Fechar

1. Identificação
Tipo de ReferênciaArtigo em Evento (Conference Proceedings)
Siteplutao.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP3W/3MTMTHU
Repositóriosid.inpe.br/plutao/2016/12.05.18.46.20
Última Atualização2016:12.09.15.05.02 (UTC) lattes
Repositório de Metadadossid.inpe.br/plutao/2016/12.05.18.46.21
Última Atualização dos Metadados2018:06.21.04.25.16 (UTC) administrator
DOI10.13140/RG.2.2.26048.12805
Rótulolattes: 2916855460918534 4 KortingNamiFonsFelg:2016:HOEFOB
Chave de CitaçãoKörtingNamiFonsFelg:2016:HoEfOb
TítuloHow to effectively obtain metadata from remote sensing big data?
FormatoDVD
Ano2016
Data de Acesso27 nov. 2022
Tipo SecundárioPRE CI
Número de Arquivos1
Tamanho500 KiB
2. Contextualização
Autor1 Körting, Thales Sehn
2 Namikawa, Laércio Massaru
3 Fonseca, Leila Maria Garcia
4 Felgueiras, Carlos Alberto
Identificador de Curriculo1
2 8JMKD3MGP5W/3C9JHL5
3 8JMKD3MGP5W/3C9JHLD
4 8JMKD3MGP5W/3C9JGQD
Grupo1 DPI-OBT-INPE-MCTI-GOV-BR
2 DPI-OBT-INPE-MCTI-GOV-BR
3 OBT-OBT-INPE-MCTI-GOV-BR
4 DPI-OBT-INPE-MCTI-GOV-BR
Afiliação1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 Instituto Nacional de Pesquisas Espaciais (INPE)
4 Instituto Nacional de Pesquisas Espaciais (INPE)
Endereço de e-Mail do Autor1 thales.korting@inpe.br
2 laercio.namikawa@inpe.br
3 leila.fonseca@inpe.br
4 carlos.felgueiras@inpe.br
Nome do EventoGEOBIA 2016 Solutions and Synergies
Localização do EventoEnschede, The Nederlands
Data14-16 set.
Título do LivroProceedings
Tipo TerciárioPaper
Histórico (UTC)2016-12-05 19:23:58 :: lattes -> administrator :: 2016
2016-12-09 07:36:09 :: administrator -> lattes :: 2016
2016-12-22 16:51:11 :: lattes -> administrator :: 2016
2018-06-21 04:25:16 :: administrator -> simone :: 2016
3. Conteúdo e estrutura
É a matriz ou uma cópia?é a matriz
Estágio do Conteúdoconcluido
Transferível1
Tipo do ConteúdoExternal Contribution
Tipo de Versãopublisher
Palavras-ChaveBig data
Remote Sensing
Metadata
Image Processing
Water indices
Pattern recognition
ResumoWhat can be considered big data when dealing with remote sensing imagery? In general terms, big data is defined as data requiring high management capabilities characterized by 3 Vs: Volume, Velocity and Variety. In the past, (e.g. 1975), considering the computational and databases resources available, a series of Landsat-1 imagery from the same region could be considered big data. Nowadays, several satellites are available, and they produce massive amounts of data. Certainly, an image data set obtained by a single satellite, for a specific region and along time, fills the 3 Vs requirements to be considered big data as well. In order to deal with remote sensing big data, we propose to explore the generation of metadata based on the detection of simple features. Besides the intrinsic geographic information on every remote sensing scene, no additional metadata is usually considered. We propose basic image processing algorithms to detect basic well-known patterns, and include them as tags, such as cloud, shadow, stadium, vegetation, and water, according to what is detectable at each spatial resolution. In this work we show preliminary results using imagery from RapidEye sensor, with 5 meter spatial resolution, composed by two full coverages of Brazil with RapidEye multispectral imagery (around 40k scenes).
ÁreaSRE
Arranjo 1urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDPI > How to effectively...
Arranjo 2urlib.net > BDMCI > Fonds > Produção anterior à 2021 > CGOBT > How to effectively...
Conteúdo da Pasta docacessar
Conteúdo da Pasta sourcenão têm arquivos
Conteúdo da Pasta agreementnão têm arquivos
4. Condições de acesso e uso
URL dos dadoshttp://urlib.net/ibi/8JMKD3MGP3W/3MTMTHU
URL dos dados zipadoshttp://urlib.net/zip/8JMKD3MGP3W/3MTMTHU
Idiomaen
Arquivo Alvokorting_how.pdf
Grupo de Leitoresadministrator
lattes
Visibilidadeshown
Permissão de Leituraallow from all
Permissão de Atualizaçãonão transferida
5. Fontes relacionadas
Repositório Espelhourlib.net/www/2011/03.29.20.55
Unidades Imediatamente Superiores8JMKD3MGPCW/3EQCCU5
8JMKD3MGPCW/3EU2H28
URL (dados não confiáveis)https://www.conftool.net/geobia2016/index.php?page=browseSessions&abstracts=show&form_session=16&presentations=show
Acervo Hospedeirodpi.inpe.br/plutao@80/2008/08.19.15.01
6. Notas
NotasSetores de Atividade: Atividades dos serviços de tecnologia da informação.
Informações Adicionais: ABSTRACT:
What can be considered big data when dealing with remote sensing imagery? In general terms, big data is defined as data requiring high
management capabilities characterized by 3 V?s: Volume, Velocity and Variety. In the past, (e.g. 1975), considering the computational
and databases resources available, a series of Landsat-1 imagery from the same region could be considered big data. Nowadays, several
satellites are available, and they produce massive amounts of data. Certainly, an image data set obtained by a single satellite, for a
specific region and along time, fills the 3 V?s requirements to be considered big data as well. In order to deal with remote sensing big
data, we propose to explore the generation of metadata based on the detection of simple features. Besides the intrinsic geographic information on every remote sensing scene, no additional metadata is usually considered. We propose basic image processing algorithms to
detect basic well-known patterns, and include them as tags, such as cloud, shadow, stadium, vegetation, and water, according to what
is detectable at each spatial resolution. In this work we show preliminary results using imagery from RapidEye sensor, with 5 meter
spatial resolution, composed by two full coverages of Brazil with RapidEye multispectral imagery (around 40k scenes)..
Campos Vaziosarchivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel dissemination e-mailaddress edition editor isbn issn lineage mark nextedition numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress rightsholder secondarydate secondarykey secondarymark serieseditor session shorttitle sponsor subject tertiarymark type usergroup volume
7. Controle da descrição
e-Mail (login)simone
atualizar 


Fechar