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Multiobjective subpixel land-cover mapping / Ailong Ma in IEEE Transactions on geoscience and remote sensing, vol 56 n° 1 (January 2018)
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Titre : Multiobjective subpixel land-cover mapping Type de document : Article/Communication Auteurs : Ailong Ma, Auteur ; Yanfei Zhong, Auteur ; Da He, Auteur ; Liangpei Zhang, Auteur Année de publication : 2018 Article en page(s) : pp 422 - 435 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] carte d'occupation du sol
[Termes IGN] image hyperspectrale
[Termes IGN] optimisation (mathématiques)
[Termes IGN] problème inverseRésumé : (Auteur) The hyperspectral subpixel mapping (SPM) technique can generate a land-cover map at the subpixel scale by modeling the relationship between the abundance map and the spatial distribution image of the subpixels. However, this is an inverse ill-posed problem. The most widely used way to resolve the problem is to introduce additional information as a regularization term and acquire the unique optimal solution. However, the regularization parameter either needs to be determined manually or it cannot be determined in a fully adaptive manner. Thus, in this paper, the multiobjective subpixel land-cover mapping (MOSM) framework for hyperspectral remote sensing imagery is proposed, in which the two function terms [the fidelity term and the prior term (i.e., the regularization term)] can be optimized simultaneously, and there is no need to determine the regularization parameter explicitly. In order to achieve this goal, two strategies are designed in MOSM: 1) a high-resolution distribution image-based individual encoding strategy is designed in order to calculate the prior term accurately and 2) a subfitness-based individual comparison strategy is designed in order to generate subpixel land-cover mapping solutions with a high quality to update the population. Four data sets (one simulated, two synthetic, and one real hyperspectral image) were used to test the proposed method. The experimental results show that MOSM can perform better than the other subpixel land-cover mapping methods, demonstrating the effectiveness of MOSM in balancing the fidelity term and prior term in the SPM model. Numéro de notice : A2018-187 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2748701 Date de publication en ligne : 10/11/2017 En ligne : https://doi.org/10.1109/TGRS.2017.2748701 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89845
in IEEE Transactions on geoscience and remote sensing > vol 56 n° 1 (January 2018) . - pp 422 - 435[article]Satellite remote sensing of the variability of the continental hydrology cycle in the lower Mekong basin over the last two decades / Binh Pham-Duc (2018)
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Titre : Satellite remote sensing of the variability of the continental hydrology cycle in the lower Mekong basin over the last two decades Type de document : Thèse/HDR Auteurs : Binh Pham-Duc, Auteur ; Catherine Prigent, Directeur de thèse ; Filipe Aires, Directeur de thèse Editeur : Paris : Sorbonne Université Année de publication : 2018 Importance : 234 p. Format : 21 x 30 cm Note générale : bibliographie
Thèse de doctorat de Sciences de l'Environnement, Sorbonne UniversitéLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte hydrographique
[Termes IGN] changement climatique
[Termes IGN] classification par réseau neuronal
[Termes IGN] climat tropical
[Termes IGN] corrélation temporelle
[Termes IGN] eau de surface
[Termes IGN] image Aqua-MODIS
[Termes IGN] image Landsat-8
[Termes IGN] image Sentinel-SAR
[Termes IGN] Mekong (fleuve)
[Termes IGN] modèle hydrographique
[Termes IGN] précipitation
[Termes IGN] série temporelle
[Termes IGN] surveillance hydrologique
[Termes IGN] télédétection spatiale
[Termes IGN] variation saisonnièreIndex. décimale : THESE Thèses et HDR Résumé : (auteur) Surface water is essential for all forms of life since it is involved in almost all processes of life on Earth. Quantifying and monitoring surface water and its variations are important because of the strong connections between surface water, other hydrological components (groundwater and soil moisture, for example), and the changing climate system. Satellite remote sensing of land surface hydrology has shown great potential in studying hydrology from space at regional and global scales. In this thesis, different techniques using several types of satellite estimates have been made to study the variation of surface water, as well as other hydrological components in the lower Mekong basin (located in Vietnam and Cambodia) over the last two decades. This thesis focuses on four aspects. First, the use of visible/infrared MODIS/Terra satellite observations to monitor surface water in the lower Mekong basin is investigated. Four different classification methods are applied, and their results of surface water maps show similar seasonality and dynamics. The most suitable classification method, that is specially designed for tropical regions, is chosen to produce regular surface water maps of the region at 500 m spatial resolution, from January 2001 to present time. Compared to reference data, the MODIS-derived surface water time series show the same amplitude, and very high temporal correlation for the 2001-2007 period (> 95%). Second, the use of SAR Sentinel-1 satellite observations for the same objective is studied. Optical satellite data are replaced by SAR satellite data to benefit the ability of their microwave wavelengths to pass through clouds. Free-cloud Landsat-8 satellite imagery are set as targets to train and optimize a Neural Network (NN). Predicted surface water maps (30 m spatial resolution) are built for