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Robust interpolation of DEMs from lidar-derived elevation data / Chuanfa Chen in IEEE Transactions on geoscience and remote sensing, vol 56 n° 2 (February 2018)
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Titre : Robust interpolation of DEMs from lidar-derived elevation data Type de document : Article/Communication Auteurs : Chuanfa Chen, Auteur ; Yanyan Li, Auteur ; Na Zhao, Auteur ; Changqing Yan, Auteur Année de publication : 2018 Article en page(s) : pp 1059 - 1068 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] fonction spline
[Termes IGN] interpolation
[Termes IGN] méthode robuste
[Termes IGN] modèle numérique de surfaceRésumé : (Auteur) Light detection and ranging (lidar)-derived elevation data are commonly subjected to outliers due to the boundaries of occlusions, physical imperfections of sensors, and surface reflectance. Outliers have a serious negative effect on the accuracy of digital elevation models (DEMs). To decrease the impact of outliers on DEM construction, we propose a robust interpolation algorithm of multiquadric (MQ) based on a regularized least absolute deviation (LAD) technique. The objective function of the proposed method includes a regularization-based smoothing term and an LAD-based fitting term, respectively, used to smooth noisy samples and resist the influence of outliers. To solve the objective function of the proposed method, we develop a simple scheme based on the split-Bregman iteration algorithm. Results from simulated data sets indicate that when sample points are noisy or contaminated by outliers, the proposed method is more accurate than the classical MQ and two recently developed robust algorithms of MQ for surface modeling. Real-world examples of interpolating 1 private and 11 publicly available airborne lidar-derived data sets demonstrate that the proposed method averagely produces better results than two promising interpolation methods including regularized spline with tension (RST) and gridded data-based robust thin plate spline (RTPS). Specifically, the image of RTPS is too smooth to retain terrain details. Although RST can keep subtle terrain features, it is distorted by some misclassified object points (i.e., pseudooutliers). The proposed method obtains a good tradeoff between resisting the effect of outliers and preserving terrain features. Overall, the proposed method can be considered as an alternative for interpolating lidar-derived data sets potentially including outliers. Numéro de notice : A2018-193 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2758795 Date de publication en ligne : 17/10/2017 En ligne : https://doi.org/10.1109/TGRS.2017.2758795 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89858
in IEEE Transactions on geoscience and remote sensing > vol 56 n° 2 (February 2018) . - pp 1059 - 1068[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)
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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]Transformation between surface spherical harmonic expansion of arbitrary high degree and order and double Fourier series on sphere / Toshio Fukushima in Journal of geodesy, vol 92 n° 2 (February 2018)
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Titre : Transformation between surface spherical harmonic expansion of arbitrary high degree and order and double Fourier series on sphere Type de document : Article/Communication Auteurs : Toshio Fukushima, Auteur Année de publication : 2018 Article en page(s) : pp 123 - 130 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie
[Termes IGN] harmonique sphérique
[Termes IGN] série de Fourier
[Termes IGN] transformation géométrique
[Termes IGN] transformation inverseRésumé : (Auteur) In order to accelerate the spherical harmonic synthesis and/or analysis of arbitrary function on the unit sphere, we developed a pair of procedures to transform between a truncated spherical harmonic expansion and the corresponding two-dimensional Fourier series. First, we obtained an analytic expression of the sine/cosine series coefficient of the 4π fully normalized associated Legendre function in terms of the rectangle values of the Wigner d function. Then, we elaborated the existing method to transform the coefficients of the surface spherical harmonic expansion to those of the double Fourier series so as to be capable with arbitrary high degree and order. Next, we created a new method to transform inversely a given double Fourier series to the corresponding surface spherical harmonic expansion. The key of the new method is a couple of new recurrence formulas to compute the inverse transformation coefficients: a decreasing-order, fixed-degree, and fixed-wavenumber three-term formula for general terms, and an increasing-degree-and-order and fixed-wavenumber two-term formula for diagonal terms. Meanwhile, the two seed values are analytically prepared. Both of the forward and inverse transformation procedures are confirmed to be sufficiently accurate and applicable to an extremely high degree/order/wavenumber as 230≈109. The developed procedures will be useful not only in the synthesis and analysis of the spherical harmonic expansion of arbitrary high degree and order, but also in the evaluation of the derivatives and integrals of the spherical harmonic expansion. Numéro de notice : A2018-057 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-017-1049-3 Date de publication en ligne : 13/07/2017 En ligne : https://doi.org/10.1007/s00190-017-1049-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89390
