest stands of pure species combining airborne lidar data and very high resolution multispectral imagery / Clément Dechesne in ISPRS Journal of photogrammetry and remote sensing, vol 126 (April 2017)
[article]
Titre : Semantic segmentation of forest stands of pure species combining airborne lidar data and very high resolution multispectral imagery Type de document : Article/Communication Auteurs : Clément Dechesne , Auteur ; Clément Mallet , Auteur ; Arnaud Le Bris , Auteur ; Valérie Gouet-Brunet , Auteur Année de publication : 2017 Projets : HYEP / Weber, Christiane Article en page(s) : pp 129 – 145 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] classification automatique
[Termes IGN] classification dirigée
[Termes IGN] délimitation
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] espèce végétale
[Termes IGN] extraction d'arbres
[Termes IGN] fusion d'images
[Termes IGN] image aérienne
[Termes IGN] image multibande
[Termes IGN] peuplement forestier
[Termes IGN] segmentation sémantique
[Termes IGN] semis de pointsRésumé : (auteur) Forest stands are the basic units for forest inventory and mapping. Stands are defined as large forested areas (e.g., ⩾⩾2 ha) of homogeneous tree species composition and age. Their accurate delineation is usually performed by human operators through visual analysis of very high resolution (VHR) infra-red images. This task is tedious, highly time consuming, and should be automated for scalability and efficient updating purposes. In this paper, a method based on the fusion of airborne lidar data and VHR multispectral images is proposed for the automatic delineation of forest stands containing one dominant species (purity superior to 75%). This is the key preliminary task for forest land-cover database update. The multispectral images give information about the tree species whereas 3D lidar point clouds provide geometric information on the trees and allow their individual extraction. Multi-modal features are computed, both at pixel and object levels: the objects are individual trees extracted from lidar data. A supervised classification is then performed at the object level in order to coarsely discriminate the existing tree species in each area of interest. The classification results are further processed to obtain homogeneous areas with smooth borders by employing an energy minimum framework, where additional constraints are joined to form the energy function. The experimental results show that the proposed method provides very satisfactory results both in terms of stand labeling and delineation (overall accuracy ranges between 84% and 99%). Numéro de notice : A2017-116 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : FORET/IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.02.011 Date de publication en ligne : 27/02/2017 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2017.02.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84511
in ISPRS Journal of photogrammetry and remote sensing > vol 126 (April 2017) . - pp 129 – 145[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2017041 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017043 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2017042 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt Airborne Lidar/INS/GNSS : algorithm uses fuzzy controlled Scale Invariant Feature Transform (SIFT) / Haowei Xu in GPS world, vol 28 n° 3 (March 2017)
[article]
Titre : Airborne Lidar/INS/GNSS : algorithm uses fuzzy controlled Scale Invariant Feature Transform (SIFT) Type de document : Article/Communication Auteurs : Haowei Xu, Auteur ; Lian Baowang, Auteur ; Charles K. Toth, Auteur ; Dorota Brzezinska, Auteur Année de publication : 2017 Article en page(s) : pp 26 - 32 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] classification floue
[Termes IGN] couplage GNSS-INS
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] SIFT (algorithme)Résumé : (Auteur) Lidar with its superior performance can replace GNSS in the integration solution by providing fixes for the drifting inertial measurement unit (IMU). Tests show its potential for terrain-referenced navigation due to its high accuracy, resolution, update rate and anti-jamming abilities. A novel algorithm uses scanning lidar ranging data and a reference database to calculate the navigation solution of the platform and then further fuse with the inertial navigation system (INS) output data. Numéro de notice : A2017-290 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85325
in GPS world > vol 28 n° 3 (March 2017) . - pp 26 - 32[article]A classification-segmentation framework for the detection of individual trees in dense MMS point cloud data acquired in urban areas / Martin Weinmann in Remote sensing, vol 9 n° 3 (March 2017)
[article]
Titre : A classification-segmentation framework for the detection of individual trees in dense MMS point cloud data acquired in urban areas Type de document : Article/Communication Auteurs : Martin Weinmann, Auteur ; Michael Weinmann, Auteur ; Clément Mallet , Auteur ; Mathieu Brédif , Auteur Année de publication : 2017 Projets : IQmulus / Métral, Claudine Article en page(s) : pp 277 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] algorithme de décalage moyen
[Termes IGN] arbre (flore)
[Termes IGN] classification
[Termes IGN] Delft (Pays-Bas)
[Termes IGN] détection d'objet
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] segmentation
[Termes IGN] semis de points
[Termes IGN] voxel
