LiDAR survey on 209.7 hectares in Feliz Natal IV, Mato Grosso, Brasil in 2017

The LiDAR data Feliz Natal municipality - IV (FND_A01_2017_LiDAR) refers to the survey carried out in the Feliz Natal municipality, Mato Grosso 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 (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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Bibliographic Details
Main Authors: Santos, Maiza Nara dos, Keller, Michael, Batistella, Mateus
Other Authors: Bolfe, Victória
Format: LiDAR data biblioteca
Language:English
Published: Redape 2017
Subjects:Agricultural Sciences, Earth and Environmental Sciences, remote sensing, forest degradation, forest cover, LIDAR, sistema de informação geográfica, cobertura florestal,
Online Access:https://doi.org/10.48432/SLULIX
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spelling dat-redape-br-10.48432SLULIX2023-03-17T05:00:01ZLiDAR survey on 209.7 hectares in Feliz Natal IV, Mato Grosso, Brasil in 2017https://doi.org/10.48432/SLULIXSantos, Maiza Nara dosKeller, MichaelBatistella, MateusRedapeThe LiDAR data Feliz Natal municipality - IV (FND_A01_2017_LiDAR) refers to the survey carried out in the Feliz Natal municipality, Mato Grosso 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 (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 do município de Feliz Natal - IV (FND_A01_2017_LiDAR) referem-se ao levantamento realizado no município de Feliz Natal, Mato Grosso, 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 classificados de nuvem de pontos formatados em LAS (entregues 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.”Agricultural SciencesEarth and Environmental Sciencesremote sensingforest degradationforest coverLIDARsistema de informação geográficacobertura florestalEnglish2017-04-12Bolfe, VictóriaDrucker, Debora PignatariDrucker, Debora PignatariVictoria, Daniel de CastroMorton, DouglasPinagé, Ekena RangelVictoria, Daniel de CastroLiDAR dataDados geoespaciais
institution EMBRAPA
collection Dataverse
country Brasil
countrycode BR
component Datos de investigación
access En linea
En linea
databasecode dat-redape-br
tag biblioteca
region America del Sur
libraryname Sistema de bibliotecas de EMBRAPA
language English
topic Agricultural Sciences
Earth and Environmental Sciences
remote sensing
forest degradation
forest cover
LIDAR
sistema de informação geográfica
cobertura florestal
Agricultural Sciences
Earth and Environmental Sciences
remote sensing
forest degradation
forest cover
LIDAR
sistema de informação geográfica
cobertura florestal
spellingShingle Agricultural Sciences
Earth and Environmental Sciences
remote sensing
forest degradation
forest cover
LIDAR
sistema de informação geográfica
cobertura florestal
Agricultural Sciences
Earth and Environmental Sciences
remote sensing
forest degradation
forest cover
LIDAR
sistema de informação geográfica
cobertura florestal
Santos, Maiza Nara dos
Keller, Michael
Batistella, Mateus
LiDAR survey on 209.7 hectares in Feliz Natal IV, Mato Grosso, Brasil in 2017
description The LiDAR data Feliz Natal municipality - IV (FND_A01_2017_LiDAR) refers to the survey carried out in the Feliz Natal municipality, Mato Grosso 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 (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."
author2 Bolfe, Victória
author_facet Bolfe, Victória
Santos, Maiza Nara dos
Keller, Michael
Batistella, Mateus
format LiDAR data
topic_facet Agricultural Sciences
Earth and Environmental Sciences
remote sensing
forest degradation
forest cover
LIDAR
sistema de informação geográfica
cobertura florestal
author Santos, Maiza Nara dos
Keller, Michael
Batistella, Mateus
author_sort Santos, Maiza Nara dos
title LiDAR survey on 209.7 hectares in Feliz Natal IV, Mato Grosso, Brasil in 2017
title_short LiDAR survey on 209.7 hectares in Feliz Natal IV, Mato Grosso, Brasil in 2017
title_full LiDAR survey on 209.7 hectares in Feliz Natal IV, Mato Grosso, Brasil in 2017
title_fullStr LiDAR survey on 209.7 hectares in Feliz Natal IV, Mato Grosso, Brasil in 2017
title_full_unstemmed LiDAR survey on 209.7 hectares in Feliz Natal IV, Mato Grosso, Brasil in 2017
title_sort lidar survey on 209.7 hectares in feliz natal iv, mato grosso, brasil in 2017
publisher Redape
publishDate 2017
url https://doi.org/10.48432/SLULIX
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