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1. Identificação
Tipo de ReferênciaArtigo em Revista Científica (Journal Article)
Sitemtc-m21d.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP3W34T/4A63UAB
Repositóriosid.inpe.br/mtc-m21d/2023/11.03.17.21   (acesso restrito)
Última Atualização2023:11.03.17.21.48 (UTC) simone
Repositório de Metadadossid.inpe.br/mtc-m21d/2023/11.03.17.21.48
Última Atualização dos Metadados2024:01.02.17.16.52 (UTC) administrator
DOI10.1016/j.rsase.2023.101074
ISSN2352-9385
Chave de CitaçãoAraújoGalvDala:2023:EvChVe
TítuloEvaluating changes with vegetation cover in PRISMA's spectral, spatial, and temporal attributes and their performance for classifying savannahs in Brazil
Ano2023
MêsNov.
Data de Acesso13 maio 2024
Tipo de Trabalhojournal article
Tipo SecundárioPRE PI
Número de Arquivos1
Tamanho18352 KiB
2. Contextualização
Autor1 Araújo, Juliana de Abreu
2 Galvão, Lênio Soares
3 Dalagnol, Ricardo
Identificador de Curriculo1
2 8JMKD3MGP5W/3C9JHLF
Grupo1 SER-SRE-DIPGR-INPE-MCTI-GOV-BR
2 DIOTG-CGCT-INPE-MCTI-GOV-BR
Afiliação1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 University of California Los Angeles (UCLA)
Endereço de e-Mail do Autor1 juliana.araujo@inpe.br
2 lenio.galvao@inpe.br
RevistaRemote Sensing Applications: Society and Environment
Volume32
Páginase101074
Histórico (UTC)2023-11-03 17:22:03 :: simone -> administrator :: 2023
2024-01-02 17:16:52 :: administrator -> simone :: 2023
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-ChaveAbsorption bands
Brasília National Park
Cerrado
Hyperspectral remote sensing
Reflectance
Vegetation indices
ResumoThe recent advent of hyperspectral satellites with larger swath width than that of previous sampling missions brings new perspectives for mapping savannahs in Brazil. Here, we evaluated changes with vegetation cover in different spectral, spatial, and temporal attributes, derived from the PRecursore IperSpettrale della Missione Applicativa (PRISMA), and their performance for Random Forest (RF) classification of savannah physiognomies at the Brasília National Park (BNP). To obtain the spectral attributes, we selected a PRISMA image acquired during the local dry season (August 17, 2020). We evaluated the classification performance of the reflectance of 166 bands, 22 vegetation indices (VIs), and four endmember fractions derived from a linear spectral mixture model (SMA). In addition, 24 parameters describing the depth, area, width, and asymmetry of the absorption bands centred at 680 nm (chlorophyll), 980 nm and 1200 nm (leaf water), and 1750 nm, 2100 nm and 2300 nm (lignin-cellulose) were also considered in the analysis. For the spatial attributes, we tested the performance of 8 Gray Level Co-occurrence Matrix (GLCM) metrics of image texture associated with the 864-nm near-infrared (NIR) band. In order to determine the temporal attributes, we considered other three PRISMA images obtained in 2020 (11 May, 4 September, and 3 October). Using these images, we calculated the rate of changes for each of the 22 VIs in the browning and greening periods of the savannah environment. A feature selection procedure was applied to the datasets. The results showed that the vegetation gradient from savannah grassland to woodland areas controlled the behavior of most attributes. For instance, the reflectance of the PRISMA NIR bands and the depth of the chlorophyll (680 nm) and leaf water (980 nm and 1200 nm) absorption bands increased with increasing vegetation cover. On the other hand, the reflectance of the visible and shortwave infrared (SWIR) bands and the depth of spectral features associated with non-photosynthetic vegetation followed the opposite pattern. Except for the metrics of image texture, the other spectral (reflectance, VIs, endmember fractions, and absorption band parameters) and temporal (browning and greening rates of vegetation changes) attributes had close classification performance before or after feature selection. When combined into a single dataset, gains of 15% in overall classification accuracy were observed when compared to the individual use of reflectance data in the analysis. From the seven savannah classes tested for classification, areas of woodland savannah, savannah grassland, and riparian forest were adequately mapped using this approach (F1-scores between 0.72 and 0.91). In contrast, areas of wooded savannah, with and without Trembleias species, had low F1-scores (0.28 and 0.20, respectively). Our findings reinforce the need of considering different hyperspectral attributes in classification approaches of the savannahs in Brazil.
ÁreaSRE
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4. Condições de acesso e uso
Idiomaen
Arquivo Alvo1-s2.0-S2352938523001568-main.pdf
Grupo de Usuáriossimone
Grupo de Leitoresadministrator
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Visibilidadeshown
Permissão de Leituradeny from all and allow from 150.163
Permissão de Atualizaçãonão transferida
5. Fontes relacionadas
Unidades Imediatamente Superiores8JMKD3MGPCW/3F3NU5S
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Lista de Itens Citandosid.inpe.br/mtc-m21/2012/07.13.14.53.28 2
DivulgaçãoPORTALCAPES; SCOPUS.
Acervo Hospedeirourlib.net/www/2021/06.04.03.40
6. Notas
Campos Vaziosalternatejournal archivingpolicy 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 secondarymark session shorttitle sponsor subject tertiarymark tertiarytype url
7. Controle da descrição
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