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Sensitivity of urban material classification to spatial and spectral configurations from visible to short-wave infrared / Arnaud Le Bris (2019)
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Titre : Sensitivity of urban material classification to spatial and spectral configurations from visible to short-wave infrared Type de document : Article/Communication Auteurs : Arnaud Le Bris , Auteur ; Nesrine Chehata
, Auteur
Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2019 Projets : HYEP / Weber, Christiane Conférence : JURSE 2019, Joint Urban Remote Sensing Event 22/05/2019 24/05/2019 Vannes France Proceedings IEEE Importance : 4 p. Format : 21 x 30 cm Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] analyse de sensibilité
[Termes IGN] image à haute résolution
[Termes IGN] image à très haute résolution
[Termes IGN] image aérienne
[Termes IGN] image hyperspectrale
[Termes IGN] image multibande
[Termes IGN] objet géographique urbain
[Termes IGN] pouvoir de résolution géométrique
[Termes IGN] signature spectraleRésumé : (Auteur) Urban material maps are useful for several city modeling or monitoring applications and can be retrieved from remote sensing data. This study investigates the impact of spectral and spatial sensor configuration on urban material classification results, comparing several configurations corresponding to existing or envisaged airborne or space sensors. Images corresponding to such sensors were simulated out of an airborne hyperspectral acquisition. At the end, the relevance of an enhanced spectral configuration and especially providing bands from the SWIR domain was proven, as well as the need for a fine spatial resolution to retrieve urban objects. However, the (late) fusion of multispectral imagery at 2 m resolution with hyperspectral data at 8 m resolution was also proven to lead to good results. Numéro de notice : C2019-005 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Autre URL associée : vers HAL Thématique : IMAGERIE/URBANISME Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/JURSE.2019.8809029 Date de publication en ligne : 22/08/2019 En ligne : https://doi.org/10.1109/JURSE.2019.8809029 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92587 Documents numériques
en open access
Sensitivity of urban material classification to spatial and spectral configurations... - pdf auteurAdobe Acrobat PDFThe necessary yet complex evaluation of 3D city models: a semantic approach / Oussama Ennafii (2019)
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Titre : The necessary yet complex evaluation of 3D city models: a semantic approach Type de document : Article/Communication Auteurs : Oussama Ennafii , Auteur ; Clément Mallet
, Auteur ; Arnaud Le Bris
, Auteur ; Florent Lafarge, Auteur
Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2019 Projets : 1-Pas de projet / Weber, Christiane Conférence : JURSE 2019, Joint Urban Remote Sensing Event 22/05/2019 24/05/2019 Vannes France Proceedings IEEE Importance : 4 p. Format : 21 x 30 cm Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] compréhension de l'image
[Termes IGN] détection d'anomalie
[Termes IGN] image à très haute résolution
[Termes IGN] modèle 3D de l'espace urbain
[Termes IGN] précision sémantique
[Termes IGN] taxinomieRésumé : (Auteur) The automatic modeling of urban scenes in 3D from geospatial data has been studied for more than thirty years.However, the output models still have to undergo a tedious task of correction at city scale. In this work, we propose an approach for automatically evaluating the quality of 3D building models.A taxonomy of potential errors is first proposed. Handcrafted features are computed, based on the geometric properties of buildings and, when available, Very High Resolution images and depth data. They are fed into a Random Forest classifier for the prediction of the quality of the models. We tested our framework on three distinct urban areas in France. We can satisfactorily detect, on average 96% of the most frequent errors. Numéro de notice : C2019-001 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/JURSE.2019.8809002 Date de publication en ligne : 22/08/2019 En ligne : https://doi.org/10.1109/JURSE.2019.8809002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92103 Documents numériques
en open access
The necessary yet complex evaluation of 3D city models - pdf auteurAdobe Acrobat PDF
Titre : The ‘urban’ component of the French Land Data and Services Centre (Theia) Type de document : Article/Communication Auteurs : Anne Puissant, Auteur ; Arnaud Sellé, Auteur ; Nicolas Baghdadi, Auteur ; Vincent Thierion, Auteur ; Arnaud Le Bris , Auteur ; Jean-Louis Roujean, Auteur
Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2019 Projets : 2-Pas d'info accessible - article non ouvert / Weber, Christiane Conférence : JURSE 2019, Joint Urban Remote Sensing Event 22/05/2019 24/05/2019 Vannes France Proceedings IEEE Importance : 4 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données
[Termes IGN] image aérienne