the studied region from January 2015 to present time, by applying a threshold (0.85) to the output of the NN. Compared to reference free-cloud Landsat-8 surface water maps, results derived from the NN show high spatial correlation (_90%), as well as true positive detection of water pixels (_90%). Predicted SAR surface water maps are also compared to floodability maps derived from topography data, and results show high consistency between the two independent maps with 98% of SAR-derived water pixels located in areas with a high probability of inundation (>60%). Third, the surface water volume variation is calculated as the product of the surface water extent and the surface water height. The two components are validated with other hydrological products, and results show good consistencies. The surface water height are linearly interpolated over inundated areas to build monthly maps at 500 m spatial resolution, then are used to calculate changes in the surface water volume. Results show high correlations when compared to variation of the total land surface water volume derived from GRACE data (95%), and variation of the in situ discharge estimates (96%). Fourth, two monthly global multi-satellite surface water products (GIEMS & SWAMPS) are compared together over the 1993-2007 period at regional and global scales. Ancillary data are used to support the analyses when available. Similar temporal dynamics of global surface water are observed when compared GIEMS and SWAMPS, but _50% of the SWAMPS inundated surfaces are located along the coast line. Over the Amazon and Orinoco basins, GIEMS and SWAMPS have very high water surface time series correlations (95% and 99%, respectively), but SWAMPS maximum water extent is just a half of what observed from GIEMS and SAR estimates. SWAMPS fails to capture surface water dynamics over the Niger basin since its surface water seasonality is out of phase with both GIEMS- and MODIS-derived water extent estimates, as well as with in situ river discharge data. Note de contenu : 1- Introduction
2- Surface water monitoring within the Mekong Delta and Cambodia using visible and Infrared MODIS satellite
observations
3- Surface water monitoring within the Mekong Delta and Cambodia using SAR Sentinel-1 satellite observations
4- Toward the analyses of the change in surface water volume within the lower Mekong Delta
5- Comparison between Global Terrestrial Surface Water datasets
6- Conclusions and perspectivesNuméro de notice : 25731 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Sciences de l'Environnement : Observatoire de Paris : 2018 Organisme de stage : Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique LERMA (Observatoire de Paris) nature-HAL : Thèse DOI : sans En ligne : https://tel.archives-ouvertes.fr/tel-02109003 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94914 Superpixel partitioning of very high resolution satellite images for large-scale classification perspectives with deep convolutional neural networks / Tristan Postadjian (2018)
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Titre : Superpixel partitioning of very high resolution satellite images for large-scale classification perspectives with deep convolutional neural networks Type de document : Article/Communication Auteurs : Tristan Postadjian , Auteur ; Arnaud Le Bris
, Auteur ; Hichem Sahbi, Auteur ; Clément Mallet
, Auteur
Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2018 Projets : GeoSud / Conférence : IGARSS 2018, IEEE International Geoscience And Remote Sensing Symposium, observing, understanding and forecasting the dynamics of our planet 22/07/2018 27/07/2018 Valencia Espagne Proceedings IEEE Importance : pp 1328 - 1331 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage profond
[Termes IGN] base de données topographiques
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification pixellaire
[Termes IGN] image à très haute résolution
[Termes IGN] image infrarouge
[Termes IGN] image RVB
[Termes IGN] image SPOT 6
[Termes IGN] image SPOT 7
[Termes IGN] réseau neuronal convolutif
[Termes IGN] segmentation d'imageRésumé : (auteur) Supervised classification is the fundamental task for landcover map generation. Deep neural networks recently outperformed other state-of-the-art classifiers in many machine learning challenges, from semantic segmentation to speech recognition. Such strategies are now commonly employed in the literature for the purpose of land-cover mapping. This paper develops the strategy for the use of deep networks to label very high resolution satellite images, with the perspective of mapping regions at country scale. Therefore, a superpixel based method is introduced in order to (i) ensure correct delineation of objects and (ii) perform the classification in a dense way but with decent computing times. Numéro de notice : C2018-056 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/IGARSS.2018.8519222 Date de publication en ligne : 05/11/2018 En ligne : https://doi.org/10.1109/IGARSS.2018.8519222 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91370 Synergie des données Sentinel optiques et radar pour l’observation et l’analyse de la végétation du littoral du Pays de Brest / Antoine Billey (2018)
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Titre : Synergie des données Sentinel optiques et radar pour l’observation et l’analyse de la végétation du littoral du Pays de Brest Type de document : Mémoire Auteurs : Antoine Billey, Auteur Editeur : Le Mans : Ecole Supérieure des Géomètres et Topographes ESGT Année de publication : 2018 Importance : 62 p. Format : 21 x 30 cm Note générale : bibliographie
Mémoire présenté en vue d'obtenir le diplôme d'Ingénieur CNAM spécialité : Géomètre et TopographeLangues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Brest
