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Automatic atmospheric correction for shortwave hyperspectral remote sensing data using a time-dependent deep neural network / Jian Sun in ISPRS Journal of photogrammetry and remote sensing, vol 174 (April 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 174 (April 2021) . - pp 117 - 131 Titre : Automatic atmospheric correction for shortwave hyperspectral remote sensing data using a time-dependent deep neural network Type de document : Article/Communication Auteurs : Jian Sun, Auteur ; Fangcao Xu, Auteur ; Guido Cervone, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 117 - 131 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage profond [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] correction atmosphérique [Termes IGN] détection de cible [Termes IGN] image hyperspectrale [Termes IGN] modèle de transfert radiatif [Termes IGN] rayonnement solaire [Termes IGN] réflectivité Résumé : (auteur) Atmospheric correction is an essential step in hyperspectral imaging and target detection from spectrometer remote sensing data. State-of-the-art atmospheric correction approaches either require extensive filed experiments or prior knowledge of atmospheric characteristics to improve the predicted accuracy, which are computational expensive and unsuitable for real time application. To take full advantages of remote sensing observation in quickly and reliably acquiring data for a large area, an automatic and efficient processing tool is required for atmospheric correction. In this paper, we propose a time-dependent neural network for automatic atmospheric correction and target detection using multi-scan hyperspectral data under different elevation angles. In addition to the total radiance, the collection day and time are also incorporated to improve the time-dependency of the network and represent the seasonal and diurnal characteristics of atmosphere and solar radiation. Results show that the proposed network has the capacity to accurately provide atmospheric characteristics and estimate precise reflectivity spectra with 95,72% averaged accuracy for different materials, including vegetation, sea ice, and ocean. Additional experiments are designed to investigate the network’s temporal dependency and performance on missing data. The error analysis confirms that our proposed network is capable of estimating atmospheric characteristics under both seasonally and diurnally varying environments and handling the influence of missing data. Both the predicted results and error analysis are promising and demonstrate that our network has the ability of providing accurate atmospheric correction and target detection in real time. Numéro de notice : A2021-208 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.02.007 Date de publication en ligne : 24/02/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.02.007 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97186 [article]

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Assessment of renewable energy resources with remote sensing / Fernando Ramos Martins (2021)  

Public Titre : Assessment of renewable energy resources with remote sensing Type de document : Monographie Auteurs : Fernando Ramos Martins, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2021 Importance : 244 p. Format : 16 x 23 cm ISBN/ISSN/EAN : 978-3-0365-0481-0 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] apprentissage automatique [Termes IGN] climat [Termes IGN] détection des nuages [Termes IGN] données lidar [Termes IGN] énergie éolienne [Termes IGN] énergie géothermique [Termes IGN] énergie renouvelable [Termes IGN] énergie solaire [Termes IGN] Extreme Gradient Machine [Termes IGN] hydroélectricité [Termes IGN] image GOES [Termes IGN] Matlab [Termes IGN] prévision météorologique [Termes IGN] rayonnement solaire [Termes IGN] réseau neuronal artificiel Résumé : (éditeur) The book “Assessment of Renewable Energy Resources with Remote Sensing" focuses on disseminating scientific knowledge and technological developments for the assessment and forecasting of renewable energy resources using remote sensing techniques. The eleven papers inside the book provide an overview of remote sensing applications on hydro, solar, wind and geothermal energy resources and their major goal is to provide state of art knowledge to contribute with the renewable energy resource deployment, especially in regions where energy demand is rapidly expanding. Renewable energy resources have an intrinsic relationship with local environmental features and the regional climate. Even small and fast environment and/or climate changes can cause significant variability in power generation at different time and space scales. Methodologies based on remote sensing are the primary source of information for the development of numerical models that aim to support the planning and operation of an electric system with a substantial contribution of intermittent energy sources. In addition, reliable data and knowledge on renewable energy resource assessment are fundamental to ensure sustainable expansion considering environmental, financial and energetic security. Note de contenu : 1- Enhancement of cloudless skies frequency over a large tropical reservoir in Brazil 2- On the land-sea contrast in the surface solar radiation (SSR) in the Baltic region 3- Real-time automatic cloud detection using a low-cost sky camera 4- Attenuation factor estimation of direct normal irradiance combining sky camera images and mathematical models in an inter-tropical area 5- Multistep-ahead solar radiation forecasting scheme based on the light gradient boosting machine: A case study of Jeju Island 6- Modified search strategies assisted crossover whale optimization algorithm with selection operator for parameter extraction of solar photovoltaic models 7- Industry experience of developing day-ahead photovoltaic plant forecasting system based on machine learning 8- The global wind resource observed by scatterometer 9- Coastal wind measurements using a single scanning LiDAR 10- Characterizing geological heterogeneities for geothermal purposes through combined geophysical prospecting methods 11- A computational workflow for generating a voxel-based design approach based on subtractive shading envelopes and attribute information of point cloud data Numéro de notice : 28653 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Recueil / ouvrage collectif DOI : 10.3390/books978-3-0365-0481-0 En ligne : https://doi.org/10.3390/books978-3-0365-0481-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99795

