Descripteur
Documents disponibles dans cette catégorie (4545)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
The story of DB4GeO – A service-based geo-database architecture to support multi-dimensional data analysis and visualization / Martin Breunig in ISPRS Journal of photogrammetry and remote sensing, vol 117 (July 2016)
[article]
Titre : The story of DB4GeO – A service-based geo-database architecture to support multi-dimensional data analysis and visualization Type de document : Article/Communication Auteurs : Martin Breunig, Auteur ; Paul Vincent Kuper, Auteur ; Edgar Butwilowski, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 187 – 205 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] architecture orientée services
[Termes IGN] données 4D
[Termes IGN] données localisées 3D
[Termes IGN] données multidimensionnelles
[Termes IGN] données spatiotemporelles
[Termes IGN] exploration de données
[Termes IGN] géodatabase
[Termes IGN] géovisualisation
[Termes IGN] modèle conceptuel de données localisées
[Termes IGN] service web géographiqueRésumé : (auteur) Multi-dimensional data analysis and visualization need efficient data handling to archive original data, to reproduce results on large data sets, and to retrieve space and time partitions just in time. This article tells the story of more than twenty years research resulting in the development of DB4GeO, a web service-based geo-database architecture for geo-objects to support the data handling of 3D/4D geo-applications. Starting from the roots and lessons learned, the concepts and implementation of DB4GeO are described in detail. Furthermore, experiences and extensions to DB4GeO are presented. Finally, conclusions and an outlook on further research also considering 3D/4D geo-applications for DB4GeO in the context of Dubai 2020 are given. Numéro de notice : A2016-585 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.12.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.12.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81726
in ISPRS Journal of photogrammetry and remote sensing > vol 117 (July 2016) . - pp 187 – 205[article]Spectral band selection for urban material classification using hyperspectral libraries / Arnaud Le Bris in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol III-7 (July 2016)
[article]
Titre : Spectral band selection for urban material classification using hyperspectral libraries Type de document : Article/Communication Auteurs : Arnaud Le Bris , Auteur ; Nesrine Chehata , Auteur ; Xavier Briottet , Auteur ; Nicolas Paparoditis , Auteur Année de publication : 2016 Article en page(s) : pp 33 - 40 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] bande spectrale
[Termes IGN] base de données d'images
[Termes IGN] capteur superspectral
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] image aérienne
[Termes IGN] image hyperspectrale
[Termes IGN] milieu urbain
[Termes IGN] optimisation (mathématiques)
[Termes IGN] rayonnement infrarouge
[Termes IGN] signature spectraleRésumé : (auteur) In urban areas, information concerning very high resolution land cover and especially material maps are necessary for several city modelling or monitoring applications. That is to say, knowledge concerning the roofing materials or the different kinds of ground areas is required. Airborne remote sensing techniques appear to be convenient for providing such information at a large scale. However, results obtained using most traditional processing methods based on usual red-green-blue-near infrared multispectral images remain limited for such applications. A possible way to improve classification results is to enhance the imagery spectral resolution using superspectral or hyperspectral sensors. In this study, it is intended to design a superspectral sensor dedicated to urban materials classification and this work particularly focused on the selection of the optimal spectral band subsets for such sensor. First, reflectance spectral signatures of urban materials were collected from 7 spectral libraires. Then, spectral optimization was performed using this data set. The band selection workflow included two steps, optimising first the number of spectral bands using an incremental method and then examining several possible optimised band subsets using a stochastic algorithm. The same wrapper relevance criterion relying on a confidence measure of Random Forests classifier was used at both steps. To cope with the limited number of available spectra for several classes, additional synthetic spectra were generated from the collection of reference