1. Identificação | |
Tipo de Referência | Artigo em Revista Científica (Journal Article) |
Site | mtc-m21d.sid.inpe.br |
Código do Detentor | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
Identificador | 8JMKD3MGP3W34T/4A5HPFL |
Repositório | sid.inpe.br/mtc-m21d/2023/10.31.17.18 (acesso restrito) |
Última Atualização | 2023:10.31.17.18.01 (UTC) simone |
Repositório de Metadados | sid.inpe.br/mtc-m21d/2023/10.31.17.18.01 |
Última Atualização dos Metadados | 2024:01.02.17.16.51 (UTC) administrator |
DOI | 10.1016/j.jsames.2023.104614 |
ISSN | 0895-9811 |
Chave de Citação | HerrmannNasCasFreKlu:2023:SpMoFi |
Título | Spatial modeling of fire in the atlantic forest considering future climate change scenarios in Rio Grande do Sul state - Brazil |
Ano | 2023 |
Mês | Nov. |
Data de Acesso | 16 maio 2024 |
Tipo de Trabalho | journal article |
Tipo Secundário | PRE PI |
Número de Arquivos | 1 |
Tamanho | 6782 KiB |
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2. Contextualização | |
Autor | 1 Herrmann, Pamela Boelter 2 Nascimento, Victor Fernandez 3 Casagrande, Fernanda 4 Freitas, Marcos Wellausen Dias de 5 Klug, Augusta Carla |
Grupo | 1 2 3 DIMNT-CGCT-INPE-MCTI-GOV-BR |
Afiliação | 1 Universidade Federal do Rio Grande do Sul (UFRGS) 2 Universidade Federal do ABC (UFABC) 3 Instituto Nacional de Pesquisas Espaciais (INPE) 4 Universidade Federal do Rio Grande do Sul (UFRGS) 5 Institute of Technology, Engineering Computing, Software Systems and Digital Marketing (INFNET) |
Endereço de e-Mail do Autor | 1 pamelaboelter@gmail.com 2 victor.fernandez@ufabc.edu.br 3 fe.casagrande2@gmail.com 4 marcoswfreitas@gmail.com 5 augusta.klug@al.infnet.edu.br |
Revista | Journal of South American Earth Sciences |
Volume | 131 |
Páginas | e104614 |
Nota Secundária | A1_INTERDISCIPLINAR A1_GEOGRAFIA A2_GEOCIÊNCIAS A2_ENGENHARIAS_III A2_CIÊNCIAS_AGRÁRIAS_I B1_ODONTOLOGIA B1_MEDICINA_II B1_CIÊNCIAS_AMBIENTAIS B1_BIODIVERSIDADE B1_ANTROPOLOGIA_/_ARQUEOLOGIA B2_QUÍMICA B2_MATERIAIS B2_CIÊNCIAS_BIOLÓGICAS_I B3_ASTRONOMIA_/_FÍSICA C_ENGENHARIAS_II |
Histórico (UTC) | 2023-10-31 17:18:01 :: simone -> administrator :: 2023-10-31 17:18:03 :: administrator -> simone :: 2023 2023-10-31 17:18:56 :: simone -> administrator :: 2023 2024-01-02 17:16:51 :: administrator -> simone :: 2023 |
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3. Conteúdo e estrutura | |
É a matriz ou uma cópia? | é a matriz |
Estágio do Conteúdo | concluido |
Transferível | 1 |
Tipo do Conteúdo | External Contribution |
Tipo de Versão | publisher |
Palavras-Chave | Grasslands Machine learning Climate change Fire Climate scenarios |
Resumo | Several biomes worldwide have a long history of conflict over fire use and management. The Atlantic Forest Biome (AFB) is a Brazilian biome that suffers the most from land use and cover changes that cause environmental degradation. The impact of climate change is expected to exacerbate this situation, with extreme weather events potentially leading to a higher frequency and intensity of fire. The main goal of this study is to understand the spatiotemporal distribution of fires for future climate scenarios obtained from CMIP6 climate simulations in the AFB in Rio Grande do Sul (RS) state, Brazil, using machine learning algorithms. This study selected several environmental and anthropogenic variables as factors associated with the cause, occurrence, and spread of fire. The results showed an uneven fire density distribution in the study area. An extensive fire cluster was found in pasture areas located northeast of RS state, reaching more than 1500 fire foci per km2 on average per year. The final model had a training R2 value of 0.99 and a test R2 value of 0.93. The most significant variable identified by the model was the average maximum temperature during the warm period, while livestock is the most influential economic activity. Regarding the simulated fire densities, the period between 2021 and 2040 in the SSP 5.8-5 scenario displayed maximum values that were equivalent to those observed in 2018, with an expansion in the occurrence region observed for the same scenario. However, unexpectedly, between 2081 and 2100, fire density decreased across all areas under the SSP 5.8-5 scenario. This study provides useful insights into climate change context scenarios, offering valuable insights into the intricate relationship between natural processes and human influences, ultimately contributing to informed decision-making and sustainable environmental management. |
Área | MET |
Arranjo | urlib.net > BDMCI > Fonds > Produção a partir de 2021 > CGCT > Spatial modeling of... |
Conteúdo da Pasta doc | acessar |
Conteúdo da Pasta source | não têm arquivos |
Conteúdo da Pasta agreement | |
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4. Condições de acesso e uso | |
Idioma | en |
Arquivo Alvo | 1-s2.0-S0895981123004261-main.pdf |
Grupo de Usuários | simone |
Grupo de Leitores | administrator simone |
Visibilidade | shown |
Política de Arquivamento | denypublisher denyfinaldraft24 |
Permissão de Leitura | deny from all and allow from 150.163 |
Permissão de Atualização | não transferida |
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5. Fontes relacionadas | |
Unidades Imediatamente Superiores | 8JMKD3MGPCW/46KUATE |
Divulgação | WEBSCI; PORTALCAPES; COMPENDEX; SCOPUS. |
Acervo Hospedeiro | urlib.net/www/2021/06.04.03.40 |
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6. Notas | |
Campos Vazios | alternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel e-mailaddress format isbn label lineage mark mirrorrepository nextedition notes number orcid parameterlist parentrepositories previousedition previouslowerunit progress project resumeid rightsholder schedulinginformation secondarydate secondarykey session shorttitle sponsor subject tertiarymark tertiarytype url |
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7. Controle da descrição | |
e-Mail (login) | simone |
atualizar | |
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