Galileo and QZSS precise orbit and clock determination using new satellite metadata / Xingxing Li in Journal of geodesy, vol 93 n° 8 (August 2019)  

Public [article]  inJournal of geodesy > vol 93 n° 8 (August 2019) . - pp 1123 - 1136 Titre : Galileo and QZSS precise orbit and clock determination using new satellite metadata Type de document : Article/Communication Auteurs : Xingxing Li, Auteur ; Yongqiang Yuan, Auteur ; Jiande Huang, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 1123 - 1136 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] centre de phase [Termes IGN] constellation Galileo [Termes IGN] données satellitaires [Termes IGN] GIOVE (satellite) [Termes IGN] horloge du satellite [Termes IGN] lacet [Termes IGN] métadonnées [Termes IGN] modèle d'orbite [Termes IGN] orbite précise [Termes IGN] orbitographie [Termes IGN] Quasi-Zenith Satellite System [Termes IGN] rayonnement solaire [Termes IGN] variance d'Allan Résumé : (auteur) During 2016–2018, satellite metadata/information including antenna parameters, attitude laws and physical characteristics such as mass, dimensions and optical properties were released for Galileo and QZSS (except for the QZS-1 optical coefficients). These metadata are critical for improving the accuracy of precise orbit and clock determination. In this contribution, we evaluate the benefits of these new metadata to orbit and clock in three aspects: the phase center offsets and variations (PCO and PCV), the yaw-attitude model and solar radiation pressure (SRP) model. The updating of Galileo PCO and PCV corrections, from the values estimated by Deutsches Zentrum für Luft- und Raumfahrt and Deutsches GeoForschungsZentrum to the chamber calibrations disclosed by new metadata, has only a slight influence on Galileo orbits, with overlap differences within only 1 mm. By modeling the yaw attitude of Galileo satellites and QZS-2 spacecraft (SVN J002) according to new published attitude laws, the residuals of ionosphere-free carrier-phase combinations can be obviously decreased in yaw maneuver seasons. With the new attitude models, the 3D overlap RMS in eclipse seasons can be decreased from 12.3 cm, 14.7 cm, 16.8 cm and 34.7 cm to 11.7 cm, 13.4 cm, 15.8 cm and 32.9 cm for Galileo In-Orbit Validation (IOV), Full Operational Capability (FOC), FOC in elliptical orbits (FOCe) and QZS-2 satellites, respectively. By applying the a priori box-wing SRP model with new satellite dimensions and optical coefficients, the 3D overlap RMS are 5.3 cm, 6.2 cm, 5.3 cm and 16.6 cm for Galileo IOV, FOCe, FOC and QZS-2 satellites, with improvements of 11.0%, 14.7%, 14.0% and 13.8% when compared with the updated Extended CODE Orbit Model (ECOM2). The satellite laser ranging (SLR) validation reveals that the a priori box-wing model has smaller mean biases of − 0.4 cm, − 0.4 cm and 0.6 cm for Galileo FOCe, FOC and QZS-2 satellites, while a slightly larger mean bias of − 1.0 cm is observed for Galileo IOV satellites. Moreover, the SLR residual dependencies of Galileo IOV and FOC satellites on the elongation angle almost vanish when the a priori box-wing SRP model is applied. As for satellite clocks, a visible bump appears in the Modified Allan deviation at integration time of 20,000 s for Galileo Passive Hydrogen Maser with ECOM2, while it almost vanishes when the a priori box-wing SRP model and new metadata are applied. The standard deviations of clock overlap can also be significantly reduced by using new metadata. Numéro de notice : A2019-383 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-019-01230-4 Date de publication en ligne : 02/02/2019 En ligne : https://doi.org/10.1007/s00190-019-01230-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93462 [article]

Seasonal pattern in time series of variances of GPS residual errors Anova estimates / Darko Anđić in Geodetski vestnik, vol 63 n° 2 (June - August 2019)  

