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Local curvature entropy-based 3D terrain representation using a comprehensive Quadtree / Giyu Chen in ISPRS Journal of photogrammetry and remote sensing, vol 139 (May 2018)
[article]
Titre : Local curvature entropy-based 3D terrain representation using a comprehensive Quadtree Type de document : Article/Communication Auteurs : Giyu Chen, Auteur ; Gang Liu, Auteur ; Xiaogang Ma, Auteur ; Gregoire Mariethoz, Auteur ; Zhenwen He, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 30 - 45 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] arbre quadratique
[Termes IGN] entropie
[Termes IGN] modèle numérique de terrain
[Termes IGN] niveau de détail
[Termes IGN] visualisation 3DRésumé : (Auteur) Large scale 3D digital terrain modeling is a crucial part of many real-time applications in geoinformatics. In recent years, the improved speed and precision in spatial data collection make the original terrain data more complex and bigger, which poses challenges for data management, visualization and analysis. In this work, we presented an effective and comprehensive 3D terrain representation based on local curvature entropy and a dynamic Quadtree. The Level-of-detail (LOD) models of significant terrain features were employed to generate hierarchical terrain surfaces. In order to reduce the radical changes of grid density between adjacent LODs, local entropy of terrain curvature was regarded as a measure of subdividing terrain grid cells. Then, an efficient approach was presented to eliminate the cracks among the different LODs by directly updating the Quadtree due to an edge-based structure proposed in this work. Furthermore, we utilized a threshold of local entropy stored in each parent node of this Quadtree to flexibly control the depth of the Quadtree and dynamically schedule large-scale LOD terrain. Several experiments were implemented to test the performance of the proposed method. The results demonstrate that our method can be applied to construct LOD 3D terrain models with good performance in terms of computational cost and the maintenance of terrain features. Our method has already been deployed in a geographic information system (GIS) for practical uses, and it is able to support the real-time dynamic scheduling of large scale terrain models more easily and efficiently. Numéro de notice : A2018-110 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.03.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.03.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89540
in ISPRS Journal of photogrammetry and remote sensing > vol 139 (May 2018) . - pp 30 - 45[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2018051 RAB Revue Centre de documentation En réserve L003 Disponible A spatio-temporal index for aerial full waveform laser scanning data / Debra F. Laefer in ISPRS Journal of photogrammetry and remote sensing, vol 138 (April 2018)
[article]
Titre : A spatio-temporal index for aerial full waveform laser scanning data Type de document : Article/Communication Auteurs : Debra F. Laefer, Auteur ; Anh-Vu Vo, Auteur ; Michela Bertolotto, Auteur Année de publication : 2018 Article en page(s) : pp 232 - 251 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] arbre-R
[Termes IGN] base de données localisées
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forme d'onde pleine
[Termes IGN] index spatiotemporel
[Termes IGN] indexation spatiale
[Termes IGN] octreeRésumé : (Auteur) Aerial laser scanning is increasingly available in the full waveform version of the raw signal, which can provide greater insight into and control over the data and, thus, richer information about the scanned scenes. However, when compared to conventional discrete point storage, preserving raw waveforms leads to vastly larger and more complex data volumes. To begin addressing these challenges, this paper introduces a novel bi-level approach for storing and indexing full waveform (FWF) laser scanning data in a relational database environment, while considering both the spatial and the temporal dimensions of that data. In the storage scheme's upper level, the full waveform datasets are partitioned into spatial and temporal coherent groups that are indexed by a two-dimensional R∗-tree. To further accelerate intra-block data retrieval, at the lower level a three-dimensional local octree is created for each pulse block. The local octrees are implemented in-memory and can be efficiently written to a database for reuse. The indexing solution enables scalable and efficient three-dimensional (3D) spatial and spatio-temporal queries on the actual pulse data - functionalities not available in other systems. The proposed FWF laser scanning data solution is capable of managing multiple FWF datasets derived from large flight missions. The flight structure is embedded into the data