LiDAR Surveys over Selected Forest Research Sites, Brazilian Amazon, 2008-2018

Description

This dataset provides the complete catalog of point cloud data collected during LiDAR surveys over selected forest research sites across the Amazon rainforest in Brazil between 2008 and 2018 for the Sustainable Landscapes Brazil Project. Flight lines were selected to overfly key field research sites in the Brazilian states of Acre, Amazonas, Bahia, Goias, Mato Grosso, Para, Rondonia, Santa Catarina, and Sao Paulo. The point clouds have been georeferenced, noise-filtered, and corrected for misalignment of overlapping flight lines. They are provided in 1 km2 tiles. The data were collected to measure forest canopy structure across Amazonian landscapes to monitor the effects of selective logging on forest biomass and carbon balance, and forest recovery over time.

Resources

Name Format Description Link
21 Search results for publications that cite this dataset by its DOI. https://scholar.google.com/scholar?q=10.3334%2FORNLDAAC%2F1644
21 This link allows direct data access via Earthdata login https://daac.ornl.gov/daacdata/cms/LiDAR_Forest_Inventory_Brazil/
21 ORNL DAAC Data Set Documentation https://daac.ornl.gov/CMS/guides/LiDAR_Forest_Inventory_Brazil.html
21 Data set Landing Page DOI URL https://doi.org/10.3334/ORNLDAAC/1644
21 This link allows direct data access via Earthdata login https://daac.ornl.gov/daacdata/cms/LiDAR_Forest_Inventory_Brazil/data/
33 LiDAR Surveys over Selected Forest Research Sites, Brazilian Amazon, 2008-2018: LiDAR_Forest_Inventory_Brazil.pdf https://data.ornldaac.earthdata.nasa.gov/public/cms/LiDAR_Forest_Inventory_Brazil/comp/LiDAR_Forest_Inventory_Brazil.pdf
22 Bounding boxes for LiDAR tiles from surveys over western Para, Brazil are depicted in Google Earth from the KMZ file. Each feature in the KMZ provides key metadata about the corresponding tile. Source: cms_brazil_lidar_tile_inventory.kmz https://daac.ornl.gov/CMS/guides/LiDAR_Forest_Inventory_Brazil_Fig1.jpg

Tags

  • topography
  • land-surface
  • biosphere
  • spectral-engineering
  • vegetation
  • lidar
  • earth-science

Topics

Categories