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A new method for 3D individual tree extraction using multispectral airborne LiDAR point clouds / Wenxia Dai in ISPRS Journal of photogrammetry and remote sensing, vol 144 (October 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 144 (October 2018) . - pp 400 - 411 Titre : A new method for 3D individual tree extraction using multispectral airborne LiDAR point clouds Type de document : Article/Communication Auteurs : Wenxia Dai, Auteur ; Yang Bisheng, Auteur ; Zhen Dong, Auteur ; Ahmed Shaker, Auteur Année de publication : 2018 Article en page(s) : pp 400 - 411 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] extraction d'arbres [Termes IGN] forêt [Termes IGN] houppier [Termes IGN] Ontario (Canada) [Termes IGN] Pinophyta [Termes IGN] segmentation [Termes IGN] semis de points Résumé : (Auteur) Characterization of individual trees is essential for many applications in forest management and ecology. Previous studies relied on single tree detection from monochromatic wavelength airborne laser scanning (ALS) systems and they focused on the use of the geometric spatial information of the point clouds (i.e., X, Y, and Z coordinates). However, there is quite often a difficulty dealing with clumped trees when only the geometric spatial information is considered. The emergence of multispectral LiDAR sensors provides a new solution for individual tree structure acquisition. The aim of this paper is to investigate the performance of multispectral ALS data for delineating individual trees which are challenging by using the monochromatic wavelength ALS system. The proposed workflow utilizes the mean shift segmentation method on different feature spaces for crown isolation. In addition, both spatial domain and multispectral domain are used to refine the under-segmentation crown segments. Ten plots (2 sets of different structural complexity) located in the dense coniferous forest area in Tobermory, Ontario, Canada are selected as experiment data. Results show that the developed method correctly detects 88% and 82% of the dominant trees with and without multispectral information, respectively. Compared with segmentation using geometric spatial information solely, the main improvements are achieved for clumped tree segment with the distinguished multispectral features. This study demonstrates that multispectral airborne laser scanning data is more capable for individual tree delineation than monochromatic wavelength laser scanning data in dealing with forests with clumped crowns in dense forests. Numéro de notice : A2018-404 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.08.010 Date de publication en ligne : 17/08/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.08.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90862 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2018101	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2018103	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2018102	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt

3D 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)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 130 (August 2017) . - pp 329 - 343 Titre : 3D local feature BKD to extract road information from mobile laser scanning point clouds Type de document : Article/Communication Auteurs : Yang Bisheng, Auteur ; Yuan Liu, Auteur ; Zhen Dong, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 329 - 343 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] classificateur [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] densité des points [Termes IGN] données localisées 3D [Termes IGN] estimation par noyau [Termes IGN] extraction du réseau routier [Termes IGN] semis de points [Termes IGN] télémétrie laser mobile [Termes IGN] variable binaire Résumé : (Auteur) Extracting road information from point clouds obtained through mobile laser scanning (MLS) is essential for autonomous vehicle navigation, and has hence garnered a growing amount of research interest in recent years. However, the performance of such systems is seriously affected due to varying point density and noise. This paper proposes a novel three-dimensional (3D) local feature called the binary kernel descriptor (BKD) to extract road information from MLS point clouds. The BKD consists of Gaussian kernel density estimation and binarization components to encode the shape and intensity information of the 3D point clouds that are fed to a random forest classifier to extract curbs and markings on the road. These are then used to derive road information, such as the number of lanes, the lane width, and intersections. In experiments, the precision and recall of the proposed feature for the detection of curbs and road markings on an urban dataset and a highway dataset were as high as 90%, thus showing that the BKD is accurate and robust against varying point density and noise. Numéro de notice : A2017-517 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.06.007 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.06.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86479 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2017081	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2017083	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2017082	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt

A Pattern-based approach for matching nodes in heterogeneous urban road networks / Yang Bisheng in Transactions in GIS, vol 18 n° 5 (October 2014)  

Public [article]  inTransactions in GIS > vol 18 n° 5 (October 2014) . - pp 718 – 739 Titre : A Pattern-based approach for matching nodes in heterogeneous urban road networks Type de document : Article/Communication Auteurs : Yang Bisheng, Auteur ; Xuechen Luan, Auteur ; Y. Zhang, Auteur Année de publication : 2014 Article en page(s) : pp 718 – 739 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] appariement de données localisées [Termes IGN] échangeur routier [Termes IGN] géomatique [Termes IGN] géopositionnement [Termes IGN] niveau de détail [Termes IGN] réseau routier [Termes IGN] système de référence géodésique Résumé : (Auteur) This article presents an approach to hierarchical matching of nodes in heterogeneous road networks in the same urban area. Heterogeneous road networks not only exist at different levels of detail (LoD), but also have different coordinate systems, leading to difficulties in matching and integrating them. To overcome these difficulties, a pattern-based method was implemented. Based on the authors' previous work on detecting patterns of divided highways, complex road junctions, and strokes to eliminate the LoD effect of road networks, the proposed method extracts the local networks around each node in a road network and uses them as the matching units for the nodes. Second, the degree of shape similarity between the matching units is measured using a Minimum Road Edit Distance based on a transformation. Finally, the proposed method hierarchically matches the nodes in a road network using the Minimum Road Edit Distance and eliminates false matching nodes using M-estimators. An experiment involving matching heterogeneous road networks with different LoDs and coordinate systems was carried out to verify the validity of the proposed method. The method achieves good and effective matching regardless of differences in LoDs and road-network coordinate systems. Numéro de notice : A2014-511 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12057 Date de publication en ligne : 07/10/2013 En ligne : https://doi.org/10.1111/tgis.12057 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74111 [article]

A shape-based segmentation method for mobile laser scanning point clouds / Yang Bisheng in ISPRS Journal of photogrammetry and remote sensing, vol 81 (July 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 81 (July 2013) . - pp 19 - 30 Titre : A shape-based segmentation method for mobile laser scanning point clouds Type de document : Article/Communication Auteurs : Yang Bisheng, Auteur ; Zhen Dong, Auteur Année de publication : 2013 Article en page(s) : pp 19 - 30 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] connexité (topologie) [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] segmentation [Termes IGN] semis de points [Termes IGN] traitement automatique de données Résumé : (Auteur) Segmentation of mobile laser point clouds of urban scenes into objects is an important step for post-processing (e.g., interpretation) of point clouds. Point clouds of urban scenes contain numerous objects with significant size variability, complex and incomplete structures, and holes or variable point densities, raising great challenges for the segmentation of mobile laser point clouds. This paper addresses these challenges by proposing a shape-based segmentation method. The proposed method first calculates the optimal neighborhood size of each point to derive the geometric features associated with it, and then classifies the point clouds according to geometric features using support vector machines (SVMs). Second, a set of rules are defined to segment the classified point clouds, and a similarity criterion for segments is proposed to overcome over-segmentation. Finally, the segmentation output is merged based on topological connectivity into a meaningful geometrical abstraction. The proposed method has been tested on point clouds of two urban scenes obtained by different mobile laser scanners. The results show that the proposed method segments large-scale mobile laser point clouds with good accuracy and computationally effective time cost, and that it segments pole-like objects particularly well. Numéro de notice : A2013-386 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.04.002 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.04.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32524 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2013071	RAB	Revue	Centre de documentation	En réserve L003	Disponible