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1. Identificação
Tipo de ReferênciaArtigo em Evento (Conference Proceedings)
Siteplutao.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP3W/3KN2JCL
Repositóriosid.inpe.br/plutao/2015/12.04.11.18
Última Atualização2015:12.11.12.45.12 (UTC) simone
Repositório de Metadadossid.inpe.br/plutao/2015/12.04.11.18.22
Última Atualização dos Metadados2018:06.04.23.25.41 (UTC) administrator
DOI10.5194/isprsarchives-XL-3-W3-473-2015
ISBN16821750
Rótulolattes: 9686528152912455 1 FerreiraZoZaFéShSo:2015:UsShIn
Chave de CitaçãoFerreiraZoZaFéShSo:2015:UsShIn
TítuloOn the use of shortwave infrared for tree species discrimination in tropical semideciduous forest
Ano2015
Data de Acesso09 maio 2024
Tipo SecundárioPRE CI
Número de Arquivos1
Tamanho528 KiB
2. Contextualização
Autor1 Ferreira, Matheus Pinheiro
2 Zortea, Maciel
3 Zanotta, Daniel Capella
4 Féret, Jean-Baptiste
5 Shimabukuro, Yosio Edemir
6 Souza Filho, Carlos Roberto de
Identificador de Curriculo1
2
3
4
5 8JMKD3MGP5W/3C9JJCQ
Grupo1 SER-SRE-SPG-INPE-MCTI-GOV-BR
2
3
4
5 DSR-OBT-INPE-MCTI-GOV-BR
Afiliação1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Institute of Informatics, Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
3 Institute for Education Science and Technology, Rio Grande, Brazil
4 Territoires, Environnement, Teledetection et Information Spatiale, Montpellier, France
5 Instituto Nacional de Pesquisas Espaciais (INPE)
6 Universidade Estadual de Campinas, Institute of Geosciences, Campinas, Brazil
Endereço de e-Mail do Autor1 mpf@dsr.inpe.br
2 mzortea@gmail.com
3 daniel.zanotta@riogrande.ifrs.edu.br
4 jb.feret@teledetection.fr
5 yosio@ltid.inpe.br
6 beto@ige.unicamp.br
EditorN. , Paparoditis
A. -M. , Raimond
G. , Sithole
G. , Rabatel
A. , Coltekin
F. , Rottensteiner
X. , Briottet
S. , Christophe
I. , Dowman
S. O. , Elberink
G. , Patane
C. , Mallet
Nome do EventoInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Archives)
Localização do EventoLa grande Motte, France
Data28 Sept. - 02 Oct.
Volume40
Páginas473-476
Título do LivroProceedings
Tipo TerciárioArtigo
OrganizaçãoInternational Society for Photogrammetry and Remote Sensing
Histórico (UTC)2015-12-04 11:18:22 :: lattes -> administrator ::
2016-06-04 01:09:09 :: administrator -> simone :: 2015
2016-08-19 16:41:42 :: simone -> administrator :: 2015
2018-06-04 23:25:41 :: administrator -> simone :: 2015
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-ChaveHyperspectral remote sensing
tropical forests
classification
ResumoTree species mapping in tropical forests provides valuable insights for forest managers. Keystone species can be located for collection of seeds for forest restoration, reducing fieldwork costs. However, mapping of tree species in tropical forests using remote sensing data is a challenge due to high floristic and spectral diversity. Little is known about the use of different spectral regions as most of studies performed so far used visible/near-infrared (390-1000 nm) features. In this paper we show the contribution of shortwave infrared (SWIR, 1045-2395 nm) for tree species discrimination in a tropical semideciduous forest. Using high-resolution hyperspectral data we also simulated WorldView-3 (WV-3) multispectral bands for classification purposes. Three machine learning methods were tested to discriminate species at the pixel-level: Linear Discriminant Analysis (LDA), Support Vector Machines with Linear (L-SVM) and Radial Basis Function (RBF-SVM) kernels, and Random Forest (RF). Experiments were performed using all and selected features from the VNIR individually and combined with SWIR. Feature selection was applied to evaluate the effects of dimensionality reduction and identify potential wavelengths that may optimize species discrimination. Using VNIR hyperspectral bands, RBF-SVM achieved the highest average accuracy (77.4%). Inclusion of the SWIR increased accuracy to 85% with LDA. The same pattern was also observed when WV-3 simulated channels were used to classify the species. The VNIR bands provided and accuracy of 64.2% for LDA, which was increased to 79.8 % using the new SWIR bands that are operationally available in this platform. Results show that incorporating SWIR bands increased significantly average accuracy for both the hyperspectral data and WorldView-3 simulated bands.
ÁreaSRE
Arranjo 1urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > On the use...
Arranjo 2urlib.net > BDMCI > Fonds > Produção pgr ATUAIS > SER > On the use...
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/8JMKD3MGP3W/3KN2JCL
URL dos dados zipadoshttp://urlib.net/zip/8JMKD3MGP3W/3KN2JCL
Idiomapt
Arquivo Alvo1_ferreira.pdf
Grupo de Usuárioslattes
simone
Grupo de Leitoresadministrator
simone
Visibilidadeshown
Permissão de Leituraallow from all
Permissão de Atualizaçãonão transferida
5. Fontes relacionadas
Repositório Espelhourlib.net/www/2011/03.29.20.55
Unidades Imediatamente Superiores8JMKD3MGPCW/3ER446E
8JMKD3MGPCW/3F3NU5S
URL (dados não confiáveis)http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-3-W3/473/2015/isprsarchives-XL-3-W3-473-2015.pdf
Acervo Hospedeirodpi.inpe.br/plutao@80/2008/08.19.15.01
6. Notas
Campos Vaziosarchivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel dissemination e-mailaddress edition format issn lineage mark nextedition notes numberofvolumes orcid parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress rightsholder schedulinginformation secondarydate secondarykey secondarymark serieseditor session shorttitle sponsor subject tertiarymark type
7. Controle da descrição
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