[Termes IGN] carte d'occupation du sol
[Termes IGN] carte de la végétation
[Termes IGN] classification dirigée
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] fusion de données
[Termes IGN] image multicapteur
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] image SPOT 6
[Termes IGN] littoral
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] Normalized Difference Water Index
[Termes IGN] série temporelle
[Termes IGN] surveillance de la végétation
[Termes IGN] télédétection spatiale
[Termes IGN] traitement de donnéesRésumé : (auteur) Cartographier la végétation d’un territoire est nécessaire pour le suivi et la gestion des espaces naturels. La cartographie de la végétation intéresse notamment les gestionnaires et les décideurs dans la gestion de territoire et l’aménagement du territoire. Le pays de Brest est un territoire possédant un patrimoine naturel riche et diversifié, lié au climat littoral qui subsiste. De nombreuses méthodes d’élaboration de cartes d’occupations des sols existent, et la télédétection spatiale représente un moyen efficace pour y parvenir.L’objectif de cette étude est de mettre au point une méthode de cartographie pour effectuer le suivi de la végétation du littoral du Pays de Brest à partir des nouvelles données satellites européennes. Note de contenu : Introduction
1- Contexte de l’étude
2- Méthodologie
3- Résultats et discussions
ConclusionNuméro de notice : 25724 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Mémoire ingénieur CNAM En ligne : https://dumas.ccsd.cnrs.fr/MEMOIRES-CNAM/dumas-02092722 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94879
Titre : The Use of remote sensing in hydrology Type de document : Monographie Auteurs : Frédéric Frappart, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2018 Importance : 258 p. Format : 17 x 25 cm ISBN/ISSN/EAN : 978-3-03842-910-4 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] capteur spatial
[Termes IGN] carte hydrographique
[Termes IGN] évapotranspiration
[Termes IGN] humidité du sol
[Termes IGN] hydrodynamique
[Termes IGN] hydrologie
[Termes IGN] image Cryosat
[Termes IGN] image Sentinel-SAR
[Termes IGN] inondation
[Termes IGN] modèle hydrographique
[Termes IGN] précipitation
[Termes IGN] stockage
[Termes IGN] surveillance hydrologiqueRésumé : (éditeur) Remotely sensed data are nowadays commonly used for regional/global monitoring of hydrological variables including soil moisture, rainfall, water levels, flood extent, evapotranspiration or land water storage, as well as the forcing, calibration and assimilation into hydrodynamic, hydrological and hydrometeorological models. In the years to come, recent and future satellite sensors, some of them specifically designed for hydrological purposes, will provide systematic observations of hydrological parameters (e.g., surface and sub-surface storage and flux) at high spatial and temporal resolutions. This will offer new applications for the hydrological community. This book presents reviews and recent advances of general interest regarding the use of remote sensing for hydrology. The chapters are related to any hydrological reservoir (e.g., surface storage, soil moisture, groundwater, etc.) or flux (e.g., rainfall, evapotranspiration, discharge, etc.), the integration of satellite data into hydrological models, and the improvements to hydrology that can be expected from future satellite missions. Numéro de notice : 25962 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Monographie DOI : 10.3390/books978-3-03842-910-4 En ligne : https://doi.org/10.3390/books978-3-03842-910-4 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96538 Les usages des systèmes d’informations géographiques en matière de gestion de mobilité en milieu urbain : la mise en accessibilité aux personnes à mobilité réduite des arrêts de bus en Seine-Seine-Denis / Thi-Lieu Gremont-Dong (2018)
PermalinkUtilisation de QGIS en télédétection, ch. 6. Cartographie de la végétation à partir d'images radar Sentinel-1 / Pierre-Louis Frison (2018)
PermalinkEstimation and mapping of above-ground biomass of mangrove forests and their replacement land uses in the Philippines using Sentinel imagery / Jose Alan A. Castillo in ISPRS Journal of photogrammetry and remote sensing, vol 134 (December 2017)
PermalinkVol 44 n° 6 - November 2017 - Special content sections: Crowdsourced mapping - continued (Bulletin de Cartography and Geographic Information Science)
PermalinkAn empirical evaluation of three elevation change symbolization methods along routes in bicycle maps / Annina Brügger in Cartography and Geographic Information Science, Vol 44 n° 5 (September 2017)
PermalinkBinSq : visualizing geographic dot density patterns with gridded maps / Alvin Chua in Cartography and Geographic Information Science, Vol 44 n° 5 (September 2017)
PermalinkLa combinaison de l'image satellitaire avec les données citoyennes pour la mesure de l'ïlot de chaleur urbain : Premiers résultats sur la métropole de Lyon / Florent Renard in Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI, vol 22 n° 5 (septembre - octobre 2017)
PermalinkCrowdsourcing a cyclist perspective on suggested recreational paths in real-world networks / Kevin Baker in Cartography and Geographic Information Science, Vol 44 n° 5 (September 2017)
PermalinkEvaluation de variables limnologiques grâce à des images Landsat / Danielle Teixeira Alves Da Silva in Géomatique expert, n° 118 (septembre - octobre 2017)
PermalinkA mangrove forest map of China in 2015: Analysis of time series Landsat 7/8 and Sentinel-1A imagery in Google Earth Engine cloud computing platform / Bangqian Chen in ISPRS Journal of photogrammetry and remote sensing, vol 131 (September 2017)
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