Assessment of Renewable Energy Resources with Remote Sensing

Open Access

Assessment of Renewable Energy Resources with Remote Sensing

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 ove...

Full description

Saved in:
Bibliographic Details
Sonstige:
Martins, Fernando Ramos
Year of Publication:2021
Language:English
Physical Description:1 electronic resource (244 p.)
Tags: Add Tag
No Tags, Be the first to tag this record!
id 993546057304498
ctrlnum (CKB)5400000000043445
(oapen)https://directory.doabooks.org/handle/20.500.12854/68491
(EXLCZ)995400000000043445
collection bib_alma
record_format marc
spelling Martins, Fernando Ramos edt
Assessment of Renewable Energy Resources with Remote Sensing
Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
1 electronic resource (244 p.)
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Open access Unrestricted online access star
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.
English
Research & information: general bicssc
metaheuristic
parameter extraction
solar photovoltaic
whale optimization algorithm
cloud detection
digitized image processing
artificial neural networks
solar irradiance estimation
solar irradiance forecasting
solar energy
sky camera
remote sensing
CSP plants
coastal wind measurements
scanning LiDAR
plan position indicator
velocity volume processing
Hazaki Oceanographical Research Station
cloud coverage
image processing
total sky imagery
geothermal energy
geophysical prospecting
time domain electromagnetic method
electrical resistivity tomography
potential well field location
GES-CAL software
smart island
solar radiation forecasting
light gradient boosting machine
multistep-ahead prediction
feature importance
voxel-design approach
shading envelopes
point cloud data
computational design method
passive design strategy
lake breeze influence
hydropower reservoir
solar irradiance enhancement
solar energy resource
wind speed
extreme value analysis
scatterometer
feature engineering
forecasting
graphical user interface software
machine learning
photovoltaic power plant
surface solar radiation
global radiation
satellite
Baltic area
coastline
cloud
convection
climate
renewable energy resource assessment and forecasting
remote sensing data acquisition
data processing
statistical analysis
machine learning techniques
3-0365-0480-X
3-0365-0481-8
Martins, Fernando Ramos oth
language English
format eBook
author2 Martins, Fernando Ramos
author_facet Martins, Fernando Ramos
author2_variant f r m fr frm
author2_role Sonstige
title Assessment of Renewable Energy Resources with Remote Sensing
spellingShingle Assessment of Renewable Energy Resources with Remote Sensing
title_full Assessment of Renewable Energy Resources with Remote Sensing
title_fullStr Assessment of Renewable Energy Resources with Remote Sensing
title_full_unstemmed Assessment of Renewable Energy Resources with Remote Sensing
title_auth Assessment of Renewable Energy Resources with Remote Sensing
title_new Assessment of Renewable Energy Resources with Remote Sensing
title_sort assessment of renewable energy resources with remote sensing
publisher MDPI - Multidisciplinary Digital Publishing Institute
publishDate 2021
physical 1 electronic resource (244 p.)
isbn 3-0365-0480-X
3-0365-0481-8
illustrated Not Illustrated
work_keys_str_mv AT martinsfernandoramos assessmentofrenewableenergyresourceswithremotesensing
status_str n
ids_txt_mv (CKB)5400000000043445
(oapen)https://directory.doabooks.org/handle/20.500.12854/68491
(EXLCZ)995400000000043445
carrierType_str_mv cr
is_hierarchy_title Assessment of Renewable Energy Resources with Remote Sensing
author2_original_writing_str_mv noLinkedField
_version_ 1796652002096185344
fullrecord <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>04604nam-a2201045z--4500</leader><controlfield tag="001">993546057304498</controlfield><controlfield tag="005">20240315202342.0</controlfield><controlfield tag="006">m o d </controlfield><controlfield tag="007">cr|mn|---annan</controlfield><controlfield tag="008">202105s2021 xx |||||o ||| 0|eng d</controlfield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(CKB)5400000000043445</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(oapen)https://directory.doabooks.org/handle/20.500.12854/68491</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(EXLCZ)995400000000043445</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Martins, Fernando Ramos</subfield><subfield code="4">edt</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Assessment of Renewable Energy Resources with Remote Sensing</subfield></datafield><datafield tag="260" ind1=" " ind2=" "><subfield code="a">Basel, Switzerland</subfield><subfield code="b">MDPI - Multidisciplinary Digital Publishing Institute</subfield><subfield code="c">2021</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 electronic resource (244 p.)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">computer</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">online resource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="506" ind1=" " ind2=" "><subfield code="a">Open access</subfield><subfield code="f">Unrestricted online access</subfield><subfield code="2">star</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">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.</subfield></datafield><datafield tag="546" ind1=" " ind2=" "><subfield code="a">English</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Research &amp; information: general</subfield><subfield code="2">bicssc</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">metaheuristic</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">parameter extraction</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">solar photovoltaic</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">whale optimization algorithm</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">cloud detection</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">digitized image processing</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">artificial neural networks</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">solar irradiance estimation</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">solar irradiance forecasting</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">solar energy</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">sky camera</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">remote sensing</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">CSP plants</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">coastal wind measurements</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">scanning LiDAR</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">plan position indicator</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">velocity volume processing</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Hazaki Oceanographical Research Station</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">cloud coverage</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">image processing</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">total sky imagery</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">geothermal energy</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">geophysical prospecting</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">time domain electromagnetic method</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">electrical resistivity tomography</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">potential well field location</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">GES-CAL software</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">smart island</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">solar radiation forecasting</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">light gradient boosting machine</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">multistep-ahead prediction</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">feature importance</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">voxel-design approach</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">shading envelopes</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">point cloud data</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">computational design method</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">passive design strategy</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">lake breeze influence</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">hydropower reservoir</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">solar irradiance enhancement</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">solar energy resource</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">wind speed</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">extreme value analysis</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">scatterometer</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">feature engineering</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">forecasting</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">graphical user interface software</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">machine learning</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">photovoltaic power plant</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">surface solar radiation</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">global radiation</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">satellite</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Baltic area</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">coastline</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">cloud</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">convection</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">climate</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">renewable energy resource assessment and forecasting</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">remote sensing data acquisition</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">data processing</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">statistical analysis</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">machine learning techniques</subfield></datafield><datafield tag="776" ind1=" " ind2=" "><subfield code="z">3-0365-0480-X</subfield></datafield><datafield tag="776" ind1=" " ind2=" "><subfield code="z">3-0365-0481-8</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Martins, Fernando Ramos</subfield><subfield code="4">oth</subfield></datafield><datafield tag="906" ind1=" " ind2=" "><subfield code="a">BOOK</subfield></datafield><datafield tag="ADM" ind1=" " ind2=" "><subfield code="b">2024-03-16 06:11:59 Europe/Vienna</subfield><subfield code="f">system</subfield><subfield code="c">marc21</subfield><subfield code="a">2022-04-04 09:22:53 Europe/Vienna</subfield><subfield code="g">false</subfield></datafield><datafield tag="AVE" ind1=" " ind2=" "><subfield code="i">DOAB Directory of Open Access Books</subfield><subfield code="P">DOAB Directory of Open Access Books</subfield><subfield code="x">https://eu02.alma.exlibrisgroup.com/view/uresolver/43ACC_OEAW/openurl?u.ignore_date_coverage=true&amp;portfolio_pid=5338129780004498&amp;Force_direct=true</subfield><subfield code="Z">5338129780004498</subfield><subfield code="b">Available</subfield><subfield code="8">5338129780004498</subfield></datafield></record></collection>

Similar Items