spectra: intra-class variability was simulated by multiplying reference spectra by a random coefficient. At the end, selected band subsets were evaluated considering the classification quality reached using a rbf svm classifier. It was confirmed that a limited band subset was sufficient to classify common urban materials. The important contribution of bands from the Short Wave Infra-Red (SWIR) spectral domain (1000–2400 nm) to material classification was also shown. Numéro de notice : A2016-825 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-III-7-33-2016 Date de publication en ligne : 07/06/2016 En ligne : http://dx.doi.org/10.5194/isprs-annals-III-7-33-2016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82695
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol III-7 (July 2016) . - pp 33 - 40[article]Fusion of hyperspectral and VHR multispectral image classifications in urban α–areas / Alexandre Hervieu in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol III-3 (July 2016)
[article]
Titre : Fusion of hyperspectral and VHR multispectral image classifications in urban α–areas Type de document : Article/Communication Auteurs : Alexandre Hervieu , Auteur ; Arnaud Le Bris , Auteur ; Clément Mallet , Auteur Année de publication : 2016 Projets : HYEP / Weber, Christiane Article en page(s) : pp 457 - 464 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] fusion d'images
[Termes IGN] image hyperspectrale
[Termes IGN] image multibande
[Termes IGN] méthode de réduction d'énergie
[Termes IGN] occupation du sol
[Termes IGN] optimisation (mathématiques)
[Termes IGN] zone urbaineRésumé : (auteur) An energetical approach is proposed for classification decision fusion in urban areas using multispectral and hyperspectral imagery at distinct spatial resolutions. Hyperspectral data provides a great ability to discriminate land-cover classes while multispectral data,usually at higher spatial resolution, makes possible a more accurate spatial delineation of the classes. Hence, the aim here is to achieve the most accurate classification maps by taking advantage of both data sources at the decision level: spectral properties of the hyperspectral data and the geometrical resolution of multispectral images. More specifically, the proposed method takes into account probability class membership maps in order to improve the classification fusion process. Such probability maps are available using standard classification techniques such as Random Forests or Support Vector Machines. Classification probability maps are integrated into an energy framework where minimization of a given energy leads to better classification maps. The energy is minimized using a graph-cut method called quadratic pseudo-boolean optimization (QPBO) with α-expansion. A first model is proposed that gives satisfactory results in terms of classification results and visual interpretation. This model is compared to a standard Potts models adapted to the considered problem. Finally, the model is enhanced by integrating the spatial contrast observed in the data source of higher spatial resolution (i.e., the multispectral image). Obtained results using the proposed energetical decision fusion process are shown on two urban multispectral/hyperspectral datasets. 2-3% improvement is noticed with respect to a Potts formulation and 3-8% compared to a single hyperspectral-based classification. Numéro de notice : A2016-826 Affiliation des auteurs : LASTIG MATIS (2012-2019) Autre URL associée : vers HAL Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-III-3-457-2016 Date de publication en ligne : 06/06/2016 En ligne : http://dx.doi.org/10.5194/isprs-annals-III-3-457-2016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82697
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol III-3 (July 2016) . - pp 457 - 464[article]Documents numériques
en open access
Fusion of hyperspectral and VHR ... - pdf éditeurAdobe Acrobat PDF An assessment of algorithmic parameters affecting image classification accuracy by random forests / Dee Shi in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 6 (June 2016)
[article]
Titre : An assessment of algorithmic parameters affecting image classification accuracy by random forests Type de document : Article/Communication Auteurs : Dee Shi, Auteur ; Xiaojun Yang, Auteur Année de publication : 2016 Article en page(s) : pp 407 - 417 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme d'apprentissage
[Termes IGN] classification
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] impact sur les données
[Termes IGN] occupation du sol