[Termes IGN] image spatialeRésumé : (auteur) The THEIA data and services centre has been created with the objective of increasing the use of space data by the scientific community and the public actors. THEIA structured the French scientific community 1) through a mutualized Service and Data Infrastructure (SDI) distributed between several centers, allowing access to a variety of products; 2) through the setup of Regional Animation Networks (RAN) to federate and animate users (scientists and public / private actors) and 3) through Scientific Expertise Centres (SEC) clustering virtual research groups on a thematic domain. The research works carried out for urban studies in three SEC are presented in this paper. The works are organized around the design and development of value-added products and services. Numéro de notice : C2019-003 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/JURSE.2019.8808998 Date de publication en ligne : 22/08/2019 En ligne : https://doi.org/10.1109/JURSE.2019.8808998 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92208 Time-space tradeoff in deep learning models for crop classification on satellite multi-spectral image time series / Vivien Sainte Fare Garnot (2019)
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Titre : Time-space tradeoff in deep learning models for crop classification on satellite multi-spectral image time series Type de document : Article/Communication Auteurs : Vivien Sainte Fare Garnot , Auteur ; Loïc Landrieu
, Auteur ; Sébastien Giordano
, Auteur ; Nesrine Chehata
, Auteur
Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2019 Projets : 1-Pas de projet / Weber, Christiane Conférence : IGARSS 2019, IEEE International Geoscience And Remote Sensing Symposium 28/07/2019 02/08/2019 Yokohama Japon Proceedings IEEE Importance : 4 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage profond
[Termes IGN] classification par réseau neuronal
[Termes IGN] cultures
[Termes IGN] image Sentinel-MSI
[Termes IGN] série temporelleRésumé : (auteur) In this article, we investigate several structured deep learning models for crop type classification on multi-spectral time series. In particular, our aim is to assess the respective importance of spatial and temporal structures in such data. With this objective, we consider several designs of convolutional, recurrent, and hybrid neural networks, and assess their performance on a large dataset of freely available Sentinel-2 imagery. We find that the best-performing approaches are hybrid configurations for which most of the parameters (up to 90%) are allocated to modeling the temporal structure of the data. Our results thus constitute a set of guidelines for the design of bespoke deep learning models for crop type classification. Numéro de notice : C2019-018 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Autre URL associée : URL ArXiv Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/IGARSS.2019.8900517 Date de publication en ligne : 14/11/2019 En ligne : https://doi.org/10.1109/IGARSS.2019.8900517 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93352 Urban morpho-types classification from SPOT-6/7 imagery and Sentinel-2 time series / Arnaud Le Bris (2019)
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Titre : Urban morpho-types classification from SPOT-6/7 imagery and Sentinel-2 time series Type de document : Article/Communication Auteurs : Arnaud Le Bris , Auteur ; Nesrine Chehata
, Auteur
Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2019 Projets : GeoSud / Weber, Christiane Conférence : JURSE 2019, Joint Urban Remote Sensing Event 22/05/2019 24/05/2019 Vannes France Proceedings IEEE Importance : 4 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] image Sentinel-MSI
[Termes IGN] image SPOT 6
[Termes IGN] image SPOT 7
[Termes IGN] morphologie urbaine
[Termes IGN] série temporelle
[Termes IGN] zone urbaineRésumé : (auteur) This paper aims at detecting several urban morpho-type classes out of SPOT-6/7 imagery and Sentinel-2 time series. Urban classes of Urban Atlas are considered. The proposed strategy is a bottom-up one. It first detects basic urban objects (buildings, roads, vegetation), and use them to calculate multi-scale morphological features. These features are then fed to a Random Forest classifier trained from samples out of Urban Atlas urban classes. Obtained results is optionally merged with a Random Forest classification based on Sentinel-2 time series. Obtained results are promising. Numéro de notice : C2019-004 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Autre URL associée : vers HAL Thématique : IMAGERIE/URBANISME Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/JURSE.2019.8808988 Date de publication en ligne : 22/08/2019 En ligne : https://doi.org/10.1109/JURSE.2019.8808988 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92209 Comparative study of visual saliency maps in the problem of classification of architectural images with Deep CNNs / Abraham Montoya Obeso (2018)
PermalinkCrop-rotation structured classification using multi-source sentinel images and LPIS for crop type mapping / Simon Bailly (2018)
PermalinkDecision fusion of SPOT6 and multitemporal Sentinel2 images for urban area detection / Cyril Wendl (2018)
PermalinkDetection and area estimation for photovoltaic panels in urban hyperspectral remote sensing data by an original NMF-based unmixing method / Moussa Sofiane Karoui (2018)
PermalinkDomain adaptation for large scale classification of very high resolution satellite images with deep convolutional neural networks / Tristan Postadjian (2018)
PermalinkPermalinkPermalinkPotential and limits of Sentinel-1 data for small alpine glaciers monitoring / Matthias Jauvin (2018)
PermalinkPermalinkSentinel-2 level-1 calibration and validation status from the mission performance centre / Catherine Bouzinac (2018)
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