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Metadados

1. Identificação
Tipo de ReferênciaArtigo em Revista Científica (Journal Article)
Sitemtc-m21b.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP3W34P/3NNFRAB
Repositóriosid.inpe.br/mtc-m21b/2017/04.18.17.12   (acesso restrito)
Última Atualização2017:04.18.17.12.22 (UTC) administrator
Repositório de Metadadossid.inpe.br/mtc-m21b/2017/04.18.17.12.22
Última Atualização dos Metadados2018:06.04.02.27.24 (UTC) administrator
DOI10.1016/j.rse.2017.03.016
ISSN0034-4257
Chave de CitaçãoCarreirasJoneLucaShim:2017:MaMaLa
TítuloMapping major land cover types and retrieving the age of secondary forests in the Brazilian Amazon by combining single-date optical and radar remote sensing data
Ano2017
MêsJune
Data de Acesso26 abr. 2024
Tipo de Trabalhojournal article
Tipo SecundárioPRE PI
Número de Arquivos1
Tamanho5909 KiB
2. Contextualização
Autor1 Carreiras, João M. B.
2 Jones, Joshua
3 Lucas, Richard M.
4 Shimabukuro, Yosio Edemir
Identificador de Curriculo1
2
3
4 8JMKD3MGP5W/3C9JJCQ
Grupo1
2
3
4 DIDSR-CGOBT-INPE-MCTIC-GOV-BR
Afiliação1 University of Sheffield
2 Aberystwyth University
3 University of New South Wales
4 Instituto Nacional de Pesquisas Espaciais (INPE)
Endereço de e-Mail do Autor1 j.carreiras@sheffield.ac.uk
2
3
4 yosio.shimabukuro@inpe.br
RevistaRemote Sensing of Environment
Volume194
Páginas16-32
Nota SecundáriaA1_INTERDISCIPLINAR A1_GEOCIÊNCIAS A1_ENGENHARIAS_I A1_CIÊNCIAS_BIOLÓGICAS_I A1_CIÊNCIAS_AMBIENTAIS A1_CIÊNCIAS_AGRÁRIAS_I A1_BIODIVERSIDADE
Histórico (UTC)2017-04-18 17:12:22 :: simone -> administrator ::
2017-04-18 17:12:22 :: administrator -> simone :: 2017
2017-04-18 17:13:00 :: simone -> administrator :: 2017
2018-06-04 02:27:24 :: administrator -> simone :: 2017
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-ChaveAge of secondary forests
ALOS PALSAR
Amazon
Landsat TM
Random forests
Tropical secondary forests
ResumoSecondary forests play an important role in restoring carbon and biodiversity lost previously through deforestation and degradation and yet there is little information available on the extent of different successional stages. Such knowledge is particularly needed in tropical regions where past and current disturbance rates have been high but regeneration is rapid. Focusing on three areas in the Brazilian Amazon (Manaus, Santarém, Machadinho d'Oeste), this study aimed to evaluate the use of single-date Landsat Thematic Mapper (TM) and Advanced Land Observing Satellite (ALOS) Phased Arrayed L-band Synthetic Aperture Radar (PALSAR) data in the 20072010 period for i) discriminating mature forest, non-forest and secondary forest, and ii) retrieving the age of secondary forests (ASF), with 100 m × 100 m training areas obtained by the analysis of an extensive time-series of Landsat sensor data over the three sites. A machine learning algorithm (random forests) was used in combination with ALOS PALSAR backscatter intensity at HH and HV polarizations and Landsat 5 TM surface reflectance in the visible, near-infrared and shortwave infrared spectral regions. Overall accuracy when discriminating mature forest, non-forest and secondary forest is high (9596%), with the highest errors in the secondary forest class (omission and commission errors in the range 46% and 1220% respectively) because of misclassification as mature forest. Root mean square error (RMSE) and bias when retrieving ASF ranged between 4.34.7 years (relative RMSE = 25.532.0%) and 0.040.08 years respectively. On average, unbiased ASF estimates can be obtained using the method proposed here (Wilcoxon test, p-value > 0.05). However, the bias decomposition by 5-year interval ASF classes showed that most age estimates are biased, with consistent overestimation in secondary forests up to 1015 years of age and underestimation in secondary forests of at least 20 years of age. Comparison with the classification results obtained from the analysis of extensive time-series of Landsat sensor data showed a good agreement, with Pearson's coefficient of correlation (R) of the proportion of mature forest, non-forest and secondary forest at 1-km grid cells ranging between 0.970.98, 0.960.98 and 0.840.90 in the 20072010 period, respectively. The agreement was lower (R = 0.820.85) when using the same dataset to compare the ability of ALOS PALSAR and Landsat 5 TM data to retrieve ASF. This was also dependent on the study area, especially when considering mapping secondary forest and retrieving ASF, with Manaus displaying better agreement when compared to the results at Santarém and Machadinho d'Oeste.
ÁreaSRE
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Conteúdo da Pasta agreement
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4. Condições de acesso e uso
Idiomaen
Arquivo Alvocarreiras_mapping.pdf
Grupo de Usuáriossimone
Grupo de Leitoresadministrator
simone
Visibilidadeshown
Política de Arquivamentodenypublisher allowfinaldraft24
Permissão de Leituradeny from all and allow from 150.163
Permissão de Atualizaçãonão transferida
5. Fontes relacionadas
Unidades Imediatamente Superiores8JMKD3MGPCW/3ER446E
Lista de Itens Citando
DivulgaçãoWEBSCI; PORTALCAPES; MGA; COMPENDEX; SCOPUS.
Acervo Hospedeirosid.inpe.br/mtc-m21b/2013/09.26.14.25.20
6. Notas
Campos Vaziosalternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel e-mailaddress format isbn label lineage mark mirrorrepository 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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