Descripteur
Termes IGN > informatique > génie logiciel > programmation informatique
programmation informatiqueSynonyme(s)développement informatique |
Documents disponibles dans cette catégorie (722)
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
Gen*: a generic toolkit to generate spatially explicit synthetic populations / Kevin Chapuis in International journal of geographical information science IJGIS, vol 32 n° 5-6 (May - June 2018)
[article]
Titre : Gen*: a generic toolkit to generate spatially explicit synthetic populations Type de document : Article/Communication Auteurs : Kevin Chapuis, Auteur ; Patrick Taillandier , Auteur ; Misslin Renaud, Auteur ; Alexis Drogoul, Auteur Année de publication : 2018 Article en page(s) : pp 1194 - 1210 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] distribution spatiale
[Termes IGN] figuration de la densité
[Termes IGN] modèle orienté agent
[Termes IGN] population urbaine
[Termes IGN] programmation par contraintes
[Termes IGN] recensement démographique
[Termes IGN] régression
[Termes IGN] Rouen
[Termes IGN] système d'information géographiqueRésumé : (Auteur) Agent-based models tend to integrate more and more data that can deeply impact their outcomes. Among these data, the ones that deal with agent attributes and localization are particularly important, but are very difficult to collect. In order to tackle this issue, we propose a complete generic toolkit called Gen* dedicated to generating spatially explicit synthetic populations from global (census and GIS) data. This article focuses on the localization methods provided by Gen* that are based on regression, geometrical constraints and spatial distributions. The toolkit is applied for a case study concerning the generation of the population of Rouen (France) and shows the capabilities of Gen* regarding population spatialization. Numéro de notice : A2018-204 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1440563 Date de publication en ligne : 26/02/2018 En ligne : https://doi.org/10.1080/13658816.2018.1440563 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89875
in International journal of geographical information science IJGIS > vol 32 n° 5-6 (May - June 2018) . - pp 1194 - 1210[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 079-2018031 RAB Revue Centre de documentation En réserve L003 Disponible Traitement d’image en Python avec RSGISLib / Anonyme in Géomatique expert, n° 121 (mars - avril 2018)
[article]
Titre : Traitement d’image en Python avec RSGISLib Type de document : Article/Communication Auteurs : Anonyme, Auteur Année de publication : 2018 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] bibliothèque logicielle
[Termes IGN] logiciel de traitement d'image
[Termes IGN] Python (langage de programmation)
[Termes IGN] RSGISLibRésumé : (éditeur) Autrefois limités à quelques logiciels commerciaux excessivement onéreux (ENVI …), les outils de traitement d’image se sont progressivement « ouverts » grâce à l’initiative d’universitaires ou de grands groupes désireux de développer la pratique de la télédétection. Numéro de notice : A2018-262 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90319
in Géomatique expert > n° 121 (mars - avril 2018)[article]Exemplaires(2)
Code-barres Cote Support Localisation Section Disponibilité 265-2018021 RAB Revue Centre de documentation En réserve L003 Disponible IFN-001-P002038 PER Revue Nogent-sur-Vernisson Salle périodiques Exclu du prêt An open source framework for publishing flood inundation extent libraries in a Web GIS environment using open source technologies / Vinod Kumar Sharma in International journal of cartography, vol 4 n° 1 (March 2018)
[article]
Titre : An open source framework for publishing flood inundation extent libraries in a Web GIS environment using open source technologies Type de document : Article/Communication Auteurs : Vinod Kumar Sharma, Auteur ; Nitin Mishra, Auteur ; C.M. Bhatt, Auteur ; G. Srinivasa Rao, Auteur ; V. Bhanumurthy, Auteur Année de publication : 2018 Article en page(s) : pp 65 - 77 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] base de données localisées
[Termes IGN] bibliothèque logicielle
[Termes IGN] cadre conceptuel
[Termes IGN] cartographie des risques
[Termes IGN] Inde
[Termes IGN] inondation
[Termes IGN] risque naturel
[Termes IGN] visualisation de données
[Termes IGN] WebSIGRésumé : (auteur) The concept of static flood inundation extent libraries and their utilisation to anticipate the extent of inundation to alert and evacuate the population likely to get affected has been suggested by many researchers in different prototype studies. Actual implementation of the concept for a nation like India demands an automated practical operational software framework for systematic organisation, retrieval and visualisation of flood inundation extent libraries in a Geographic Information System (GIS) environment. Implementation of a software framework in a Web GIS environment facilitates decision-makers to access the inundation library with a functionality to overlay other spatial layers for proper situation assessment and decision-making. Utilisation of an open source software library for developing the software framework reduces the overall project cost and its re-distribution. The present work addresses the development of an automated operational framework for one of the chronically flood affected states in India (Bihar) using open source libraries for updating libraries, cataloguing, database organisation, retrieval of data and visualisation of flood extent. The developed framework first reads and arranges the flood forecast information followed by database organisation for identifying the corresponding inundation extent and other related layers available in the library for visualisation. Numéro de notice : A2018-082 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/23729333.2017.1370861 En ligne : https://doi.org/10.1080/23729333.2017.1370861 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89450
in International journal of cartography > vol 4 n° 1 (March 2018) . - pp 65 - 77[article]LRAGE : learning latent relationships with adaptive graph embedding for aerial scene classification / Yuebin Wang in IEEE Transactions on geoscience and remote sensing, vol 56 n° 2 (February 2018)
[article]
Titre : LRAGE : learning latent relationships with adaptive graph embedding for aerial scene classification Type de document : Article/Communication Auteurs : Yuebin Wang, Auteur ; Liqiang Zhang, Auteur ; Xiaohua Tong, Auteur ; Feiping Nie, Auteur ; Haiyang Huang, Auteur ; Jie Mei, Auteur Année de publication : 2018 Article en page(s) : pp 621 - 634 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage automatique
