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1. Identificação
Tipo de ReferênciaArtigo em Revista Científica (Journal Article)
Sitemtc-m21b.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP3W34P/3L9LLEL
Repositóriosid.inpe.br/mtc-m21b/2016/03.03.16.51   (acesso restrito)
Última Atualização2016:03.03.16.53.54 (UTC) simone
Repositório de Metadadossid.inpe.br/mtc-m21b/2016/03.03.16.51.05
Última Atualização dos Metadados2018:06.04.02.40.36 (UTC) administrator
DOI10.1016/j.future.2015.07.005
ISSN0167-739X
Chave de CitaçãoArcanjoLuzFazeRamo:2016:MeEvVo
TítuloMethods for evaluating volunteers’ contributions in a deforestation detection citizen science project
Ano2016
MêsMar.
Data de Acesso09 maio 2024
Tipo de Trabalhojournal article
Tipo SecundárioPRE PI
Número de Arquivos1
Tamanho6800 KiB
2. Contextualização
Autor1 Arcanjo, Jeferson de Souza
2 Luz, Eduardo F. P.
3 Fazenda, Álvaro L.
4 Ramos, Fernando Manuel
Identificador de Curriculo1
2
3
4 8JMKD3MGP5W/3C9JH4A
Grupo1 DPI-OBT-INPE-MCTI-GOV-BR
2
3
4 LAC-CTE-INPE-MCTI-GOV-BR
Afiliação1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 National Center for Monitoring and Early Warning of Natural Disasters (Cemaden)
3 Universidade Federal de São Paulo (UNIFESP)
4 Instituto Nacional de Pesquisas Espaciais (INPE)
Endereço de e-Mail do Autor1 jeferson@dpi.inpe.br
2
3
4 fernando.ramos@inpe.br
RevistaFuture Generation Computer Systems
Volume56
Páginas550-557
Nota SecundáriaA1_ENGENHARIAS_III A2_SAÚDE_COLETIVA A2_INTERDISCIPLINAR A2_ENGENHARIAS_IV A2_CIÊNCIA_DA_COMPUTAÇÃO B1_MEDICINA_I B1_CIÊNCIAS_SOCIAIS_APLICADAS_I
Histórico (UTC)2016-03-03 16:51:05 :: simone -> administrator ::
2016-06-04 05:08:16 :: administrator -> simone :: 2016
2016-06-20 12:53:20 :: simone -> administrator :: 2016
2018-06-04 02:40:36 :: 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-ChaveCitizen science
Data analysis and validation
Forest monitoring
ResumoToday, due to the availability of free remote sensing data, efficient algorithms for image classification and increased connectivity and computing power, together with international policy initiatives, such as the United Nations Programme on Reducing Emissions from Deforestation and Forest Degradation (UN-REDD), more and more countries are investing in their own national forest monitoring schemes. However, tropical forests remain under threat worldwide. Recently, a citizen science project that enables citizens around the globe to be involved in forest monitoring tasks has been proposed, called ForestWatchers (www.forestwatchers.net). Its main goal is to allow volunteers (many of them with no scientific training) around the globe, with their own smartphones, tablets and notebooks, review satellite images of forested regions and confirm whether automatic assignments of forested and deforested regions are correct. Inspected images are then sent to a central database where the results are integrated to generate up-to-date deforestation maps. This approach offers a low-cost way to both strengthen the scientific infrastructure and engage members of the public in science. Here, we describe the methods developed within the scope of the ForestWatchers project to assess the volunteers performance. These tools have been evaluated with data of two of the projects preliminary tasks. The first, called BestTile, asks volunteers to select which of several images of the same area has the least cloud cover, while in the second, called Deforestation, volunteers draw polygons on satellite images delimiting areas they believe have been deforested. The results from more than 500 volunteers show that using simple statistical tests, it is possible to achieve a triple goal: to increase the overall efficiency of the data collecting tasks by reducing the required number of volunteers per task, to identify malicious behavior and outliers, and to motivate volunteers to continue their contributions.
ÁreaSRE
Arranjo 1urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDPI > Methods for evaluating...
Arranjo 2urlib.net > BDMCI > Fonds > Produção anterior à 2021 > LABAC > Methods for evaluating...
Conteúdo da Pasta docacessar
Conteúdo da Pasta sourcenão têm arquivos
Conteúdo da Pasta agreement
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4. Condições de acesso e uso
Idiomaen
Arquivo Alvoarcanjo_methods.pdf
Grupo de Usuáriossimone
Grupo de Leitoresadministrator
simone
Visibilidadeshown
Permissão de Leituradeny from all and allow from 150.163
Permissão de Atualizaçãonão transferida
5. Fontes relacionadas
Repositório Espelhourlib.net/www/2011/03.29.20.55
Unidades Imediatamente Superiores8JMKD3MGPCW/3EQCCU5
8JMKD3MGPCW/3ESGTTP
Lista de Itens Citandosid.inpe.br/bibdigital/2013/09.09.15.05 12
sid.inpe.br/bibdigital/2013/09.22.23.14 4
DivulgaçãoWEBSCI; PORTALCAPES; COMPENDEX; SCOPUS.
Acervo Hospedeirosid.inpe.br/mtc-m21b/2013/09.26.14.25.20
6. Notas
Campos Vaziosalternatejournal archivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel e-mailaddress format isbn label lineage mark nextedition notes number orcid parameterlist parentrepositories previousedition previouslowerunit progress project rightsholder schedulinginformation secondarydate secondarykey session shorttitle sponsor subject tertiarymark tertiarytype url
7. Controle da descrição
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