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Auteur Fernando Ramos Martins |
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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
[Termes IGN] semis de pointsRésumé : (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 dataNuméro 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