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Benchmarking of convolutional neural network approaches for vegetation land cover mapping / Benjamin Carpentier (2021)
Titre : Benchmarking of convolutional neural network approaches for vegetation land cover mapping Type de document : Article/Communication Auteurs : Benjamin Carpentier, Auteur ; Antoine Masse , Auteur ; Emeric Lavergne, Auteur ; C. Sannier, Auteur Editeur : International Society for Photogrammetry and Remote Sensing ISPRS Année de publication : 2021 Collection : International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, ISSN 1682-1750 num. 43-B2-2021 Conférence : ISPRS 2021, Commission 2, XXIV ISPRS Congress, Imaging today foreseeing tomorrow 05/07/2021 09/07/2021 Nice Virtuel France OA Archives Commission 2 Importance : pp 915 - 922 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] carte d'occupation du sol
[Termes IGN] carte de la végétation
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] image Sentinel-MSI
[Termes IGN] série temporelleRésumé : (auteur) Satellite Image Time Series (SITS) are becoming available at high spatial, spectral and temporal resolutions across the globe by the latest remote sensing sensors. These series of images can be highly valuable when exploited by classification systems to produce frequently updated and accurate land cover maps. The richness of spectral, spatial and temporal features in SITS is a promising source of data for developing better classification algorithms. However, machine learning methods such as Random Forests (RF), despite their fruitful application to SITS to produce land cover maps, are structurally unable to properly handle intertwined spatial, spectral and temporal dynamics without breaking the structure of the data. Therefore, the present work proposes a comparative study of various deep learning algorithms from the Convolutional Neural Network (CNN) family and evaluate their performance on SITS classification. They are compared to the processing chain coined iota2, developed by the CESBIO and based on a RF model. Experiments are carried out in an operational context using with sparse annotations from 290 labeled polygons. Less than 80 000 pixel time series belonging to 8 land cover classes from a year of Sentinel-2 monthly syntheses are used. Results show on a test set of 131 polygons that CNNs using 3D convolutions in space and time are more accurate than 1D temporal, stacked 2D and RF approaches. Best-performing models are CNNs using spatio-temporal features, namely 3D-CNN, 2D-CNN and SpatioTempCNN, a two-stream model using both 1D and 3D convolutions. Numéro de notice : C2021-017 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Communication DOI : 10.5194/isprs-archives-XLIII-B2-2021-915-2021 Date de publication en ligne : 28/06/2021 En ligne : https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-915-2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98069 Centrality and city size effects on NO2 ground and tropospheric concentrations within European cities / Yufei Wei (2021)
contenu dans European Colloquium on Theoretical and Quantitative Geography 2021, Manchester, 3-5 November 2021 / Nuno Pinto (2021)
Titre : Centrality and city size effects on NO2 ground and tropospheric concentrations within European cities Type de document : Article/Communication Auteurs : Yufei Wei, Auteur ; Geoffrey Caruso, Auteur ; Rémi Lemoy, Auteur Editeur : Manchester [Royaume-Uni] : Manchester University Press Année de publication : 2021 Conférence : ECTQG 2021, 22nd European Colloquium on Theoretical and Quantitative Geography 03/11/2021 05/11/2021 Manchester Royaume-Uni Open Access Abstracts Importance : pp 396 - 400 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] centre urbain
[Termes IGN] dioxyde d'azote
[Termes IGN] Europe (géographie politique)
[Termes IGN] image Sentinel-5P-TROPOMI
[Termes IGN] pollution atmosphérique
[Termes IGN] villeNuméro de notice : C2021-078 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Communication DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100065 Documents numériques
en open access
Centrality and city size effects ... - pdf éditeurAdobe Acrobat PDF Change detection of land use and land cover, using landsat-8 and sentinel-2A images / Mohammed Abdulmohsen Alhedyan (2021)
Titre : Change detection of land use and land cover, using landsat-8 and sentinel-2A images Type de document : Thèse/HDR Auteurs : Mohammed Abdulmohsen Alhedyan, Auteur Editeur : Leicester [Royaume-Uni] : University of Leicester Année de publication : 2021 Importance : 228 p. Format : 21 x 30 cm Note générale : bibliographie
Thesis submitted for the degree of PhD at the University of LeicesterLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse vectorielle
[Termes IGN] Arabie Saoudite
