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Adaptive algorithm for large scale DTM interpolation from lidar data for forestry applications in steep forested terrain / Almasi S. Maguya in ISPRS Journal of photogrammetry and remote sensing, vol 85 (November 2013)
[article]
Titre : Adaptive algorithm for large scale DTM interpolation from lidar data for forestry applications in steep forested terrain Type de document : Article/Communication Auteurs : Almasi S. Maguya, Auteur ; Virpi Junttila, Auteur ; Tuomo Kauranne, Auteur Année de publication : 2013 Article en page(s) : pp 74 - 83 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] couvert forestier
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] filtrage de points
[Termes IGN] fonction spline d'interpolation
[Termes IGN] hauteur des arbres
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] modèle numérique de terrain
[Termes IGN] morphologie mathématique
[Termes IGN] Népal
[Termes IGN] penteRésumé : (Auteur) Light Detection and Ranging (lidar) has become a valuable tool in forest inventory because it yields accurate measurements of tree heights. However, tree height can be accurate only if the height of the ground, i. e., the Digital Terrain Model (dtm) is first accurately established. Although great advances have been made in lidar technology over the past decade, filtering lidar data for Digital Terrain Model (dtm) interpolation is still a challenge, especially in steep and complex terrain with forest cover. Several algorithms proposed in the literature address this challenge but their performance deteriorates with the decreasing point density caused by the presence of forest cover and steep slopes. In this paper, we propose a new adaptive algorithm for dtm interpolation from lidar data in steep terrain with forest cover. The algorithm partitions the input data and estimates a section of the dtm by fitting a linear or quadratic trend surface, or uses cubic spline interpolation depending on the complexity of the section of terrain. The performance of the algorithm is tested in three ways: by visual assessment, by comparison of the tree-height estimates produced using the generated dtm with those obtained using field survey, and by use of International Society for Photogrammetry and Remote Sensing (isprs) test data. Test results show that the algorithm can cope well with steep slopes and low lidar point densities, giving a more accurate estimate of average tree height compared to conventional algorithms. The algorithm can be used for dtm extraction in large scale forest inventory projects in challenging environments–complex terrain and low lidar point densities. Numéro de notice : A2013-608 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.08.005 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.08.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32744
in ISPRS Journal of photogrammetry and remote sensing > vol 85 (November 2013) . - pp 74 - 83[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2013111 RAB Revue Centre de documentation En réserve L003 Disponible An automated algorithm for extracting road edges from terrestrial mobile LiDAR data / Pankaj Kumar in ISPRS Journal of photogrammetry and remote sensing, vol 85 (November 2013)
[article]
Titre : An automated algorithm for extracting road edges from terrestrial mobile LiDAR data Type de document : Article/Communication Auteurs : Pankaj Kumar, Auteur ; Conor P. Mcelhinney, Auteur ; Paul Lewis, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 44 - 55 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction automatique
[Termes IGN] extraction du réseau routier
[Termes IGN] semis de points
[Termes IGN] télémétrie laser terrestreRésumé : (Auteur) Terrestrial mobile laser scanning systems provide rapid and cost effective 3D point cloud data which can be used for extracting features such as the road edge along a route corridor. This information can assist road authorities in carrying out safety risk assessment studies along road networks. The knowledge of the road edge is also a prerequisite for the automatic estimation of most other road features. In this paper, we present an algorithm which has been developed for extracting left and right road edges from terrestrial mobile LiDAR data. The algorithm is based on a novel combination of two modified versions of the parametric active contour or snake model. The parameters involved in the algorithm are selected empirically and are fixed for all the road sections. We have developed a novel way of initialising the snake model based on the navigation information obtained from the mobile mapping vehicle. We tested our algorithm on different types of road sections representing rural, urban and national primary road sections. The successful extraction of road edges from these multiple road section environments validates our algorithm. These findings and knowledge provide valuable insights as well as a prototype road edge extraction tool-set, for both national road authorities and survey companies. Numéro de notice : A2013-606 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.08.003 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.08.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32742
in ISPRS Journal of photogrammetry and remote sensing > vol 85 (November 2013) . - pp 44 - 55[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2013111 RAB Revue Centre de documentation En réserve L003 Disponible Large-scale classification of water areas using airborne topographic lidar data / Julien Smeeckaert in Remote sensing of environment, vol 138 (November 2013)
[article]
Titre : Large-scale classification of water areas using airborne topographic lidar data Type de document : Article/Communication Auteurs : Julien Smeeckaert, Auteur ; Clément Mallet , Auteur ; Nicolas David , Auteur ; Nesrine Chehata , Auteur ; António Ferraz , Auteur Année de publication : 2013 Article en page(s) : pp 134 - 148 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] grande échelle
[Termes IGN] littoral
[Termes IGN] modèle numérique de terrain
[Termes IGN] rive
[Termes IGN] rivière
[Termes IGN] semis de points
