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1. Identificação
Tipo de ReferênciaCapítulo de Livro (Book Section)
Siteplutao.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP3W/48742P5
Repositóriosid.inpe.br/plutao/2022/12.12.17.39.21   (acesso restrito)
Última Atualização2022:12.15.14.28.58 (UTC) lattes
Repositório de Metadadossid.inpe.br/plutao/2022/12.12.17.39.22
Última Atualização dos Metadados2023:01.03.16.52.57 (UTC) administrator
DOI10.3390/books978-3-0365-5668-0
ISBN9783036556
Rótulolattes: 8734553235868564 2 ShimabukuroDuArDuCaPeCa:2022:MaBuAr
Chave de CitaçãoShimabukuroDuArDuCaPeCa:2022:MaBuAr
TítuloMapping Burned Areas of Mato Grosso State Brazilian Amazon Using Multisensor Datasets
Ano2022
Data de Acesso12 maio 2024
Tipo SecundárioPRE LI
Número de Arquivos1
Tamanho11105 KiB
2. Contextualização
Autor1 Shimabukuro, Yosio Edemir
2 Dutra, Andeise Cerqueira
3 Arai, Egidio
4 Duarte, Valdete
5 Cassol, Henrique Luís Godinho
6 Pereira, Gabriel
7 Cardozo, Francielle da Silva
Identificador de Curriculo1 8JMKD3MGP5W/3C9JJCQ
2
3 8JMKD3MGP5W/3C9JGUP
4 8JMKD3MGP5W/3C9JJAU
Grupo1 DIOTG-CGCT-INPE-MCTI-GOV-BR
2 SER-SRE-DIPGR-INPE-MCTI-GOV-BR
3 DIOTG-CGCT-INPE-MCTI-GOV-BR
4 DIOTG-CGCT-INPE-MCTI-GOV-BR
5 DIOTG-CGCT-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)
5 Instituto Nacional de Pesquisas Espaciais (INPE)
6 Universidade Federal de São João Del Rei
7 Universidade Federal de São João Del Rei
Endereço de e-Mail do Autor1 yosio.shimabukuro@inpe.br
2 andeise.dutra@inpe.br
3 egidio.arai@inpe.br
4 valdete.duarte@inpe.br
5 henrique.cassol@inpe.br
6 pereira@ufsj.edu.br
7 franciellecardozo@ufsj.edu.br
EditorFernández-Manso, A.
Quintano, C.
Título do LivroAdvances in Remote Sensing of Postfire Environmental Damage and Recovery Dynamics
Editora (Publisher)MDPI
CidadeBasel
Páginas115-137
Histórico (UTC)2022-12-12 17:39:22 :: lattes -> administrator ::
2022-12-13 10:47:49 :: administrator -> lattes :: 2022
2022-12-15 14:29:00 :: lattes -> administrator :: 2022
2022-12-20 10:35:21 :: administrator -> lattes :: 2022
2022-12-20 13:36:48 :: lattes -> administrator :: 2022
2023-01-03 16:52:57 :: administrator -> simone :: 2022
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-Chaveburned areas detection
shade fraction image
linear spectral mixing model
VIIRS

PROBA-V
Landsat-8 OL
ResumoQuantifying forest fires remain a challenging task for the implementation of public policies aimed to mitigate climate change. In this paper, we propose a new method to provide an annual burned area map of Mato Grosso State located in the Brazilian Amazon region, taking advantage of the high spatial and temporal resolution sensors. The method consists of generating the vegetation, soil, and shade fraction images by applying the Linear Spectral Mixing Model (LSMM) to the Landsat-8 OLI (Operational Land Imager), PROBA-V (Project for On-Board AutonomyVegetation), and Suomi NPP-VIIRS (National Polar-Orbiting Partnership-Visible Infrared Imaging Radiometer Suite) datasets. The shade fraction images highlight the burned areas, in which values are represented by low reflectance of ground targets, and the mapping was performed using an unsupervised classifier. Burned areas were evaluated in terms of land use and land cover classes over the Amazon, Cerrado and Pantanal biomes in the Mato Grosso State. Our results showed that most of the burned areas occurred in non-forested areas (66.57%) and old deforestation (21.54%). However, burned areas over forestlands (11.03%), causing forest degradation, reached more than double compared with burned areas identified in consolidated croplands (5.32%). The results obtained were validated using the Sentinel-2 data and compared with active fire data and existing global burned areas products, such as the MODIS (Moderate Resolution Imaging Spectroradiometer product) MCD64A1 and MCD45A1, and Fire CCI (ESA Climate Change Initiative) products. Although there is a good visual agreement among the analyzed products, the areas estimated were quite different. Our results presented correlation of 51% with Sentinel-2 and agreement of r2 = 0.31, r2 = 0.29, and r2 = 0.43 with MCD64A1, MCD45A1, and Fire CCI products, respectively. However, considering the active fire data, it was achieved the better performance between active fire presence and burn mapping (92%). The proposed method provided a general perspective about the patterns of fire in various biomes of Mato Grosso State, Brazil, that are important for the environmental studies, specially related to fire severity, regeneration, and greenhouse gas emissions.
ÁreaSRE
Arranjo 1urlib.net > BDMCI > Fonds > Produção pgr ATUAIS > SER > Mapping Burned Areas...
Arranjo 2urlib.net > BDMCI > Fonds > Produção a partir de 2021 > CGCT > Mapping Burned Areas...
Conteúdo da Pasta docacessar
Conteúdo da Pasta sourcenão têm arquivos
Conteúdo da Pasta agreementnão têm arquivos
4. Condições de acesso e uso
Idiomaen
Arquivo Alvoshimabukuro_mapping.pdf
Grupo de Usuárioslattes
Visibilidadeshown
Permissão de Leituradeny from all and allow from 150.163
5. Fontes relacionadas
Unidades Imediatamente Superiores8JMKD3MGPCW/3F3NU5S
8JMKD3MGPCW/46KUATE
URL (dados não confiáveis)https://www.mdpi.com/books/book/6270-advances-in-remote-sensing-of-postfire-environmental-damage-and-recovery-dynamics
Acervo Hospedeirodpi.inpe.br/plutao@80/2008/08.19.15.01
6. Notas
Campos Vaziosarchivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel dissemination documentstage e-mailaddress edition format issn lineage mark mirrorrepository nextedition notes numberofvolumes orcid parameterlist parentrepositories previousedition previouslowerunit progress project readergroup rightsholder schedulinginformation secondarydate secondarykey secondarymark serieseditor seriestitle session shorttitle sponsor subject tertiarymark tertiarytype translator volume
7. Controle da descrição
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