in Journal of geodesy > vol 92 n° 2 (February 2018) . - pp 123 - 130[article]A typification method for linear pattern in urban building generalisation / Xianyong Gong in Geocarto international, vol 33 n° 2 (February 2018)
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Titre : A typification method for linear pattern in urban building generalisation Type de document : Article/Communication Auteurs : Xianyong Gong, Auteur ; Fang Wu, Auteur Année de publication : 2018 Article en page(s) : pp 189 - 207 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] généralisation cartographique automatisée
[Termes IGN] généralisation du bâti
[Termes IGN] itération
[Termes IGN] modèle linéaire
[Termes IGN] reconnaissance de formes
[Termes IGN] triangulation de Delaunay
[Termes IGN] typification
[Vedettes matières IGN] GénéralisationRésumé : (Auteur) This paper presents a typification method for linear pattern in urban building generalization. The proposed method includes two processes. Firstly, structural knowledge in terms of linear pattern is detected using a two-step algorithm taking the advantages of Gestalt visual perception, computational geometry and graph theory. Spatial neighbourhood is captured using interpolated constrained Delaunay triangulation and the resulting proximity graph is pruned to be heterogeneous to get acceptable linear patterns with regard to Gestalt visual perception. Then, a typification strategy is proposed, in which typification is regarded as a progressive and iterative process consisting of elimination, exaggeration and displacement. The typification strategy iteratively executes eliminating the building with minimum overall effect, exaggerating remaining buildings considering key location and spatial characteristics and displacing them to preserve the linear pattern until elimination quantity is satisfied. Experiments show that this proposed strategy is effective and linear patterns are guaranteed with correctness and completeness. Numéro de notice : A2018-034 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2016.1240718 En ligne : https://doi.org/10.1080/10106049.2016.1240718 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89207
in Geocarto international > vol 33 n° 2 (February 2018) . - pp 189 - 207[article]Active learning-based optimized training library generation for object-oriented image classification / Rajeswari Balasubramaniam in IEEE Transactions on geoscience and remote sensing, vol 56 n° 1 (January 2018)
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Titre : Active learning-based optimized training library generation for object-oriented image classification Type de document : Article/Communication Auteurs : Rajeswari Balasubramaniam, Auteur ; Srivalsan Namboodiri, Auteur ; Rama Rao Nidamanuri, Auteur ; Rama Krishna Sai Subrahmanyam Gorthi, Auteur Année de publication : 2018 Article en page(s) : pp 575 - 585 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] apprentissage dirigé
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] image aérienne
[Termes IGN] image multibandeRésumé : (Auteur) In this paper, we introduce an active learning (AL)-based object training library generation for a multiclassifier object-oriented image analysis (OOIA) system. While several AL approaches do exist for pixel-based training library generation and for hyperspectral image classification, there is no standard training library generation strategy for OOIA of very high spatial resolution images. Given a sufficient number of training samples, supervised classification is the method of choice for image classification. However, this strategy becomes computationally expensive with the increase in the number of classes or the number of images to be classified. The above-mentioned issue is solved in this proposed method, where an optimized training library of objects (superpixels) is generated based on a batch mode AL approach. A softmax classifier is used as a detector in this method, which helps in determining the right samples to be chosen for library updation. To this end, we construct a multiclassifier system with max-voting decision to classify an image at pixel level. This algorithm was applied on three different very high-resolution airborne data sets, each with varying complexity in terms of variations in geographical context, sensors, illumination, and view angles. Our method has empirically outperformed the traditional OOIA by producing equivalent accuracy with a training library that is orders of magnitude smaller. In addition, the most distinctive ability of the algorithm is experienced in the most heterogeneous data set, where its performance in terms of accuracy is around twice the performance of the traditional method in the same situation. The generality of this classification strategy is proved through its performance on multispectral images and for cross-domain application. Finally, the robustness of this method is identified by comparing its performance with an alternative AL approach-self-learning-based semisupervised SVM. The capability of the proposed method to handle highly heterogeneous data is identified as the primary reason for its robustness. Numéro de notice : A2018-188 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2751568 Date de publication en ligne : 29/09/2017 En ligne : https://doi.org/10.1109/TGRS.2017.2751568 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89847
