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Object-based classification of terrestrial laser scanning point clouds for landslide monitoring / Andreas Mayr in Photogrammetric record, vol 32 n° 160 (December 2017)  

Public [article]  inPhotogrammetric record > vol 32 n° 160 (December 2017) . - pp 377 - 397 Titre : Object-based classification of terrestrial laser scanning point clouds for landslide monitoring Type de document : Article/Communication Auteurs : Andreas Mayr, Auteur ; Martin Rutzinger, Auteur ; Magnus Bremer, Auteur ; Sander J. Oude Elberink, Auteur ; Felix Stumpf, Auteur ; Clemens Geitner, Auteur Année de publication : 2017 Conférence : VGC 2016, 2nd virtual geoscience conference 22/09/2016 23/09/2016 Bergen Norvège Proceedings Wiley Article en page(s) : pp 377 - 397 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] apprentissage automatique [Termes IGN] classification orientée objet [Termes IGN] compréhension de l'image [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] effondrement de terrain [Termes IGN] relation topologique 3D [Termes IGN] semis de points [Termes IGN] surveillance géologique Résumé : (auteur) Terrestrial laser scanning (TLS) is often used to monitor landslides and other gravitational mass movements with high levels of geometric detail and accuracy. However, unstructured TLS point clouds lack semantic information, which is required to geomorphologically interpret the measured changes. Extracting meaningful objects in a complex and dynamic environment is challenging due to the objects' fuzziness in reality, as well as the variability and ambiguity of their patterns in a morphometric feature space. This work presents a point‐cloud‐based approach for classifying multitemporal scenes of a hillslope affected by shallow landslides. The 3D point clouds are segmented into morphologically homogeneous and spatially connected parts. These segments are classified into seven target classes (scarp, eroded area, deposit, rock outcrop and different classes of vegetation) in a two‐step procedure: a supervised classification step with a machine‐learning classifier using morphometric features, followed by a correction step based on topological rules. This improves the final object extraction considerably. Numéro de notice : A2017-899 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12215 Date de publication en ligne : 13/12/2017 En ligne : https://doi.org/10.1111/phor.12215 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89522 [article]

Crowdsourcing, citizen science or volunteered geographic information? The current state of crowdsourced geographic information / Linda M. See in ISPRS International journal of geo-information, vol 5 n° 5 (May 2016)    

Public [article]  inISPRS International journal of geo-information > vol 5 n° 5 (May 2016) . - pp 1 - 23 Titre : Crowdsourcing, citizen science or volunteered geographic information? The current state of crowdsourced geographic information Type de document : Article/Communication Auteurs : Linda M. See, Auteur ; Peter Mooney, Auteur ; Giles M. Foody, Auteur ; Lucy Bastin, Auteur ; Alexis Comber, Auteur ; Jacinto Estima, Auteur ; Steffen Fritz, Auteur ; Norman Kerle, Auteur ; Bin Jiang, Auteur ; Mari Laakso, Auteur ; Hai-Ying Liu, Auteur ; Grega Milčinski, Auteur ; Matej Nikšič, Auteur ; Marco Painho, Auteur ; Andrea Pődör, Auteur ; Ana-Maria Olteanu-Raimond , Auteur ; Martin Rutzinger, Auteur Année de publication : 2016 Article en page(s) : pp 1 - 23 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] analyse du discours [Termes IGN] cartographie collaborative [Termes IGN] citoyen [Termes IGN] données localisées des bénévoles [Termes IGN] état de l'art [Termes IGN] participation du public [Termes IGN] production participative [Termes IGN] science citoyenne [Termes IGN] terminologie Résumé : (Auteur) Citizens are increasingly becoming an important source of geographic information, sometimes entering domains that had until recently been the exclusive realm of authoritative agencies. This activity has a very diverse character as it can, amongst other things, be active or passive, involve spatial or aspatial data and the data provided can be variable in terms of key attributes such as format, description and quality. Unsurprisingly, therefore, there are a variety of terms used to describe data arising from citizens. In this article, the expressions used to describe citizen sensing of geographic information are reviewed and their use over time explored, prior to categorizing them and highlighting key issues in the current state of the subject. The latter involved a review of ~100 Internet sites with particular focus on their thematic topic, the nature of the data and issues such as incentives for contributors. This review suggests that most sites involve active rather than passive contribution, with citizens typically motivated by the desire to aid a worthy cause, often receiving little training. As such, this article provides a snapshot of the role of citizens in crowdsourcing geographic information and a guide to the current status of this rapidly emerging and evolving subject. Numéro de notice : A2016--119 Affiliation des auteurs : LASTIG COGIT+Ext (2012-2019) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi5050055 En ligne : http://dx.doi.org/10.3390/ijgi5050055 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84782 [article]