[Termes IGN] précision de la classificationRésumé : (Auteur) Random forests as a promising ensemble learning algorithm have been increasingly used for remote sensor image classification, and are found to perform identical or better than some popular classifiers. With only two algorithmic parameters, they are relatively easier to implement. Existing literature suggests that the performance of random forests is insensitive to changing algorithmic parameters. However, this was largely based on the classifier's accuracy that does not necessarily represent the resulting thematic map accuracy. The current study extends beyond the classifier's accuracy assessment and investigate how the algorithmic parameters could affect the resulting thematic map accuracy by random forests. A set of random forest models with different parameter settings was carefully constructed and then used to classify a satellite image into multiple land cover categories. Both the classifier's accuracy and the map accuracy were assessed. The results reveal that these parameters can affect the map accuracy up to 9 ∼16 percent for some classes, although their impact on the classifier's accuracy was quite limited. A careful parameterization prioritizing thematic map accuracy can help improve the performance of random forests in image classification, especially for spectrally complex land cover classes. These findings can help establish practical guidance on the use of random forests in the remote sensing community. Numéro de notice : A2016-440 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.82.6.407 En ligne : http://dx.doi.org/10.14358/PERS.82.6.407 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81345
in Photogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 6 (June 2016) . - pp 407 - 417[article]An evaluation of unsupervised and supervised learning algorithms for clustering landscape types in the United States / Jochen Wendel in Cartography and Geographic Information Science, Vol 43 n° 3 (June 2016)
[article]
Titre : An evaluation of unsupervised and supervised learning algorithms for clustering landscape types in the United States Type de document : Article/Communication Auteurs : Jochen Wendel, Auteur ; Barbara P. Buttenfield, Auteur ; Lauwrence V. Stanislawski, Auteur Année de publication : 2016 Article en page(s) : pp 233 - 249 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] classification dirigée
[Termes IGN] classification non dirigée
[Termes IGN] données hydrographiques
[Termes IGN] Etats-Unis
[Termes IGN] généralisation cartographique automatisée
[Termes IGN] intégration de données
[Termes IGN] système d'information géographiqueRésumé : (Auteur) Knowledge of landscape type can inform cartographic generalization of hydrographic features, because landscape characteristics provide an important geographic context that affects variation in channel geometry, flow pattern, and network configuration. Landscape types are characterized by expansive spatial gradients, lacking abrupt changes between adjacent classes; and as having a limited number of outliers that might confound classification. The US Geological Survey (USGS) is exploring methods to automate generalization of features in the National Hydrography Data set (NHD), to associate specific sequences of processing operations and parameters with specific landscape characteristics, thus obviating manual selection of a unique processing strategy for every NHD watershed unit. A chronology of methods to delineate physiographic regions for the United States is described, including a recent maximum likelihood classification based on seven input variables. This research compares unsupervised and supervised algorithms applied to these seven input variables, to evaluate and possibly refine the recent classification. Evaluation metrics for unsupervised methods include the Davies–Bouldin index, the Silhouette index, and the Dunn index as well as quantization and topographic error metrics. Cross validation and misclassification rate analysis are used to evaluate supervised classification methods. The paper reports the comparative analysis and its impact on the selection of landscape regions. The compared solutions show problems in areas of high landscape diversity. There is some indication that additional input variables, additional classes, or more sophisticated methods can refine the existing classification. Numéro de notice : A2016-166 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/15230406.2015.1067829 En ligne : https://doi.org/10.1080/15230406.2015.1067829 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80472