[Termes IGN] Corine (base de données)
[Termes IGN] détection de changement
[Termes IGN] image Landsat-8
[Termes IGN] image Sentinel-MSI
[Termes IGN] occupation du sol
[Termes IGN] Royaume-Uni
[Termes IGN] utilisation du solRésumé : (auteur) The main theme of this research is the development of a new hybrid method for change detection of land use and land cover (LULC). LULC change detection is one of most widely used applications of remote sensing. This study used data from two different optical sensors, Landsat-8 images and Sentinel-2A images. Given the newly developed capabilities of these remote sensing satellites, it was necessary to devise appropriate techniques to realise the benefits that they offer. Therefore, three effective change detection methods have been tested, comprehensively analysed, and used to inform the design and development of a new hybrid method of change detection. The studied change detection methods were change vector analysis (CVA), multi-index integrated change analysis (MIICA), and the comprehensive change detection method (CCDM). Case studies were conducted in two regions, Bristol (United Kingdom) and Hail (Saudi Arabia), to provide sufficient variety of inputs to enable the response of more LULC varieties to be recorded. Finally, the Coordination of Information on the Environment (Corine) land cover scheme was used to identify land cover types and LULC changes. In the study area of Bristol, the new hybrid change detection method achieved an overall accuracy of 90% and 0.81 kappa, while the results for the study area of Hail were 74% overall accuracy and 0.40 kappa. The change detection results obtained by the new hybrid method constitute a significant improvement over the implementation of the existing CVA, MIICA and CCDM methods at the two study areas while using Landsat-8 and Sentinel-2A images. Note de contenu : 1- Introduction
2- Literature review
3- Classification system, study areas, data sources and data preparation process
4- Evaluation of existing change detection
5- The hybrid change detection method
6- Discussion
7- ConclusionNuméro de notice : 28466 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : PhD thesis : Leicester : Geography, Geology, and Environment : 2021 DOI : 10.25392/leicester.data.16988440.v1 En ligne : https://doi.org/10.25392/leicester.data.16988440.v1 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99094
Titre : Climate variability and change in the 21th Century Type de document : Monographie Auteurs : Stefanos Stefanidis, Éditeur scientifique ; Konstantia Tolika, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2021 Importance : 384 p. Format : 15 x 22 cm ISBN/ISSN/EAN : 978-3-0365-0109-3 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] bassin hydrographique
[Termes IGN] Caucase
[Termes IGN] chaleur
[Termes IGN] changement climatique
[Termes IGN] climatologie
[Termes IGN] Côte d'Ivoire
[Termes IGN] cultures irriguées
[Termes IGN] gestion de l'eau
[Termes IGN] Guinée
[Termes IGN] image NPP-VIIRS
[Termes IGN] image Sentinel-OLCI
[Termes IGN] image Terra-MODIS
[Termes IGN] incendie
[Termes IGN] modèle hydrographique
[Termes IGN] précipitation
[Termes IGN] ressources en eau
[Termes IGN] sécheresse
[Termes IGN] série temporelleRésumé : (auteur) Water resources management should be assessed under climate change conditions, as historic data cannot replicate future climatic conditions. - Climate change impacts on water resources are bound to affect all water uses, i.e., irrigated agriculture, domestic and industrial water supply, hydropower generation, and environmental flow (of streams and rivers) and water level (of lakes). - Bottom-up approaches, i.e., the forcing of hydrologic simulation models with climate change models’ outputs, are the most common engineering practices and considered as climate-resilient water management approaches. - Hydrologic simulations forced by climate change scenarios derived from regional climate models (RCMs) can provide accurate assessments of the future water regime at basin scales. - Irrigated agriculture requires special attention as it is the principal water consumer and alterations of both precipitation and temperature patterns will directly affect agriculture yields and incomes. - Integrated water resources management (IWRM) requires multidisciplinary and interdisciplinary approaches, with climate change to be an emerging cornerstone in the IWRM concept. Note de contenu : 1- Study on temporal variations of surface temperature and rainfall at Conakry Airport, Guinea: 1960–2016
2- Ushering in the new era of radiometric intercomparison of multispectral sensors with precision SNO analysis
3- The 10-year return levels of maximum wind speeds under frozen and unfrozen soil forest conditions in Finland