[Termes IGN] zone urbaineRésumé : (auteur) In this paper, we present a novel framework for detecting individual trees in densely sampled 3D point cloud data acquired in urban areas. Given a 3D point cloud, the objective is to assign point-wise labels that are both class-aware and instance-aware, a task that is known as instance-level segmentation. To achieve this, our framework addresses two successive steps. The first step of our framework is given by the use of geometric features for a binary point-wise semantic classification with the objective of assigning semantic class labels to irregularly distributed 3D points, whereby the labels are defined as “tree points” and “other points”. The second step of our framework is given by a semantic segmentation with the objective of separating individual trees within the “tree points”. This is achieved by applying an efficient adaptation of the mean shift algorithm and a subsequent segment-based shape analysis relying on semantic rules to only retain plausible tree segments. We demonstrate the performance of our framework on a publicly available benchmark dataset, which has been acquired with a mobile mapping system in the city of Delft in the Netherlands. This dataset contains 10.13 M labeled 3D points among which 17.6 % are labeled as “tree points”. The derived results clearly reveal a semantic classification of high accuracy (up to 90.77 %) and an instance-level segmentation of high plausibility, while the simplicity, applicability and efficiency of the involved methods even allow applying the complete framework on a standard laptop computer with a reasonable processing time (less than 2.5 h) Numéro de notice : A2017-140 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs9030277 Date de publication en ligne : 16/03/2017 En ligne : http://doi.org/10.3390/rs9030277 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84614
in Remote sensing > vol 9 n° 3 (March 2017) . - pp 277[article]Joint inpainting of depth and reflectance with visibility estimation / Marco Bevilacqua in ISPRS Journal of photogrammetry and remote sensing, vol 125 (March 2017)
[article]
Titre : Joint inpainting of depth and reflectance with visibility estimation Type de document : Article/Communication Auteurs : Marco Bevilacqua, Auteur ; Jean-François Aujol, Auteur ; Pierre Biasutti , Auteur ; Mathieu Brédif , Auteur ; Aurélie Bugeau, Auteur Année de publication : 2017 Projets : 1-Pas de projet / Métral, Claudine Article en page(s) : pp 16 - 32 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] carte de profondeur
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image en couleur
[Termes IGN] inpainting
[Termes IGN] point caché
[Termes IGN] réflectance
[Termes IGN] semis de points
[Termes IGN] visibilitéRésumé : (Auteur) This paper presents a novel strategy to generate, from 3-D lidar measures, dense depth and reflectance images coherent with given color images. It also estimates for each pixel of the input images a visibility attribute. 3-D lidar measures carry multiple information, e.g. relative distances to the sensor (from which we can compute depths) and reflectances. When projecting a lidar point cloud onto a reference image plane, we generally obtain sparse images, due to undersampling. Moreover, lidar and image sensor positions typically differ during acquisition; therefore points belonging to objects that are hidden from the image view point might appear in the lidar images. The proposed algorithm estimates the complete depth and reflectance images, while concurrently excluding those hidden points. It consists in solving a joint (depth and reflectance) variational image inpainting problem, with an extra variable to concurrently estimate handling the selection of visible points. As regularizers, two coupled total variation terms are included to match, two by two, the depth, reflectance, and color image gradients. We compare our algorithm with other image-guided depth upsampling methods, and show that, when dealing with real data, it produces better inpainted images, by solving the visibility issue. Numéro de notice : A2017-073 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.01.005 Date de publication en ligne : 17/01/2017 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2017.01.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84310
in ISPRS Journal of photogrammetry and remote sensing > vol 125 (March 2017) . - pp 16 - 32[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2017031 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017033 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2017032 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt Mapping forest attributes using data from stereophotogrammetry of aerial images and field data from the national forest inventory / Jonas Bohlin in Silva fennica, vol 51 n° 2 (2017)PermalinkMapping spatial distribution of forest age in China / Yuan Zhang in Earth and space science, vol 4 n° 3 (March 2017)PermalinkReconstructing forest canopy from the 3D triangulations of airborne laser scanning point data for the visualization and planning of forested landscapes / Jari Vauhkonen in Annals of Forest Science, vol 74 n° 1 (March 2017)PermalinkAerial lidar point cloud voxelization with its 3D ground filtering application / Liying Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 2 (February 2017)PermalinkCharacterizing vegetation canopy structure using airborne remote sensing data / Debsunder Dutta in IEEE Transactions on geoscience and remote sensing, vol 55 n° 2 (February 2017)PermalinkClimatic microrefugia under anthropogenic climate change: implications for species redistribution / Jonathan Lenoir in Ecography, vol 40 n° 2 (February 2017)PermalinkIntegrating elevation data and multispectral high-resolution images for an improved hybrid Land Use/Land Cover mapping / Mirco Sturari in European journal of remote sensing, vol 50 n° 1 (2017)PermalinkMultiview marker-free registration of forest terrestrial laser scanner data with embedded confidence metrics / David Kelbe in IEEE Transactions on geoscience and remote sensing, vol 55 n° 2 (February 2017)PermalinkOn the fusion of lidar and aerial color imagery to detect urban vegetation and buildings / Madhurima Bandyopadhyay in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 2 (February 2017)PermalinkTerrestrial laser scanning as a tool for assessing tree growth / Jonathan Sheppard in iForest, biogeosciences and forestry, vol 10 n° 1 (February 2017)Permalink