Resultado da Pesquisa
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1 referência encontrada buscando em 17 dentre 17 Arquivos.
Data e hora local de busca: 19/04/2024 05:59.
1. Identificação
Tipo de ReferênciaArtigo em Evento (Conference Proceedings)
Sitemtc-m21b.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP3W34P/3Q9K3GE
Repositóriosid.inpe.br/mtc-m21b/2017/12.27.15.11
Última Atualização2021:02.19.12.46.33 (UTC) simone
Repositório de Metadadossid.inpe.br/mtc-m21b/2017/12.27.15.11.56
Última Atualização dos Metadados2022:03.18.22.12.28 (UTC) administrator
Chave SecundáriaINPE--PRE/
Chave de CitaçãoJorgeShimSantGasp:2017:InTrDe
TítuloIndividual tree detection in intact forest and degraded forest areas in the north region of Mato Grosso State, Brazilian Amazon
Ano2017
Data de Acesso19 abr. 2024
Tipo SecundárioPRE CI
Número de Arquivos1
Tamanho71 KiB
2. Contextualização
Autor1 Jorge, Anderson Alex
2 Shimabukuro, Yosio Edemir
3 Santos, Erone Ghizoni
4 Gasparini, Kaio
Identificador de Curriculo1
2 8JMKD3MGP5W/3C9JJCQ
Grupo1 SESOF-COADM-INPE-MCTIC-GOV-BR
2 DIDSR-CGOBT-INPE-MCTIC-GOV-BR
3 SER-SRE-SESPG-INPE-MCTIC-GOV-BR
4 SER-SRE-SESPG-INPE-MCTIC-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)
Endereço de e-Mail do Autor1 anderson.jorge_bsservices@inpe.br
2 yosio.shimabukuro@inpe.br
Nome do EventoAGU Fall Meeting
Localização do EventoNew Orleans
Data11-15 Dec.
Título do LivroProceedings
Histórico (UTC)2017-12-27 15:11:56 :: simone -> administrator ::
2018-06-04 02:28:10 :: administrator -> simone :: 2017
2021-02-19 12:46:34 :: simone -> administrator :: 2017
2022-03-18 22:12:28 :: 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
ResumoThe State of Mato Grosso - MT has the second largest area with degraded forest among the states of the Brazilian Legal Amazon. Land use and land cover change processes that occur in this region cause the loss of forest biomass, releasing greenhouse gases that contribute to the increase of temperature on earth. These degraded forest areas lose biomass according to the intensity and magnitude of the degradation type. The estimate of forest biomass, commonly performed by forest inventory through sample plots, shows high variance in degraded forest areas. Due to this variance and complexity of tropical forests, the aim of this work was to estimate forest biomass using LiDAR point clouds in three distinct forest areas: one degraded by fire, another by selective logging and one area of intact forest. The approach applied in these areas was the Individual Tree Detection (ITD). To isolate the trees, we generated Canopy Height Models (CHM) images, which are obtained by subtracting the Digital Elevation Model (MDE) and the Digital Terrain Model (MDT), created by the cloud of LiDAR points. The trees in the CHM images are isolated by an algorithm provided by the Quantitative Ecology research group at the School of Forestry at Northern Arizona University (SILVA, 2015). With these points, metrics were calculated for some areas, which were used in the model of biomass estimation. The methodology used in this work was expected to reduce the error in biomass estimate in the study area. The cloud points of the most representative trees were analyzed, and thus field data was correlated with the individual trees found by the proposed algorithm. In a pilot study, the proposed methodology was applied generating the individual tree metrics: total height and area of the crown. When correlating 339 isolated trees, an unsatisfactory R² was obtained, as heights found by the algorithm were lower than those obtained in the field, with an average difference of 2.43 m. This shows that the algorithm used to isolate trees in temperate areas did not obtained satisfactory results in the tropical forest of Mato Grosso State. Due to this, in future works two algorithms, one developed by Dalponte et al. (2015) and another by Li et al. (2012) will be used.
ÁreaSRE
Arranjo 1urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > Individual tree detection...
Arranjo 2urlib.net > BDMCI > Fonds > Produção pgr ATUAIS > SER > Individual tree detection...
Arranjo 3urlib.net > BDMCI > Fonds > Produção anterior à 2021 > SESOF > Individual tree detection...
Conteúdo da Pasta docacessar
Conteúdo da Pasta sourcenão têm arquivos
Conteúdo da Pasta agreement
agreement.html 27/12/2017 13:11 1.0 KiB 
4. Condições de acesso e uso
URL dos dadoshttp://urlib.net/ibi/8JMKD3MGP3W34P/3Q9K3GE
URL dos dados zipadoshttp://urlib.net/zip/8JMKD3MGP3W34P/3Q9K3GE
Idiomaen
Arquivo Alvojorge_individual.pdf
Grupo de Usuáriossimone
Grupo de Leitoresadministrator
simone
Visibilidadeshown
Permissão de Atualizaçãonão transferida
5. Fontes relacionadas
Repositório Espelhosid.inpe.br/mtc-m21b/2013/09.26.14.25.22
Unidades Imediatamente Superiores8JMKD3MGPCW/3ER446E
8JMKD3MGPCW/3F3NU5S
8JMKD3MGPCW/3F3TG4S
Lista de Itens Citandosid.inpe.br/bibdigital@80/2006/04.07.15.50.13 1
Acervo Hospedeirosid.inpe.br/mtc-m21b/2013/09.26.14.25.20
6. Notas
Campos Vaziosarchivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel dissemination doi e-mailaddress edition editor format isbn issn keywords label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress readpermission rightsholder schedulinginformation secondarydate secondarymark serieseditor session shorttitle sponsor subject tertiarymark tertiarytype type url volume
7. Controle da descrição
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