4- Characterization of meteorological droughts occurrences in Côte d’Ivoire: Case of the Sassandra watershed
5- Constraints to vegetation growth reduced by region-specific changes in seasonal climate
6- Influence of bias correction methods on simulated Köppen−Geiger climate zones in Europe
7- Analysis of climate change in the Caucasus region: End of the 20th–beginning of the 21st century
8- Assessing heat waves over Greece using the Excess Heat Factor (EHF)
9- Statistical analysis of recent and future rainfall and temperature variability in the Mono River watershed (Benin, Togo)
10- Multi-model forecasts of very-large fire occurences during the end of the 21st Century
11- Objective definition of climatologically homogeneous areas in the Southern Balkans based on the ERA5 data set
12- Time series analysis of MODIS-derived NDVI for the Hluhluwe-Imfolozi Park, South Africa: Impact of recent intense drought
13- Selecting and downscaling a set of climate models for projecting climatic change for impact assessment in the upper indus basin (UIB)
14- Estimating the impact of artificially injected stratospheric aerosols on the global mean surface temperature in the 21th Century
15- A proposal to evaluate drought characteristics using multiple climate models for multiple timescales
16- Spatial and temporal rainfall variability over the mountainous central Pindus (Greece)
17- Intercomparison of univariate and joint bias correction methods in changing climate from a hydrological perspective
18- Projected changes in precipitation, temperature, and drought across California’s hydrologic regions in the 21st CenturyNuméro de notice : 28454 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Recueil / ouvrage collectif DOI : 10.3390/books978-3-0365-0109-3 En ligne : https://doi.org/10.3390/books978-3-0365-0109-3 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99023
Titre : Copernicus Sentinel-2 geometric calibration status Type de document : Article/Communication Auteurs : Sébastien Clerc, Auteur ; Marion Neveu Van Malle, Auteur ; Stéphane Massera , Auteur ; Carine Quang, Auteur ; Alice Chambrelan, Auteur ; François Guyot, Auteur ; Laetitia Pessiot, Auteur ; Rosario Iannone, Auteur ; Valentina Boccia, Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2021 Projets : 1-Pas de projet / Conférence : IGARSS 2021, IEEE International Geoscience And Remote Sensing Symposium 11/07/2021 16/07/2021 Bruxelles Belgique Proceedings IEEE Importance : pp 8170 - 8172 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] étalonnage géométrique
[Termes IGN] image Sentinel-MSIRésumé : (auteur) The Sentinel-2 mission is a key element of the Copernicus Earth monitoring program of the European Union. The mission is currently composed of two satellites and provides a continuous observation of land and coastal areas at high spatial resolution and with a revisit time of 5 days at the equator. The geometric uncertainty of the Sentinel-2 product is a critical contributor to the performance of the mission. We present the approach used to calibrate the geometric performance of Sentinel-2 data and latest activities, especially related to the co-registration with the Global Reference Image (GRI). Generation of the GRI, coregistration algorithm, called geometric refinement, and preliminary results are presented. Numéro de notice : C2021-085 Affiliation des auteurs : IGN+Ext (2020- ) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/IGARSS47720.2021.9555090 Date de publication en ligne : 12/10/2021 En ligne : https://doi.org/10.1109/IGARSS47720.2021.9555090 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101284 Deep learning for wildfire progression monitoring using SAR and optical satellite image time series / Puzhao Zhang (2021)PermalinkDétection de changement d’occupation du sol à l’aide de données Sentinel en contexte tropical / Lucas Martelet (2021)PermalinkDiurnal cycles of C-band temporal coherence and backscattering coefficient over an olive orchard in a semi-arid area: Comparison of in situ and Sentinel-1 radar observations / Adnane Chakir (2021)PermalinkDiurnal cycles of C-band temporal coherence and backscattering coefficient over a wheat field in a semi-arid area / Nadia Ouaadi (2021)PermalinkDynamics of inundation events in the rivers-estuaries-ocean continuum in Bengal delta : synergy between hydrodynamic modelling and spaceborne remote sensing / Md Jamal Uddin Kahn (2021)PermalinkEnsemble learning methods on the space of covariance matrices : application to remote sensing scene and multivariate time series classification / Sara Akodad (2021)PermalinkPermalinkÉvaluation de l'évapotranspiration des zones irriguées en piémont du Haut Atlas, Maroc / Jamal Elfarkh (2021)PermalinkEvaluation of Sentinel-1 & 2 time series for the identification and characterization of ecological continuities, from wooded to crop-dominated