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Derivation of tree skeletons and error assessment using LiDAR point cloud data of varying quality / Magnus Bremer in ISPRS Journal of photogrammetry and remote sensing, vol 80 (June 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 80 (June 2013) . - pp 39 - 50 Titre : Derivation of tree skeletons and error assessment using LiDAR point cloud data of varying quality Type de document : Article/Communication Auteurs : Magnus Bremer, Auteur ; Martin Rutzinger, Auteur ; V. Wichmann, Auteur Année de publication : 2013 Article en page(s) : pp 39 - 50 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] arbre (flore) [Termes IGN] artefact [Termes IGN] données lidar [Termes IGN] semis de points [Termes IGN] squelettisation [Termes IGN] vecteur propre Résumé : (Auteur) The architecture of trees is of particular interest for 3D model creation in forestry and ecolocical applications. Terrestrial (TLS) and mobile laser scanning (MLS) systems are used to acquire detailed geometrical data of trees. Since 3D point clouds from laser scanning consist of large data amounts representing uninterpreted topographical information including noise and data gaps, an extraction of salient tree structures is important for further applications. We present a fully automated modular workflow for topological reliable reconstruction of tree architecture. Object-based point cloud processing such as branch extraction is combined with tree skeletonization. Branch extraction is performed using a segmentation procedure followed by segment-based analysis of form indices derived from eigenvector metrics. Extracted branch primitives are simplified and connected to line features during skeletonization. The modular workflow allows comprehensive parameter tests and error assessments that are used for a calibration of the module parameters with respect to various characteristics of the input data (e.g noise, scanning resolution, and the number of scan positions). The estimated parameter settings are validated using an exemplary MLS data set. The quality of input point cloud data, strongly influencing the quality of the skeleton results, can be improved by the presented branch extraction procedure. The potential for data improvement increases with increasing point densities. For our object-based appoach, we can show that the presence of erroneous structures and filtering artifacts have the strongest influence onto the quality of the derived skeletons. In contrast to traditional skeletonization approaches, the existance of data gaps has less influence onto the results. Numéro de notice : A2013-297 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.03.003 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.03.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32435 [article]

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081-2013061	RAB	Revue	Centre de documentation	En réserve L003	Disponible

EuroSDR project Commission 2, Mobile mapping - road environment mapping using mobile laser scanning / Harri Kaartinen (2013)

Public contenu dans EuroSDR-Project, Commission 1 and Commission 2 / Eija Honkavaara (March 2013)     Titre : EuroSDR project Commission 2, Mobile mapping - road environment mapping using mobile laser scanning : final report Type de document : Chapitre/Contribution Auteurs : Harri Kaartinen, Auteur ; Juha Hyyppä, Auteur ; Antero Kukko, Auteur ; Matti Lehtomäki, Auteur ; Anttoni Jaakkola, Auteur ; M. George Vosselman, Auteur ; Sander J. Oude Elberink, Auteur ; Martin Rutzinger, Auteur ; Shi Pu, Auteur ; Matti Vaaja, Auteur Editeur : Dublin : European Spatial Data Research EuroSDR Année de publication : 2013 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] base de données routières [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] lasergrammétrie [Termes IGN] système de numérisation mobile [Termes IGN] télémétrie laser Note de contenu : 1. Introduction 2. State-of-the-art in mobile laser scanning 3. Benchmarking of mobile laser scanning systems on a test field 4. Benchmarking of pole detection algorithms 5. Discusion ans conclusions Numéro de notice : H2013-009 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Chapître / contribution Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75593

Recognizing basic structures from mobile laser scanning data for road inventory studies / Shi Pu in ISPRS Journal of photogrammetry and remote sensing, vol 66 n° 6 supplement (December 2011)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 66 n° 6 supplement (December 2011) . - pp 28 - 39 Titre : Recognizing basic structures from mobile laser scanning data for road inventory studies Type de document : Article/Communication Auteurs : Shi Pu, Auteur ; Martin Rutzinger, Auteur ; M. George Vosselman, Auteur ; Sander J. Oude Elberink, Auteur Année de publication : 2011 Article en page(s) : pp 28 - 39 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] classification ascendante hiérarchique [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] reconnaissance de formes [Termes IGN] réseau routier [Termes IGN] semis de points [Termes IGN] zone urbaine dense Résumé : (Auteur) Road safety inspection is currently carried out by time-consuming visual inspection. The latest mobile mapping systems provide an efficient technique for acquiring very dense point clouds along road corridors, so that automated procedures for recognizing and extracting structures can be developed. This paper presents a framework for structure recognition from mobile laser scanned point clouds. It starts with an initial rough classification into three larger categories: ground surface, objects on ground, and objects off ground. Based on a collection of characteristics of point cloud segments like size, shape, orientation and topological relationships, the objects on ground are assigned to more detailed classes such as traffic signs, trees, building walls and barriers. Two mobile laser scanning data sets acquired by different systems are tested with the recognition methods. Performance analyses of the test results are provided to demonstrate the applicability and limits of the methods. While poles are recognized for up to 86%, classification into further categories requires further work and integration with imagery. Numéro de notice : A2011-516 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2011.08.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2011.08.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31410 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
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