storage model and can be used for querying predicates. Such functionality is important to FWF data exploration since aircraft locations and orientations are frequently required for FWF data analyses. Empirical tests on real datasets of up to 1 billion pulses from Dublin, Ireland prove the almost perfect scalability of the system. The use of the local 3D octree in the indexing structure accelerated pulse clipping by 1.2–3.5 times for non-axis-aligned (NAA) polyhedron shaped clipping windows, while axis-aligned (AA) polyhedron clipping was better served using only the top indexing layer. The distinct behaviours of the hybrid indexing for AA and NAA clipping windows are attributable to the different proportion of the local-index-related overheads with respect to the total querying costs. When temporal constraints were added, generally the number of costly spatial checks were reduced, thereby shortening the querying times. Numéro de notice : A2018-125 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.01.012 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.01.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89587
in ISPRS Journal of photogrammetry and remote sensing > vol 138 (April 2018) . - pp 232 - 251[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2018041 RAB Revue Centre de documentation En réserve L003 Disponible 081-2018043 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2018042 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt Analyse de l'incertitude et de la précision thématique de classifications GEOBIA d'une image WorldView-2 / François Messner in Revue Française de Photogrammétrie et de Télédétection, n° 216 (février 2018)
[article]
Titre : Analyse de l'incertitude et de la précision thématique de classifications GEOBIA d'une image WorldView-2 Type de document : Article/Communication Auteurs : François Messner, Auteur ; Jeannine Corbonnois, Auteur ; Fanny Stella Tchitouo Ntenzou, Auteur Année de publication : 2018 Article en page(s) : pp 19 - 37 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse discriminante
[Termes IGN] arbre de décision
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification dirigée
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] distance de Kullback-Leibler
[Termes IGN] ensachage
[Termes IGN] entropie
[Termes IGN] image Worldview
[Termes IGN] modèle orienté objet
[Termes IGN] précision de la classification
[Termes IGN] Sarthe (72)Résumé : (Auteur) L'évaluation de la précision des cartes thématiques produites par télédétection est une finalité de tout processus de classification modélisant le paysage. Reposant traditionnellement sur la matrice de confusion, elle peut être complétée par des méthodes alternatives plus à même de prendre en compte le biais relatif à la sélection des échantillons d'apprentissage, ainsi que par l'emploi d'approches représentant spatialement l'incertitude inhérente aux classifications. Une telle démarche est adoptée dans cet article, en évaluant la précision à l'aide des estimateurs du Maximum de Probabilité a Posteriori, puis en déterminant, pour chaque unité de carte, des mesures d'incertitude : l'entropie a quadratique, la divergence de Kullback-Leibler et un indice de concordance qualitatif. Ces traitements sont analysés et comparés selon 3 classifieurs, Random Forest, C5.0 et l'Analyse Discriminante Linéaire et selon 4 stratégies de classification : classifieurs seuls, classifieurs avec procédure de bagging, classifieurs avec procédure d'apprentissage actifs et classifieurs avec procédure d'apprentissage actif et de bagging. Les résultats obtenus soulignent la complémentarité des estimateurs de précision pour mettre en évidence un biais dans l'évaluation de la précision ou dans la détermination des probabilités a posteriori, et justifie la prise en considération des indices d'incertitude comme source d'informations sur la distribution spatiale des erreurs de cartographie. Numéro de notice : A2018-092 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.52638/rfpt.2018.310 Date de publication en ligne : 19/04/2018 En ligne : https://doi.org/10.52638/rfpt.2018.310 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89502
in Revue Française de Photogrammétrie et de Télédétection > n° 216 (février 2018) . - pp 19 - 37[article]Semantic enrichment of octree structured point clouds for multi‐story 3D pathfinding / Florian W. Fichtner in Transactions in GIS, vol 22 n° 1 (February 2018)
[article]
Titre : Semantic enrichment of octree structured point clouds for multi‐story 3D pathfinding Type de document : Article/Communication Auteurs : Florian W. Fichtner, Auteur ; Abdoulaye A. Diakité, Auteur ; Sisi Zlatanova, Auteur ; Robert Voûte, Auteur Année de publication : 2018 Article en page(s) : pp 233 - 248 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] calcul d'itinéraire
[Termes IGN] espace intérieur vide