in Cartography and Geographic Information Science > Vol 43 n° 3 (June 2016) . - pp 233 - 249[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 032-2016031 RAB Revue Centre de documentation En réserve L003 Disponible Conception de modèles 3D précis pour un suivi 4D optimisé des ouvrages hydrauliques linéaires : intérêt et particularité du drone / Vincent Tournadre in La Houille Blanche, revue internationale de l'eau, vol 2016 n° 3 (juin 2016)PermalinkContext-dependent detection of non-linearly distributed points for vegetation classification in airborne LiDAR / Denis Horvat in ISPRS Journal of photogrammetry and remote sensing, vol 116 (June 2016)PermalinkEnriching and improving the quality of linked data with GIS / Adam Iwaniak in Open geosciences, vol 8 n° 1 (January - July 2016)PermalinkA geolinguistic approach for comprehending local influence in OpenStreetMap / Sterling Quinn in Cartographica, vol 51 n° 2 (Summer 2016)PermalinkGeometric accuracy of topographical objects at Polish topographic maps / Radzym Lawniczack in Geodesy and cartography, vol 65 n° 1 (June 2016)PermalinkImproving sensor fusion : a parametric method for the geometric coalignment of airborne hyperspectral and lidar data / Maximilian Brell in IEEE Transactions on geoscience and remote sensing, vol 54 n° 6 (June 2016)PermalinkA manifold alignment approach for hyperspectral image visualization with natural color / Danping Liao in IEEE Transactions on geoscience and remote sensing, vol 54 n° 6 (June 2016)PermalinkModel application for rapid detection of the exact location when calling an ambulance using OGC Open GeoSMS Standards / Enes Sukic in Open geosciences, vol 8 n° 1 (January - July 2016)PermalinkOpen help / Paul Stewart in GEO: Geoconnexion international, vol 15 n° 6 (June 2016)PermalinkOptical remotely sensed time series data for land cover classification: A review / Cristina Gómez in ISPRS Journal of photogrammetry and remote sensing, vol 116 (June 2016)PermalinkQualitative spatial logics for buffered geometries / Heshan Du in Journal of Artificial Intelligence Research, vol 56 (May - August 2016)PermalinkThe current state of the creation and modernization of national geodetic and cartographic resources in Poland / Adam Doskocz in Open geosciences, vol 8 n° 1 (January - July 2016)PermalinkVector attribute profiles for hyperspectral image classification / Erchan Aptoula in IEEE Transactions on geoscience and remote sensing, vol 54 n° 6 (June 2016)PermalinkATLAS: A three-layered approach to facade parsing / Markus Mathias in International journal of computer vision, vol 118 n° 1 (May 2016)PermalinkDeep filter banks for texture recognition, description, and segmentation / Mircea Cimpoi in International journal of computer vision, vol 118 n° 1 (May 2016)PermalinkDeveloping the information infrastructure based on LADM – the case of Poland / K. J. Góźdź in Survey review, vol 48 n° 348 (May 2016)PermalinkGenerative models for road network reconstruction / Colin Kuntzsch in International journal of geographical information science IJGIS, vol 30 n° 5-6 (May - June 2016)PermalinkHybrid terrain rendering based on the external edge primitive / E.G. Paredes in International journal of geographical information science IJGIS, vol 30 n° 5-6 (May - June 2016)PermalinkL’imagerie satellitaire stéréoscopique très haute résolution spatiale Pléiades : apport pour les problématiques urbaines / Dominique Hébrard in Signature, n° 60 (mai 2016)PermalinkKinematic interpolation of movement data / Jed A. Long in International journal of geographical information science IJGIS, vol 30 n° 5-6 (May - June 2016)PermalinkLaser ranging plus GNSS / Jyh-Ching Juang in GPS world, vol 27 n° 5 (May 2016)PermalinkA novel automatic structural linear feature-based matching method based on new concepts of mathematically-generated-points and lines / Somayeh Yavari in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 5 (May 2016)PermalinkSpatiotemporal data model for network time geographic analysis in the era of big data / Bi Yu Chen in International journal of geographical information science IJGIS, vol 30 n° 5-6 (May - June 2016)PermalinkChange detection between SAR images using a pointwise approach and graph theory / Minh-Tan Pham in IEEE Transactions on geoscience and remote sensing, vol 54 n° 4 (April 2016)PermalinkFuture trends in geospatial information management : UN expert committee regards connectivity as key to growth / Frédérique Coumans in GIM international [en ligne], vol 30 n° 4 (April 2016)PermalinkGeometric algebra model for geometry-oriented