LiDAR survey on 500 hectares in Humaitá, Porto Acre, Acre, Brasil in 2013.
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , |
Tipo de documento: | Conjunto de dados |
Título da fonte: | Repositório de Dados de Pesquisa da EMBRAPA (Redape) |
Texto Completo: | https://doi.org/10.48432/JJM3DO |
Resumo: | The LiDAR data Humaitá (HUM_A01_2013_LiDAR) refers to the survey carried out in Porto Acre municipality, Acre state, Brazil. The data were collected under the project Sustainable Landscapes, a project supported by the United States Agency for International Development (USAID) and US Department of State. The United States Forest Service working in collaboration with the Brazilian Agricultural Research Corporation (Embrapa) have made possible the provision of high accuracy LiDAR data aiming at developing new methods and generating knowledge in the field. This dataset contains: a. Classified LAS formatted point cloud data – compressed LAS files: LAZ format (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State." |
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doi:10.48432/JJM3DO |
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Repositório de Dados de Pesquisa da EMBRAPA (Redape) |
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https://doi.org/10.48432/JJM3DOKeller, MichaelSantos, Maiza Nara dosBatistella, MateusLiDAR survey on 500 hectares in Humaitá, Porto Acre, Acre, Brasil in 2013.LiDAR data set "Humaitá" - HUM_A01_2013_LiDARRedapeThe LiDAR data Humaitá (HUM_A01_2013_LiDAR) refers to the survey carried out in Porto Acre municipality, Acre state, Brazil. The data were collected under the project Sustainable Landscapes, a project supported by the United States Agency for International Development (USAID) and US Department of State. The United States Forest Service working in collaboration with the Brazilian Agricultural Research Corporation (Embrapa) have made possible the provision of high accuracy LiDAR data aiming at developing new methods and generating knowledge in the field. This dataset contains: a. Classified LAS formatted point cloud data – compressed LAS files: LAZ format (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."Os dados LiDAR Humaitá (HUM_A01_2013_LiDAR) referem-se ao levantamento realizado no município de Porto Acre, estado do Acre, Brasil. Os dados foram coletados no âmbito do projeto Paisagens Sustentáveis, um projeto apoiado pela Agência dos Estados Unidos para o Desenvolvimento Internacional (USAID) e Departamento de Estado dos EUA. O Serviço Florestal dos Estados Unidos trabalhando em colaboração com a Empresa Brasileira de Pesquisa Agropecuária (Embrapa) tornou possível o fornecimento de dados LiDAR de alta precisão com o objetivo de desenvolver novos métodos e gerar conhecimento no campo. Este conjunto de dados contém: a. Dados de nuvem de pontos formatados em LAS classificados – arquivos LAS compactados: formato LAZ (entregue pelo fornecedor); b. Modelo Digital de Terreno (entregue pelo fornecedor); c. Mapa da área de cobertura LiDAR e limites dos blocos; “Os dados foram adquiridos pelo projeto Paisagens Sustentáveis Brasil, apoiado pela Empresa Brasileira de Pesquisa Agropecuária (Embrapa), Serviço Florestal dos EUA, USAID e Departamento de Estado dos EUA.”2023-03-17info:eu-repo/semantics/openAccesshttps://www.redape.dados.embrapa.br/licenses/embrapa-by-nc-4.0.xhtmlAgricultural SciencesEarth and Environmental Sciencesremote sensingforest coverforest degradationLIDARsistema de informação geográficacobertura florestalland environmentinfo:eu-repo/semantics/datasetinfo:eu-repo/semantics/datasetinfo:eu-repo/semantics/publishedVersionDatasetreponame:Repositório de Dados de Pesquisa da EMBRAPA (Redape)instname:EMBRAPAinstacron:EMBRAPARepositório de Dados de PesquisaPUBhttps://www.redape.dados.embrapa.br/oaiopendoar:2023-03-18T05:00:01Repositório de Dados de Pesquisa da EMBRAPA (Redape) - EMBRAPAfalsedoi:10.48432/JJM3DO |