[Termes IGN] information sémantique
[Termes IGN] octree
[Termes IGN] positionnement en intérieur
[Termes IGN] semis de pointsRésumé : (auteur) 3D indoor navigation in multi‐story buildings and under changing environments is still difficult to perform. 3D models of buildings are commonly not available or outdated. 3D point clouds turned out to be a very practical way to capture 3D interior spaces and provide a notion of an empty space. Therefore, pathfinding in point clouds is rapidly emerging. However, processing of raw point clouds can be very expensive, as these are semantically poor and unstructured data. In this article we present an innovative octree‐based approach for processing of 3D indoor point clouds for the purpose of multi‐story pathfinding. We semantically identify the construction elements, which are of importance for the indoor navigation of humans (i.e., floors, walls, stairs, and obstacles), and use these to delineate the available navigable space. To illustrate the usability of this approach, we applied it to real‐world data sets and computed paths considering user constraints. The structuring of the point cloud into an octree approximation improves the point cloud processing and provides a structure for the empty space of the point cloud. It is also helpful to compute paths sufficiently accurate in their consideration of the spatial complexity. The entire process is automatic and able to deal with a large number of multi‐story indoor environments. Numéro de notice : A2018-067 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12308 En ligne : https://doi.org/10.1111/tgis.12308 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89423
in Transactions in GIS > vol 22 n° 1 (February 2018) . - pp 233 - 248[article]Above-bottom biomass retrieval of aquatic plants with regression models and SfM data acquired by a UAV platform – A case study in Wild Duck Lake Wetland, Beijing, China / Ran Jing in ISPRS Journal of photogrammetry and remote sensing, vol 134 (December 2017)
[article]
Titre : Above-bottom biomass retrieval of aquatic plants with regression models and SfM data acquired by a UAV platform – A case study in Wild Duck Lake Wetland, Beijing, China Type de document : Article/Communication Auteurs : Ran Jing, Auteur ; Zhaoning Gong, Auteur ; Wenji Zhao, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 122 - 134 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] arbre de décision
[Termes IGN] biomasse
[Termes IGN] croissance végétale
[Termes IGN] drone
[Termes IGN] image aérienne
[Termes IGN] indice de végétation
[Termes IGN] lac
[Termes IGN] macrophyte
[Termes IGN] modèle de régression
[Termes IGN] orthoimage
[Termes IGN] Pékin (Chine)
[Termes IGN] régression linéaire
[Termes IGN] semis de points
[Termes IGN] structure-from-motion
[Termes IGN] zone humideRésumé : (Auteur) Above-bottom biomass (ABB) is considered as an important parameter for measuring the growth status of aquatic plants, and is of great significance for assessing health status of wetland ecosystems. In this study, Structure from Motion (SfM) technique was used to rebuild the study area with high overlapped images acquired by an unmanned aerial vehicle (UAV). We generated orthoimages and SfM dense point cloud data, from which vegetation indices (VIs) and SfM point cloud variables including average height (HAVG), standard deviation of height (HSD) and coefficient of variation of height (HCV) were extracted. These VIs and SfM point cloud variables could effectively characterize the growth status of aquatic plants, and thus they could be used to develop a simple linear regression model (SLR) and a stepwise linear regression model (SWL) with field measured ABB samples of aquatic plants. We also utilized a decision tree method to discriminate different types of aquatic plants. The experimental results indicated that (1) the SfM technique could effectively process high overlapped UAV images and thus be suitable for the reconstruction of fine texture feature of aquatic plant canopy structure; and (2) an SWL model based on point cloud variables: HAVG, HSD, HCV and two VIs: NGRDI, ExGR as independent variables has produced the best predictive result of ABB of aquatic plants in the study area, with a coefficient of determination of 0.84 and a relative root mean square error of 7.13%. In this analysis, a novel method for the quantitative inversion of a growth parameter (i.e., ABB) of aquatic plants in wetlands was demonstrated. Numéro de notice : A2017-732 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.11.002 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.11.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88431
in ISPRS Journal of photogrammetry and remote sensing > vol 134 (December 2017) . - pp 122 - 134[article]Réservation
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