Public [article]  inGeodetski vestnik > vol 63 n° 2 (June - August 2019) . - pp 260 - 271 Titre : Seasonal pattern in time series of variances of GPS residual errors Anova estimates Type de document : Article/Communication Auteurs : Darko Anđić, Auteur Année de publication : 2019 Article en page(s) : pp 260 - 271 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] double différence [Termes IGN] positionnement par GPS [Termes IGN] propagation ionosphérique [Termes IGN] propagation troposphérique [Termes IGN] rayonnement solaire [Termes IGN] résidu [Termes IGN] série temporelle [Termes IGN] variance [Termes IGN] variation saisonnière Résumé : (auteur) In this paper, which represents a continuation of the previous author's work, an inconstancy of GPS residual error ANOVA estimates and their variances are presented. For the purpose of the analysis, fixed solutions for all of the three coordinates, e (eastwards), n (northwards) and u (upwards), obtained by using ionosphere-free (L0) linear combination of double-difference phase observations in the processing of GPS data, were employed. The aim of the research was to consider the behaviour of variances of GPS residual error ANOVA estimates in time because there has not been any paper dealing with that issue so far. Herein, it turned out a seasonal pattern in related time series was present. In addition, it was concluded there was a difference in ANOVA estimate extreme values obtained when one considered daily data subsets compared to those obtained in the approach considering monthly data of the fixed solutions. GPS data collected at ending stations of a baseline of 40 km in length within a four-year period, involving the lowest and increased solar activity, were used in calculations. Numéro de notice : A2019-405 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.15292/geodetski-vestnik.2019.02.260-271 En ligne : http://dx.doi.org/10.15292/geodetski-vestnik.2019.02.260-271 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93509 [article]

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Temporal and spatial high-resolution climate data from 1961 to 2100 for the German National Forest Inventory (NFI) / Helge Dietrich in Annals of Forest Science [en ligne], vol 76 n° 1 (March 2019)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 76 n° 1 (March 2019) Titre : Temporal and spatial high-resolution climate data from 1961 to 2100 for the German National Forest Inventory (NFI) Type de document : Article/Communication Auteurs : Helge Dietrich, Auteur ; Thilo Wolf, Auteur ; Tobias Kawohl, Auteur ; Jan Wehberg, Auteur ; Gerald Kändler, Auteur ; Tobias Mette, Auteur ; Arno Röder, Auteur ; ürgen Böhner, Auteur Année de publication : 2019 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Allemagne [Termes IGN] changement climatique [Termes IGN] données environnementales [Termes IGN] données météorologiques [Termes IGN] historique des données [Termes IGN] inventaire forestier étranger (données) [Termes IGN] largeur de bande [Termes IGN] modèle numérique de surface [Termes IGN] productivité [Termes IGN] rayonnement solaire [Termes IGN] régression géographiquement pondérée [Termes IGN] série temporelle [Termes IGN] station météorologique [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) The “NFI 2012 environmental data base climate” is part of the environmental database of the German National Forest Inventory. It contains climate information for 26,450 inventory points generated from gridded daily climate data for 1961–2100 at a spatial resolution of 250 m. Grids are based on DWD-Observations and REMO EURO-CORDEX climate projections. Access to the databases is provided via the URL: https://doi.org/10.3220/DATA/20180823-102429. Associated metadata are available at https://agroenvgeo.data.inra.fr/geonetwork/srv/fre/catalog.search#/metadata/d0789030-c94e-4883-8d38-2a7332c98673. Numéro de notice : A2019-043 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s13595-018-0788-5 Date de publication en ligne : 23/01/2019 En ligne : https://doi.org/10.1007/s13595-018-0788-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92049 [article]

Simultaneous characterization of objects temperature and radiative properties through multispectral infrared thermography / Thibaud Toullier (2019)  

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A method of downscaling temperature maps based on analytical hillshading for use in species distribution modelling / Ángel M. Felicísimo in Cartography and Geographic Information Science, Vol 45 n° 4 (July 2018)  

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Use of LiDAR for calculating solar irradiance on roofs and façades of buildings at city scale: Methodology, validation, and analysis / Liang Cheng in ISPRS Journal of photogrammetry and remote sensing, vol 138 (April 2018)  

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Factors affecting forest dynamics in the Iberian Peninsula from 1987 to 2012 : The role of topography and drought / Juan José Vidal-Macua in Forest ecology and management, vol 406 (15 December 2017)  

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Estimating the solar transmittance of urban trees using airborne LiDAR and radiative transfer simulation / Haruki Oshio in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)  

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Thin cloud removal based on signal transmission principles and spectral mixture analysis / Meng Xu in IEEE Transactions on geoscience and remote sensing, vol 54 n° 3 (March 2016)  

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Effet de l’exposition sur la richesse et la composition floristique des lisières forestières dans le Gâtinais oriental (Loiret) / Richard Chevalier in Revue forestière française [en ligne], vol 67 n° 5 (septembre 2015)  

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CODE’s new solar radiation pressure model for GNSS orbit determination / Daniel Arnold in Journal of geodesy, vol 89 n° 8 (August 2015)  

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Enhanced solar radiation pressure modeling for Galileo satellites / Oliver Montenbruck in Journal of geodesy, vol 89 n° 3 (March 2015)  

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Reducing the draconitic errors in GNSS geodetic products / C.J. Rodriguez-Solano in Journal of geodesy, vol 88 n° 6 (June 2014)  

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