[Termes IGN] trait de côteRésumé : (auteur) Accurate Digital Terrain Models (DTMs) are inevitable inputs for mapping and analyzing areas subject to natural hazards. Topographic airborne laser scanning has become an established technique to characterize the Earth's surface: lidar provides 3D point clouds allowing for a fine reconstruction of the topography while preserving high frequencies of the relief. For flood hazard modeling, the key step, before going onto terrain modeling, is the discrimination of land and water areas within the delivered point clouds. Therefore, instantaneous shorelines, river banks, and inland waters can be extracted as a basis for more reliable DTM generation. This paper presents an automatic, efficient, and versatile workflow for land/water classification of airborne topographic lidar points, effective at large scales (>300 km2). For that purpose, the Support Vector Machine (SVM) method is used as a classification framework and it is embedded in a workflow designed for our specific goal. First, a restricted but carefully designed set of features, based only on 3D lidar point coordinates and flightline information, is defined as classifier input. Then, the SVM learning step is performed on small but well-targeted areas thanks to a semiautomatic region growing strategy. Finally, label probability output by SVM is merged with contextual knowledge during a probabilistic relaxation step in order to remove pixel-wise misclassification. Results show that a survey of hundreds of millions of points are labeled with high accuracy (>95% in most cases for coastal areas, and >90% for rivers) and that small natural and anthropic features of interest are still well classified even though we work at lowpoint densities (0.5–4 pts/m2). We also noticed that it may fail in water-logged areas. Nevertheless, our approach remains valid for regional and national mapping purposes, coasts and rivers, and provides a strong basis for further discrimination of land-cover classes and coastal habitats. Numéro de notice : A2013-792 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2013.07.004 Date de publication en ligne : 15/08/2013 En ligne : https://doi.org/10.1016/j.rse.2013.07.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80174
in Remote sensing of environment > vol 138 (November 2013) . - pp 134 - 148[article]Semi-automatic road/pavement modeling using mobile laser scanning / Alexandre Hervieu in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 W3 (November 2013)
[article]
Titre : Semi-automatic road/pavement modeling using mobile laser scanning Type de document : Article/Communication Auteurs : Alexandre Hervieu , Auteur ; Bahman Soheilian , Auteur Année de publication : 2013 Projets : 1-Pas de projet / Conférence : CMRT 2013, City Models, Roads and Traffic 12/11/2013 13/11/2013 Antalya Turquie OA ISPRS Annals Article en page(s) : pp 31 - 36 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] chaussée
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] modèle numérique
[Termes IGN] précision centimétriqueRésumé : (auteur) Scene analysis, in urban environments, deals with street modeling and understanding. A street mainly consists of roadways, pavements (i.e., walking areas), facades, still and moving obstacles. In this paper, we investigate the surface modeling of roadways and pavements using LIDAR data acquired by a mobile laser scanning (MLS) system. First, road border detection is considered. A system recognizing curbs and curb ramps while reconstructing the missing information in case of occlusion is presented. A user interface scheme is also described, providing an effective tool for semi-automatic processing of large amount of data. Then, based upon road edge information, a process that reconstructs surfaces of roads and pavements has been developed, providing a centimetric precision while reconstructing missing information. This system hence provides an important knowledge of the street, that may open perspectives in various domains such as path planning or road maintenance. Numéro de notice : A2013-794 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprsannals-II-3-W3-31-2013 Date de publication en ligne : 08/10/2013 En ligne : http://dx.doi.org/10.5194/isprsannals-II-3-W3-31-2013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80400
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol II-3 W3 (November 2013) . - pp 31 - 36[article]Single tree biomass modelling using airborne laser scanning / Ville Kankare in ISPRS Journal of photogrammetry and remote sensing, vol 85 (November 2013)
[article]
Titre : Single tree biomass modelling using airborne laser scanning Type de document : Article/Communication Auteurs : Ville Kankare, Auteur ; Minna Räty, Auteur ; Xiaowei Yu, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 66 - 73 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] biomasse (combustible)
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] estimation statistique
[Termes IGN] extraction automatique
[Termes IGN] Picea abies
[Termes IGN] Pinus sylvestris
[Termes IGN] semis de points
[Termes IGN] troncRésumé : (Auteur) Accurate forest biomass mapping methods would provide the means for e.g. detecting bioenergy potential, biofuel and forest-bound carbon. The demand for practical biomass mapping methods at all forest levels is growing worldwide, and viable options are being developed. Airborne laser scanning (ALS) is a promising forest biomass mapping technique, due to its capability of measuring the three-dimensional forest vegetation structure. The objective of the study was to develop new methods for tree-level biomass estimation using metrics derived from ALS point clouds and to compare the results with field references collected using destructive sampling and with existing biomass models. The study area was located in Evo, southern Finland. ALS data was collected in 2009 with pulse density equalling approximately 10 pulses/m2. Linear models were developed for the following tree biomass components: total, stem wood, living branch and total canopy biomass. ALS-derived geometric and statistical point metrics were used as explanatory variables when creating the models. The total and stem biomass root mean square error per cents equalled 26.3% and 28.4% for Scots pine (Pinus sylvestris L.), and 36.8% and 27.6% for Norway spruce (Picea abies (L.) H. Karst.), respectively. The results showed that higher estimation accuracy for all biomass components can be achieved with models created in this study compared to existing allometric biomass models when ALS-derived height and diameter were used as input parameters. Best results were achieved when adding field-measured diameter and height as inputs in the existing biomass models. The only exceptions to this were the canopy and living branch biomass estimations for spruce. The achieved results are encouraging for the use of ALS-derived metrics in biomass mapping and for further development of the models. Numéro de notice : A2013-607 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.08.008 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.08.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32743
in ISPRS Journal of photogrammetry and remote sensing > vol 85 (November 2013) . - pp 66 - 73[article]Réservation
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