dc.title.none.fl_str_mv |
LiDAR survey on 500 hectares in Humaitá, Porto Acre, Acre, Brasil in 2013. LiDAR data set "Humaitá" - HUM_A01_2013_LiDAR |
title |
LiDAR survey on 500 hectares in Humaitá, Porto Acre, Acre, Brasil in 2013. |
spellingShingle |
LiDAR survey on 500 hectares in Humaitá, Porto Acre, Acre, Brasil in 2013. Keller, Michael Agricultural Sciences Earth and Environmental Sciences remote sensing forest cover forest degradation LIDAR sistema de informação geográfica cobertura florestal land environment |
title_short |
LiDAR survey on 500 hectares in Humaitá, Porto Acre, Acre, Brasil in 2013. |
title_full |
LiDAR survey on 500 hectares in Humaitá, Porto Acre, Acre, Brasil in 2013. |
title_fullStr |
LiDAR survey on 500 hectares in Humaitá, Porto Acre, Acre, Brasil in 2013. |
title_full_unstemmed |
LiDAR survey on 500 hectares in Humaitá, Porto Acre, Acre, Brasil in 2013. |
title_sort |
LiDAR survey on 500 hectares in Humaitá, Porto Acre, Acre, Brasil in 2013. |
author |
Keller, Michael |
author_facet |
Keller, Michael Santos, Maiza Nara dos Batistella, Mateus |
author_role |
author |
author2 |
Santos, Maiza Nara dos Batistella, Mateus |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Keller, Michael Santos, Maiza Nara dos Batistella, Mateus |
dc.subject.none.fl_str_mv |
Agricultural Sciences Earth and Environmental Sciences remote sensing forest cover forest degradation LIDAR sistema de informação geográfica cobertura florestal land environment |
topic |
Agricultural Sciences Earth and Environmental Sciences remote sensing forest cover forest degradation LIDAR sistema de informação geográfica cobertura florestal land environment |
description |
The LiDAR data Humaitá (HUM_A01_2013_LiDAR) refers to the survey carried out in Porto Acre municipality, Acre state, Brazil. The data were collected under the project Sustainable Landscapes, a project supported by the United States Agency for International Development (USAID) and US Department of State. The United States Forest Service working in collaboration with the Brazilian Agricultural Research Corporation (Embrapa) have made possible the provision of high accuracy LiDAR data aiming at developing new methods and generating knowledge in the field. This dataset contains: a. Classified LAS formatted point cloud data – compressed LAS files: LAZ format (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State." |
publishDate |
2023 |
dc.date.issued.fl_str_mv |
2023-03-17 |
dc.type.openaire.fl_str_mv |
info:eu-repo/semantics/dataset |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.none.fl_str_mv |
info:eu-repo/semantics/dataset |
format |
dataset |
status_str |
publishedVersion |
dc.identifier.url.fl_str_mv |
https://doi.org/10.48432/JJM3DO |
url |
https://doi.org/10.48432/JJM3DO |
dc.rights.openaire.fl_str_mv |
info:eu-repo/semantics/openAccess https://www.redape.dados.embrapa.br/licenses/embrapa-by-nc-4.0.xhtml |
eu_rights_str_mv |
openAccess |
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https://www.redape.dados.embrapa.br/licenses/embrapa-by-nc-4.0.xhtml |
dc.format.none.fl_str_mv |
Dataset |
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Redape |
publisher.none.fl_str_mv |
Redape |
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reponame:Repositório de Dados de Pesquisa da EMBRAPA (Redape) instname:EMBRAPA instacron:EMBRAPA |
instname_str |
EMBRAPA |
instacron_str |
EMBRAPA |
institution |
EMBRAPA |
reponame_str |
Repositório de Dados de Pesquisa da EMBRAPA (Redape) |
collection |
Repositório de Dados de Pesquisa da EMBRAPA (Redape) |
repository.name.fl_str_mv |
Repositório de Dados de Pesquisa da EMBRAPA (Redape) - EMBRAPA |
repository.mail.fl_str_mv |
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_version_ |
1767415553250557952 |