[Termes IGN] classification semi-dirigée
[Termes IGN] graphe
[Termes IGN] image aérienne
[Termes IGN] programmation par contraintes
[Termes IGN] régression linéaire
[Termes IGN] scèneRésumé : (Auteur) The performance of scene classification relies heavily on the spatial and structural features that are extracted from high spatial resolution remote-sensing images. Existing approaches, however, are limited in adequately exploiting latent relationships between scene images. Aiming to decrease the distances between intraclass images and increase the distances between interclass images, we propose a latent relationship learning framework that integrates an adaptive graph with the constraints of the feature space and label propagation for high-resolution aerial image classification. To describe the latent relationships among scene images in the framework, we construct an adaptive graph that is embedded into the constrained joint space for features and labels. To remove redundant information and improve the computational efficiency, subspace learning is introduced to assist in the latent relationship learning. To address out-of-sample data, linear regression is adopted to project the semisupervised classification results onto a linear classifier. Learning efficiency is improved by minimizing the objective function via the linearized alternating direction method with an adaptive penalty. We test our method on three widely used aerial scene image data sets. The experimental results demonstrate the superior performance of our method over the state-of-the-art algorithms in aerial scene image classification. Numéro de notice : A2018-189 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2752217 Date de publication en ligne : 24/10/2017 En ligne : https://doi.org/10.1109/TGRS.2017.2752217 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89854
in IEEE Transactions on geoscience and remote sensing > vol 56 n° 2 (February 2018) . - pp 621 - 634[article]
Titre : Classification of land use from high resolution satellite imagery Type de document : Mémoire Auteurs : Yasser Kotrsi, Auteur ; Arnaud Le Bris , Encadrant ; Nesrine Chehata , Encadrant ; Anne Puissant, Encadrant ; Tristan Postadjian , Encadrant Editeur : Tunis [Tunisie] : Ecole nationale d'ingénieurs de Carthage Année de publication : 2018 Importance : 112 p. Note générale : bibliographie
End Of Studies Project Report, in fulfillment of the requirements for the degree of National engineering diploma in software engineeringLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage profond
[Termes IGN] bibliothèque logicielle
[Termes IGN] classification barycentrique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] Finistère (29)
[Termes IGN] fusion d'images
[Termes IGN] image Sentinel-MSI
[Termes IGN] image SPOT 6
[Termes IGN] milieu urbain
[Termes IGN] occupation du sol
[Termes IGN] OpenCV
[Termes IGN] Python (langage de programmation)
[Termes IGN] semis de pointsRésumé : (auteur) The MATIS team of the LaSTIG Laboratory of the french mapping agency (IGN) has for several years conducted research activities in the field of classification of remote sensing data (aerial or satellite optical images and point clouds 3D lidar) for land use (OCS), in urban and rural areas. With the arrival of the new Sentinel S1 (radar) and S2 (optical) sensors, time series of images are now available free of charge with a high temporal resolution (between 10 and 15 days) and a high spectral resolution for optical images. In addition, the national territory is covered annually by acquisition of SPOT 6-7 images. The CES Artificialisation-urbanization pole Theia aims at the production of a map of land use in urban environment, with a resolution of 10m. Early work based on the fusion of Sentinel 2 time series with very high resolution data (THR) SPOT 6-7, Pleiades led to the detection of artifical spots, as well as well shaped urban objects. It is now a question of better characterizing this urban space by investigating about the relations between those image regions as well as each one’s spatial properties in order to produce a detailed cartography classified into different types of urban fabrics (residential, dense urban, non-dense, industrial, ...). In this study we dive deep through the problematic of the land use classification, its aspects as well the different approaches to characterize the extracted information about it in order to obtain an accurate classification that corresponds well to the expected results. This study therefore focuses on the continuation of previous work and consists in obtaining a detailed cartography in different types of urban fabrics (residential, dense urban, non-dense, industrial, ..). For that, several scientific locks are raised: • Test the data fusion methods previously used for fine mapping of the urban environment. • Develop different multiscale spatial indicators (size of objects, distance between objects, density of objects, presence of vegetation, ...) to describe the city. • Exploit these indicators in order to find different types of neighborhoods and to characterize land use. The calculation of indicators is based in part on SPOT image classifications 6-7 obtained during previous work. Also the Urban Atlas database, which also details urban spaces in urban classes, is used in the learning stage as well as the Corine Land Cover database. Note de contenu : Introduction
1- Project introduction
2- State of the art and background material
3- Available data and study areas
4- Methodology
5- Results and discussions
Conclusion and perspectivesNuméro de notice : 17187 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Mémoire ingénieur Organisme de stage : LaSTIG (IGN) DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98348 Documents numériques
peut être téléchargé
Classification of land use ... - pdf auteurAdobe Acrobat PDF Développement d'un outil de manipulation optimisée de rasters volumineux / Amaury Zarzelli (2018)PermalinkDéveloppement pour l’interface Qgis d’Hydra, logiciel de modélisation hydraulique / Maximilien Jaffrès (2018)PermalinkPermalinkPermalinkPermalinkMachine learning and pose estimation for autonomous robot grasping with collaborative robots / Victor Talbot (2018)PermalinkPermalinkSimulation 3D de la constructibilité et utilisations pour l’aménagement [diaporama] / Mickaël Brasebin (2018)PermalinkPermalinkTesting deformation hypotheses by constraints on a time series of geodetic observations / Hiddo Velsink in Journal of applied geodesy, vol 12 n° 1 (January 2018)Permalink