Assessment of Renewable Energy Resources with Remote Sensing

Página do item simplificado
dc.contributor.authorMartins, Fernando Ramos [UNIFESP]
dc.contributor.authorLatteshttp://lattes.cnpq.br/9012359647335296pt_BR
dc.contributor.editorMartins, Fernando Ramos [UNIFESP]
dc.coverage.spatialBaselpt_BR
dc.date.accessioned2021-02-02T17:52:07Z
dc.date.available2021-02-02T17:52:07Z
dc.date.issued2021pt_BR
dc.description.abstractThe development of renewable energy sources plays a fundamental role in the transition towards a low carbon economy. Considering that renewable energy resources have an intrinsic relationship with meteorological conditions and climate patterns, methodologies based on the remote sensing of the atmosphere are fundamental sources of information to support the energy sector in planning and operation procedures. This Special Issue is intended to provide a highly recognized international forum to present recent advances in remote sensing to data acquisition required by the energy sector. After a review, a total of eleven papers were accepted for publication. The contributions focus on solar, wind, and geothermal energy resource. This editorial presents a brief overview of each contribution.en
dc.description.affiliationUnifespInstituto do Mar
dc.description.tableofcontentsAbout the Editor .............................................. vii Fernando Ramos Martins Editorial for the Special Issue: Assessment of Renewable Energy Resources with Remote Sensing Reprinted from: Remote Sens. 2020, 12, 3748, doi:10.3390/rs12223748 ................. 1 André R. Gonçalves, Arcilan T. Assireu, Fernando R. Martins, Madeleine S. G. Casagrande, Enrique V. Mattos, Rodrigo S. Costa, Robson B. Passos, Silvia V. Pereira, Marcelo P. Pes, Francisco J. L. Lima and Enio B. Pereira Enhancement of Cloudless Skies Frequency over a Large Tropical Reservoir in Brazil Reprinted from: Remote Sens. 2020, 12, 2793, doi:10.3390/rs12172793 ................. 7 Anders V. Lindfors, Axel Hertsberg, Aku Riihelä, Thomas Carlund, Jörg Trentmann and Richard Müller On the Land-Sea Contrast in the Surface Solar Radiation (SSR) in the Baltic Region Reprinted from: Remote Sens. 2020, 12, 3509, doi:10.3390/rs12213509 ................. 33 Joaquín Alonso-Montesinos Real-Time Automatic Cloud Detection Using a Low-Cost Sky Camera Reprinted from: Remote Sens. 2020, 12, 1382, doi:10.3390/rs12091382 ................. 43 Román Mondragón, Joaquín Alonso-Montesinos, David Riveros-Rosas, Mauro Valdés, Héctor Estévez, Adriana E. González-Cabrera and Wolfgang Stremme Attenuation Factor Estimation of Direct Normal Irradiance Combining Sky Camera Images and Mathematical Models in an Inter-Tropical Area Reprinted from: Remote Sens. 2020, 12, 1212, doi:10.3390/rs12071212 ................. 61 Jinwoong Park, Jihoon Moon, Seungmin Jung and Eenjun Hwang Multistep-Ahead Solar Radiation Forecasting Scheme Based on the Light Gradient Boosting Machine: A Case Study of Jeju Island Reprinted from: Remote Sens. 2020, 12, 2271, doi:10.3390/rs12142271 ................. 79 Guojiang Xiong, Jing Zhang, Dongyuan Shi, Lin Zhu, Xufeng Yuan and Gang Yao Modified Search Strategies Assisted Crossover Whale Optimization Algorithm with Selection Operator for Parameter Extraction of Solar Photovoltaic Models Reprinted from: Remote Sens. 2019, 11, 2795, doi:10.3390/rs11232795 ................. 101 Alexandra I. Khalyasmaa, Stanislav A. Eroshenko, Valeriy A. Tashchilin, Hariprakash Ramachandran, Teja Piepur Chakravarthi and Denis N. Butusov Industry Experience of Developing Day-Ahead Photovoltaic Plant Forecasting System Based on Machine Learning Reprinted from: Remote Sens. 2020, 12, 3420, doi:10.3390/rs12203420 ................. 125 Ian R. Young, Ebru Kirezci and Agustinus Ribal The Global Wind Resource Observed by Scatterometer Reprinted from: Remote Sens. 2020, 12, 2920, doi:10.3390/rs12182920 ................. 147 Susumu Shimada, Jay Prakash Goit, Teruo Ohsawa, Tetsuya Kogaki and Satoshi Nakamura Coastal Wind Measurements Using a Single Scanning LiDAR Reprinted from: Remote Sens. 2020, 12, 1347, doi:10.3390/rs12081347 ................. 165 Cristina Sáez Blázquez, Pedro Carrasco García, Ignacio Martín Nieto, MiguelAngel ´ Maté-González, Arturo Farfán Martín and Diego González-Aguilera Characterizing Geological Heterogeneities for Geothermal Purposes through Combined Geophysical Prospecting Methods Reprinted from: Remote Sens. 2020, 12, 1948, doi:10.3390/rs12121948 ................. 189 Miktha Farid Alkadri, Francesco De Luca, Michela Turrin and Sevil Sariyildiz A Computational Workflow for Generating A Voxel-Based Design Approach Based on Subtractive Shading Envelopes and Attribute Information of Point Cloud Data Reprinted from: Remote Sens. 2020, 12, 2561, doi:10.3390/rs12162561 ................. 207
dc.format.extent246 f.pt_BR
dc.identifierhttps://www.mdpi.com/journal/remotesensing
dc.identifier.citationMARTINS, Fernando Ramos. Assessment of Renewable Energy Resources with Remote Sensing. Basel : MDPI, 2021
dc.identifier.isbn978-3-0365-0481-0pt_BR
dc.identifier.issn2072-4292
dc.identifier.urihttps://repositorio.unifesp.br/handle/11600/60099
dc.languageengpt_BR
dc.publisherMDPIpt_BR
dc.relation.ispartofseriesPrinted Edition of the Special Issue Published in Remote Sensingpt_BR
dc.rightsinfo:eu-repo/semantics/openAccesspt_BR
dc.subjectRenewable energy resource assessment and forecastingen
dc.subjectRemote sensingen
dc.subjectData acquisitionen
dc.subjectData processingen
dc.subjectStatistical analysisen
dc.subjectMachine learning techniquesen
dc.titleAssessment of Renewable Energy Resources with Remote Sensingen
dc.typeinfo:eu-repo/semantics/bookpt_BR
unifesp.campusInstituto do Mar (IMar)pt_BR
unifesp.departamentoCiências do Marpt_BR
Arquivos
Pacote Original
Agora exibindo 1 - 1 de 1
Imagem de Miniatura
Nome:
Remote Sensing Assessment of Renewable Energy Resources with Remote Sensing.pdf
Tamanho:
72.41 MB
Formato:
Adobe Portable Document Format
Descrição:
Baixar
Licença do Pacote
Agora exibindo 1 - 1 de 1
Imagem de Miniatura
Nome:
license.txt
Tamanho:
5.3 KB
Formato:
Item-specific license agreed upon to submission
Descrição:
Baixar
Coleções
IMar - Livros