topological relation computation / Zhaoyuan Yu in Transactions in GIS, vol 20 n° 2 (April 2016)PermalinkQuantifying the completeness of and correspondence between two historical maps: a case study from nineteenth-century Palestine / Gad Schaffer in Cartography and Geographic Information Science, Vol 43 n° 2 (April - May 2016)PermalinkAutomatic keyline recognition and 3D reconstruction for quasi-planar façades in close-range images / Chang Li in Photogrammetric record, vol 31 n° 153 (March - May 2016)PermalinkLe collaboratif s'impose / Françoise de Blomac in DécryptaGéo le mag, n° 175 (mars 2016)PermalinkDie Fortführung des 3D-Gebäudemodells LoD2 in Nordrhein-Westfalen / Marco Oestereich in ZFV, Zeitschrift für Geodäsie, Geoinformation und Landmanagement, Vol 141 n° 3 (Mai - Juni 2016)PermalinkLes données géographiques 3D pour simuler l'impact de la réglementation urbaine sur la morphologie du bâti / Mickaël Brasebin in Cartes & Géomatique, n° 227 (mars - mai 2016)PermalinkA GEOBIA framework for the implementation of national and international forest definitions using very high spatial resolution optical satellite data / M. Tompoulidou in Geocarto international, vol 31 n° 3 - 4 (March - April 2016)PermalinkA land use/land cover change geospatial cyberinfrastructure to integrate big data and temporal topology / Jin Xing in International journal of geographical information science IJGIS, vol 30 n° 3-4 (March - April 2016)PermalinkMapping urban growth of the capital city of Honduras from Landsat data using the impervious surface fraction algorithm / Nguyen-Thanh Son in Geocarto international, vol 31 n° 3 - 4 (March - April 2016)PermalinkModelling the spatial evolution of map objects by map agents / Shen Ying in Geocarto international, vol 31 n° 3 - 4 (March - April 2016)PermalinkLa ville à l’échelle de l’Europe : apports du couplage et de l’expertise de bases de données issues de l’imagerie satellitale / Anne Bretagnolle in Revue internationale de géomatique, vol 26 n° 1 (janvier - mars 2016)Permalinkµ-shapes: Delineating urban neighborhoods using volunteered geographic information / Matt Aadland in Journal of Spatial Information Science (JoSIS), n° 12 (March 2016)PermalinkAutomatic geolocation correction of satellite imagery / Ozge C. Ozcanli in International journal of computer vision, vol 116 n° 3 (February 2016)PermalinkFeature-driven generalization of isobaths on nautical charts: A multi-agent system approach / Eric Guilbert in Transactions in GIS, vol 20 n° 1 (February 2016)PermalinkGeo-localization using volumetric representations of overhead imagery / Ozge C. Ozcanli in International journal of computer vision, vol 116 n° 3 (February 2016)PermalinkIdentification and utilization of land-use type importance for land-use data generalization / Wenxiu Gao in Cartographic journal (the), Vol 53 n° 1 (February 2016)PermalinkReconstructing a church in 3D / Matthias Naumann in GIM international [en ligne], vol 30 n° 2 (February 2016)PermalinkA region-line primitive association framework for object-based remote sensing image analysis / Wang Min in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 2 (February 2016)PermalinkPermalinkAcquisition et reconstruction de données 3D denses sous-marines en eau peu profonde par des robots d'exploration / Loïca Avanthey (2016)PermalinkPermalinkPermalinkAssessing the variation of visual complexity in multi-scale maps with clutter measures / Marion Dumont (2016)PermalinkPermalinkAutomatisation de la généralisation cartographique : Relations et interactions, orchestration et approches multi-agents / Cécile Duchêne (2016)PermalinkBIM and cultural heritage: compatibility tests in an archaeological site / Nora Lombardini ; Cinzia Tommasi in International journal of 3-D information modeling, vol 5 n° 1 (January - March 2016)PermalinkBuilding information model for existing buildings for facilities management: retroBIM framework / Giulia Carbonari in International journal of 3-D information modeling, vol 5 n° 1 (January - March 2016)PermalinkCartographie à grande échelle des habitats de la faune sauvage et évaluation / Alexia Dublanche (2016)PermalinkChanges in thermal infrared spectra of plants caused by temperature and water stress / Maria F. Buitrago in ISPRS Journal of photogrammetry and remote sensing, vol 111 (January 2016)PermalinkPermalinkA computational introduction to digital image processing / Alasdair McAndrew (2016)PermalinkConception et implémentation d'un modèle de style adapté à une application web 3D / Anouk Vinesse (2016)PermalinkContribution au développement d'un outil destiné