in IEEE Transactions on geoscience and remote sensing > vol 56 n° 1 (January 2018) . - pp 575 - 585[article]Adapting an existing semi-automatized image processing chain to enable Sentinel-2 data classification. / Hiyam Elbadri (2018)
PermalinkAn accurate Kriging-based regional ionospheric model using combined GPS/BeiDou observations / Mohamed Abdelazeem in Journal of applied geodesy, vol 12 n° 1 (January 2018)
PermalinkAn (almost) automated process to track the Martians dunes : ac.GetPreciseShifts / Arthur Coqué (2018)
PermalinkPermalinkBayesian statistics and Monte Carlo methods / Karl Rudolf Koch in Journal of geodetic science, vol 8 n° 1 (January 2018)
PermalinkBilan de l’Action COST ES1206 - GNSS4SWEC (Advanced Global Navigation Satellite Systems tropospheric products for monitoring severe weather events and climate) / Olivier Bock (2018)
PermalinkBruit de scintillation dans les séries temporelles de positions GNSS : origines et conséquences / Paul Rebischung (2018)
PermalinkCartographie des déformations de surface sur l’île de Taiwan par interférométrie RADAR Sentinel-1 / Miloud Fekaouni (2018)
PermalinkPermalinkClassification à très haute résolution (THR) spatiale et fusion d'occupation des sols (OCS) / Tristan Postadjian (2018)
PermalinkClassification à très large échelle d'images satellite à très haute résolution spatiale par réseaux de neurones convolutifs / Tristan Postadjian (2018)
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PermalinkComparative study of visual saliency maps in the problem of classification of architectural images with Deep CNNs / Abraham Montoya Obeso (2018)
PermalinkConception d’une méthode radar de suivi bimensuel des déforestations et d’une méthode optique de classification d’occupation des sols / Luc Baudoux (2018)
PermalinkPermalinkPermalinkCrop-rotation structured classification using multi-source sentinel images and LPIS for crop type mapping / Simon Bailly (2018)
PermalinkCut-Pursuit algorithm for regularizing nonsmooth functionals with graph total variation / Hugo Raguet (2018)
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PermalinkDecision fusion of SPOT6 and multitemporal Sentinel2 images for urban area detection / Cyril Wendl (2018)
PermalinkDeep learning based vehicular mobility models for intelligent transportation systems / Jian Zhang (2018)
PermalinkDependency of geodynamic parameters on the GNSS constellation / Stefano Scaramuzza in Journal of geodesy, vol 92 n° 1 (January 2018)
PermalinkDesign and implementation of a model predictive observer for AHRS / Jafar Keighobadi in GPS solutions, vol 22 n° 1 (January 2018)
PermalinkPermalinkDetection and localization of traffic signals with GPS floating car data and Random Forest / Yann Méneroux (2018)
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PermalinkDétermination d’un modèle géopotentiel à haute résolution en zone littorale aidé par des mesures d’horloges atomiques / Hugo Lecomte (2018)
PermalinkDomain adaptation for large scale classification of very high resolution satellite images with deep convolutional neural networks / Tristan Postadjian (2018)
PermalinkPermalinkPermalinkPermalinkPermalinkExploring image fusion of ALOS/PALSAR data and LANDSAT data to differentiate forest area / Saygin Abdikan in Geocarto international, vol 33 n° 1 (January 2018)
PermalinkExploring the impact of seasonality on urban land-cover mapping using multi-season sentinel-1A and GF-1 WFV images in a subtropical monsoon-climate region / Tao Zhou in ISPRS International journal of geo-information, vol 7 n° 1 (January 2018)
PermalinkExploring the relationship between density and completeness of urban building data in OpenStreetMap for quality estimation / Qi Zhou in International journal of geographical information science IJGIS, vol 32 n° 1-2 (January - February 2018)
PermalinkFacade repetition detection in a fronto-parallel view with fiducial lines extraction / Hongfei Xiao in Neurocomputing, vol 273 (January 2018)
PermalinkPermalinkFrom Google Maps to a fine-grained catalog of street trees / Steve Branson in ISPRS Journal of photogrammetry and remote sensing, vol 135 (January 2018)
PermalinkPermalinkFusion tardive d’images SPOT-6/7 et de données multitemporelles Sentinel-2 pour la détection de la tache urbaine / Cyril Wendl (2018)
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PermalinkGéo-référencement précis d'acquisition photogrammétrique de « longues » scènes d'intérieur / Truong Giang Nguyen (2018)
PermalinkGéolocalisation précise basée image : une approche de type “seconde itération du processus photogrammétrique” / Truong Giang Nguyen (2018)
PermalinkGeometric multi-wavelet total variation for SAR image time series analysis / Abdourrahmane M. Atto (2018)
PermalinkPermalinkPermalinkHeight biases of SRTM DEM related to EGM96: from a global perspective to regional practice / A. Üstün in Survey review, vol 50 n° 358 (January 2018)
PermalinkA hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning / Rasmus M. Houborg in ISPRS Journal of photogrammetry and remote sensing, vol 135 (January 2018)