landscapes / Audrey Mercier (2021)PermalinkExamining the effectiveness of Sentinel-1 and 2 imagery for commercial forest species mapping / Mthembeni Mngadi in Geocarto international, vol 36 n° 1 ([01/01/2021])PermalinkFlood mapping from radar remote sensing using automated image classification techniques / Lisa Landuyt (2021)PermalinkPermalinkFrom local to global: A transfer learning-based approach for mapping poplar plantations at national scale using Sentinel-2 / Yousra Hamrouni in ISPRS Journal of photogrammetry and remote sensing, vol 171 (January 2021)PermalinkGeospatial analysis of September, 2019 floods in the lower gangetic plains of Bihar using multi-temporal satellites and river gauge data / C.M. Bhatt in Geomatics, Natural Hazards and Risk, vol 12 n° 1 (2021)PermalinkPermalinkImpact of forest disturbance on InSAR surface displacement time series / Paula M. Bürgi in IEEE Transactions on geoscience and remote sensing, vol 59 n° 1 (January 2021)PermalinkInvestigation of Sentinel-1 time series for sensitivity to fern vegetation in an European temperate forest / Marlin Mueller (2021)PermalinkLearning disentangled representations of satellite image time series in a weakly supervised manner / Eduardo Hugo Sanchez (2021)PermalinkPermalinkPermalinkNear-real-time identification of the drivers of deforestation in French Guiana / Marie Ballère (2021)PermalinkProduction et mise à jour d’un produit BD Forêt V3 par apprentissage profond / Sébastien Giordano (2021)PermalinkQualification des données LiDAR GEDI pour le suivi de l’impact climatique sur la forêt de Südharz / Iris Jeuffrard (2021)PermalinkPermalinkPermalinkSAR data for tropical forest disturbance alerts in French Guiana: Benefit over optical imagery / Marie Ballère in Remote sensing of environment, Vol 252 (January 2021)PermalinkSeasonal flow variability of Greenlandic glaciers : satellite observations and numerical modeling to study driving processes / Anna Derkacheva (2021)PermalinkSemantic segmentation of sea ice type on Sentinel-1 SAR data using convolutional neural networks / Alissa Kouraeva (2021)PermalinkSuivi de la déforestation à partir de données Sentinel-1 en contexte tropical / Lucile Auzeméry (2021)PermalinkSuivi de la rotation des cultures à partir de séries temporelles d’images satellite / Félix Quinton (2021)PermalinkPermalinkPermalinkTélédétection et intégration de connaissances via la modélisation spatiale pour une cartographie plus cohérente des systèmes agricoles complexes / Arthur Crespin-Boucaud (2021)PermalinkThe use of deep machine learning for the automated selection of remote sensing data for the determination of areas of arable land degradation processes distribution / Dimitri I. Rukhovitch in Remote sensing, vol 13 n° 1 (January-1 2021)PermalinkTime-series analysis of massive satellite images : Application to earth observation / Alexandre Constantin (2021)PermalinkUnmixing-based Sentinel-2 downscaling for urban land cover mapping / Fei Xu in ISPRS Journal of photogrammetry and remote sensing, vol 171 (January 2021)PermalinkUsing remote sensing and modeling to monitor and understand harmful algal blooms. Application to Karaoun Reservoir (Lebanon) / Najwa Sharaf (2021)PermalinkVolumes by tree species can be predicted using photogrammetric UAS data, Sentinel-2 images and prior field measurements / Mikko Kukkonen in Silva fennica, vol 55 n° 1 (January 2021)PermalinkMonitoring of wheat crops using the backscattering coefficient and the interferometric coherence derived from Sentinel-1 in semi-arid areas / Nadia Ouaadi in Remote sensing of environment, Vol 251 (15 December 2020)PermalinkDeep learning for detecting and classifying ocean objects: application of YoloV3 for iceberg–ship discrimination / Frederik Hass in ISPRS International journal of geo-information, vol 9 n° 12 (December 2020)PermalinkExploring the inclusion of Sentinel-2 MSI texture metrics in above-ground biomass estimation in the community forest of Nepal / Santa Pandit in Geocarto international, vol 35 n° 16 ([01/12/2020])PermalinkForest cover mapping based on a combination of aerial images and Sentinel-2 satellite data compared to National Forest Inventory data / Selina Ganz in Forests, vol 11 n° 12 (December 2020)PermalinkInclusion of GPS clock estimates for satellites Sentinel-3A/3B in DORIS geodetic solutions / Petr Štěpánek in Journal of geodesy, vol 94 n° 12 (December 2020)PermalinkMultistrategy ensemble regression for mapping of built-up density and height with Sentinel-2 data / Christian Geiss in ISPRS Journal of photogrammetry and remote sensing, vol 170 (December 2020)PermalinkCartographie des cultures dans le périmètre du Loukkos (Maroc) : apport de la télédétection radar et optique / Siham Acharki in Revue Française de Photogrammétrie et de Télédétection, n° 222 (novembre 2020)Permalink