à la diffusion et l'analyse de données spatiales sur les grandes rivières d'Europe / Bruno Giusti (2016)PermalinkPermalinkEmpirical determination of geometric parameters for selective omission in a road network / Qi Zhou in International journal of geographical information science IJGIS, vol 30 n° 1-2 (January - February 2016)PermalinkEuropean handbook of crowdsourced geographic information, ch. 14. Querying VGI by semantic enrichment / Robert Lemmens (2016)PermalinkEuropean handbook of crowdsourced geographic information, ch. 8. Quality analysis of the Parisian OSM toponyms evolution / Vyron Antoniou (2016)PermalinkPermalinkUN-GGIM: Europe Core Data to complement the INSPIRE framework [diaporama] / Dominique Laurent (2016)PermalinkIndoor navigation of mobile robots based on visual memory and image-based visual servoing / Suman Raj Bista (2016)PermalinkInverse procedural Street Modelling: from interactive to automatic reconstruction / Rémi Cura (2016)PermalinkJean-François Renard, Mohamed Ben Zekri, responsables géomatique chez Suez Environnement / Anonyme in Géomatique expert, n° 108 (janvier - février 2016)PermalinkLand Surface Remote Sensing in Urban and Coastal Areas, 1. Optical remote sensing in urban environments / Xavier Briottet (2016)PermalinkLocalisation d’entités nommées historiques par analyse multi-critères et prise en compte des imprécisions / Sébastien Nogueira (2016)PermalinkMeasurement of the annual biomass increment of the French forests, XYLODENSMAP project [diaporama] / Jean-Michel Leban (2016)PermalinkMéthode pour la reconstruction, l'analyse et l'exploitation de réseaux tridimensionnels en milieu urbain / Marie Lacroix (2016)PermalinkModélisation des bases de données d’observation et conception de l’observatoire virtuel pour la gestion de l’interopérabilité / Romain Martin (2016)PermalinkA multiscale masking method for point geographic data / K.C. Clarke in International journal of geographical information science IJGIS, vol 30 n° 1-2 (January - February 2016)PermalinkObject-oriented semantic labelling of spectral–spatial LiDAR point cloud for urban land cover classification and buildings detection / Anandakumar M. Ramiya in Geocarto international, vol 31 n° 1 - 2 (January - February 2016)PermalinkPermalinkParallélisation des processus de traitement des données spatiales / Justin Berli (2016)PermalinkPassive microwave remote sensing of soil moisture based on dynamic vegetation scattering properties for AMSR-E / Jinyang Du in IEEE Transactions on geoscience and remote sensing, vol 54 n° 1 (January 2016)PermalinkPermalinkPrise en compte des mises à jour d’un référentiel dans une base métier : cas des réseaux linaires / Silvio Rousic in Signature, n° 59 (janvier 2016)PermalinkPermalinkRemote Sensing Observations of Continental Surfaces, ch. 6. Airborne lidar data processing / Clément Mallet (2016)PermalinkRevisiting cartography : towards identifying and developing a modern and comprehensive framework / Melih Basaraner in Geocarto international, vol 31 n° 1 - 2 (January - February 2016)PermalinkPermalinkSpatio-temporal traffic video data archiving and retrieval system / Hang Yue in Geoinformatica, vol 20 n° 1 (January - March 2016)PermalinkPermalinkPermalinkPermalinkPermalinkA “very large scale core street map” to prevent damages on underground pipelines during pipe-works [diaporama] / Pascal Lory (2016)PermalinkAn approach to fine coregistration between very high resolution multispectral images based on registration noise distribution / Youkyung Han in IEEE Transactions on geoscience and remote sensing, vol 53 n° 12 (December 2015)PermalinkAn exploration of future patterns of the contributions to OpenStreetMap and development of a contribution index / Jamal Jokar Arsanjani in Transactions in GIS, vol 19 n° 6 (December 2015)PermalinkA back-propagation neural network-based approach for multi-represented feature matching in update propagation / Yanxia Wang in Transactions in GIS, vol 19 n° 6 (December 2015)PermalinkUn cadre formel pour la généralisation multi-échelle de l'occupation du sol au sein de ScaleMaster 2.0 / Jean-François Girres in Cartes & Géomatique, n° 226 (décembre 2015)PermalinkLa carte numérique du Congo, ou comment l'envie de camper le week-end nous a conduits à publier la première carte numérique du pays / Séverine Fabre in XYZ, n° 145 (décembre 2015 - février 2016)PermalinkConceptualising the geographic world: the dimensions of negotiation in crowdsourced cartography / Andrea Ballatore in International journal of geographical information science IJGIS, vol 29 n° 12 (December 2015)Permalink