PermalinkPermalinkPermalinkIntroduction to multiple regression equations in datum transformations and their reversibility / Andrew Carey Ruffhead in Survey review, vol 50 n° 358 (January 2018)
PermalinkUn inventaire forestier multisource pour la gestion des territoires / Dinesh Babu Irulappa-Pillai-Vijayakumar (2018)
PermalinkPermalinkLearning multiscale deep features for high-resolution satellite image scene classification / Qingshan Liu in IEEE Transactions on geoscience and remote sensing, vol 56 n° 1 (January 2018)
PermalinkLeveraging correlation across space and time to interpolate geophysical data via CoKriging / Sonja Pravilovic in International journal of geographical information science IJGIS, vol 32 n° 1-2 (January - February 2018)
PermalinkLocalisation d'objets urbains à partir de sources multiples dont des images aériennes / Lionel Pibre (2018)
PermalinkLocalisation par l'image en milieu urbain : application à la réalité augmentée / Antoine Fond (2018)
PermalinkPermalinkMachine learning and pose estimation for autonomous robot grasping with collaborative robots / Victor Talbot (2018)
PermalinkPermalinkPermalinkMéthodes d'inventaire multisource : améliorer la précision des estimations de l'IFN et atteindre l'échelle des territoires [diaporama] / Cédric Vega (2018)
PermalinkMixed integer–real least squares estimation for precise GNSS positioning using a modified ambiguity function approach / Krzysztof Nowel in GPS solutions, vol 22 n° 1 (January 2018)
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PermalinkPermalinkModélisation spatio-temporelle multi-niveau à base d'ontologies pour le suivi de la dynamique en imagerie satellitaire / Fethi Ghazouani (2018)
PermalinkMultiobjective subpixel land-cover mapping / Ailong Ma in IEEE Transactions on geoscience and remote sensing, vol 56 n° 1 (January 2018)
PermalinkNavigation des personnes aux moyens des technologies des smartphones et des données d’environnements cartographiés / Fadoua Taia Alaoui (2018)
PermalinkNumerical solution to the oblique derivative boundary value problem on non-uniform grids above the Earth topography / Matej Medl’a in Journal of geodesy, vol 92 n° 1 (January 2018)
PermalinkA numerical test of the topographic bias / Lars E. Sjöberg in Journal of geodetic science, vol 8 n° 1 (January 2018)
PermalinkObject-based superresolution land-cover mapping from remotely sensed imagery / Yuehong Chen in IEEE Transactions on geoscience and remote sensing, vol 56 n° 1 (January 2018)
PermalinkOn the topographic bias and density distribution in modelling the geoid and orthometric heights / Lars E. Sjöberg in Journal of geodetic science, vol 8 n° 1 (January 2018)
PermalinkPermalinkOptimisation discrète et indices de stabilité appliqués à la stéréoscopie en contexte routier / Mathias Paget (2018)
PermalinkPermalinkOptimisation de formes en sciences de l'ingénieur : Méthodes et applications, ch. 5. Optimisation de fonction pseudo-booléennes / Laurent Caraffa (2018)
PermalinkParameter estimation with GNSS-reflectometry and GNSS synthetic aperture techniques / Miguel Angel Ribot Sanfelix (2018)
PermalinkPermalinkA posteriori bias correction of three models used for environmental reporting / Bogdan M. Strimbu in Forestry, an international journal of forest research, vol 91 n° 1 (January 2018)
PermalinkPermalinkPermalinkQGIS in Remote Sensing, Volume 2. QGIS and applications in agriculture and forest / Nicolas Baghdadi (2018)
PermalinkPermalinkQuelles recherches pour et avec l'Inventaire Forestier National ? [diaporama] / François Houllier (2018)
PermalinkPermalinkRéférencement spatial indirect : modélisation à base de relations et d'objets spatiaux vagues / Mattia Bunel (2018)
PermalinkRéseaux de neurones convolutionnels profonds pour la détection de petits véhicules en imagerie aérienne / Jean Ogier du Terrail (2018)
PermalinkPermalinkS’approprier un nouveau territoire par l’usage de l’information géographique en DREAL : Changement d’échelle et changement de pratiques / Cécile Cot in Revue internationale de géomatique, vol 28 n° 1 (janvier - mars 2018)
PermalinkPermalinkSatellite remote sensing of the variability of the continental hydrology cycle in the lower Mekong basin over the last two decades / Binh Pham-Duc (2018)
PermalinkPermalinkSimulation 3D de la constructibilité et utilisations pour l’aménagement [diaporama] / Mickaël Brasebin (2018)
PermalinkSparse signal modeling: Application to image compression, Image error concealment and compressed sensing / Ali Akbari (2018)
PermalinkPermalinkSpatio-temporal grid mining applied to image classification and cellular automata analysis / Romain Deville (2018)
PermalinkA stixel approach for enhancing semantic image segmentation using prior map information / Sylvain Jonchery (2018)
PermalinkSuivi des cultures dans le périmètre du Loukkos-Maroc : Apport de la télédétection radar et optique / Siham Acharki (2018)
PermalinkSuivi écologique des prairies semi-naturelles : analyse statistique de séries temporelles denses d’images satellite à haute résolution spatiale / Maylis Lopes (2018)
PermalinkSuperpixel partitioning of very high resolution satellite images for large-scale classification perspectives with deep convolutional neural networks / Tristan Postadjian (2018)
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