Fechar

1. Identificação
Tipo de ReferênciaArtigo em Revista Científica (Journal Article)
Siteplutao.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
IdentificadorJ8LNKAN8RW/3AFKS9M
Repositóriodpi.inpe.br/plutao/2011/09.22.16.13.13
Última Atualização2011:10.10.13.18.11 (UTC) marciana
Repositório de Metadadosdpi.inpe.br/plutao/2011/09.22.16.13.14
Última Atualização dos Metadados2018:06.05.00.01.23 (UTC) administrator
DOI10.3390/rs3091943
ISSN2072-4292
Rótulolattes: 1913003589198061 2 AraiShimPereVija:2011:AMuMu
Chave de CitaçãoAraiShimPereVija:2011:MuMuTe
TítuloA multi-resolution multi-temporal technique for detecting and mapping deforestation in the Brazilian Amazon rainforest
Ano2011
MêsSet.
Data de Acesso11 maio 2024
Tipo de Trabalhojournal article
Tipo SecundárioPRE PI
Número de Arquivos1
Tamanho7277 KiB
2. Contextualização
Autor1 Arai, Egídio
2 Shimabukuro, Yosio Edemir
3 Pereira, Gabriel
4 Vijaykumar, Nandamudi Lankalapalli
Identificador de Curriculo1 8JMKD3MGP5W/3C9JGUP
2 8JMKD3MGP5W/3C9JJCQ
3
4 8JMKD3MGP5W/3C9JHTU
Grupo1 DSR-OBT-INPE-MCT-BR
2 DSR-OBT-INPE-MCT-BR
3 DSR-OBT-INPE-MCT-BR
4 LAC-CTE-INPE-MCT-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
2 yosio@ltid.inpe.br
3 gabriel@dsr.inpe.br
4 vijay@lac.inpe.br
Endereço de e-Mailyosio@ltid.inpe.br
RevistaRemote Sensing
Volume3
Número9
Páginas1943-1956
Histórico (UTC)2011-09-23 14:11:15 :: lattes -> secretaria.cpa@dir.inpe.br :: 2011
2012-01-17 14:51:52 :: secretaria.cpa@dir.inpe.br -> administrator :: 2011
2016-06-04 01:07:45 :: administrator -> marciana :: 2011
2016-08-19 13:24:39 :: marciana -> administrator :: 2011
2018-06-05 00:01:23 :: administrator -> marciana :: 2011
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-ChaveAmazon rain forest
Amazonia
Bootstrap technique
Brazilian Amazon
Cloud interference
Computational resources
Confidence interval
Dynamic process
Environment change
High frequency
High spatial resolution
Image simulations
LANDSAT
LandSat 7
Landsat-7 (L7) Enhanced Thematic mapper plus (ETM+)
Linear regression methods
Linear spectral mixing models
Moderate resolution imaging spectroradiometer
Modis
Multi-resolutions
Multi-temporal
Observed data
Reference image
Sensibility analysis
Simulated images
Spatial resolution
T-tests
Tropical deforestation
Resumohe analysis of rapid environment changes requires orbital sensors with high frequency of data acquisition to minimize cloud interference in the study of dynamic processes such as Amazon tropical deforestation. Moreover, a medium to high spatial resolution data is required due to the nature and complexity of variables involved in the process. In this paper we describe a multiresolution multitemporal technique to simulate Landsat 7 Enhanced Thematic Mapper Plus (ETM+) image using Terra Moderate Resolution Imaging Spectroradiometer (MODIS). The proposed method preserves the spectral resolution and increases the spatial resolution for mapping Amazon Rainfores deforestation using low computational resources. To evaluate this technique, sample images were acquired in the Amazon rainforest border (MODIS tile H12-V10 and ETM+/Landsat 7 path 227 row 68) for 17 July 2002 and 05 October 2002. The MODIS-based simulated ETM+ and the corresponding original ETM+ images were compared through a linear regression method. Additionally, the bootstrap technique was used to calculate the confidence interval for the model to estimate and to perform a sensibility analysis. Moreover, a Linear Spectral Mixing Model, which is the technique used for deforestation mapping in Program for Deforestation Assessment in the Brazilian Legal Amazonia (PRODES) developed by National Institute for Space Research (INPE), was applied to analyze the differences in deforestation estimates. The results showed high correlations, with values between 0.70 and 0.94 (p < 0.05, students t test) for all ETM+ bands, indicating a good assessment between simulated and observed data (p < 0.05, Z-test). Moreover, simulated image showed a good agreement with a reference image, originating commission errors of 1% of total area estimated as deforestation in a sample area test. Furthermore, approximately 6% or 70 km² of deforestation areas were missing in simulated image classification. Therefore, the use of Landsat simulated image provides better deforestation estimation than MODIS alone.
ÁreaSRE
Arranjo 1urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > A multi-resolution multi-temporal...
Arranjo 2urlib.net > BDMCI > Fonds > Produção anterior à 2021 > LABAC > A multi-resolution multi-temporal...
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/J8LNKAN8RW/3AFKS9M
URL dos dados zipadoshttp://urlib.net/zip/J8LNKAN8RW/3AFKS9M
Idiomaen
Arquivo Alvoremotesensing-03-01943.pdf
Grupo de Usuáriosadministrator
lattes
secretaria.cpa@dir.inpe.br
Grupo de Leitoresadministrator
marciana
Visibilidadeshown
Política de Arquivamentoallowpublisher allowfinaldraft
Permissão de Leituraallow from all
Permissão de Atualizaçãonão transferida
5. Fontes relacionadas
Unidades Imediatamente Superiores8JMKD3MGPCW/3ER446E
8JMKD3MGPCW/3ESGTTP
DivulgaçãoSCIELO; COMPENDEX.
Acervo Hospedeirodpi.inpe.br/plutao@80/2008/08.19.15.01
6. Notas
Campos Vaziosalternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel format isbn lineage mark mirrorrepository nextedition notes orcid parameterlist parentrepositories previousedition previouslowerunit progress project rightsholder schedulinginformation secondarydate secondarykey secondarymark session shorttitle sponsor subject tertiarymark tertiarytype url
7. Controle da descrição
e-Mail (login)marciana
atualizar 


Fechar