LiDAR and PALSAR-Derived Forest Aboveground Biomass, Paragominas, Para, Brazil, 2012

Description

This dataset provides estimates of forest aboveground biomass for three study areas and the entire Paragominas municipality, in Para, Brazil, in 2012. Aboveground biomass (in megagrams of carbon per hectare) was measured for inventory plots within the study (focal) areas, and then assimilated and modeled with LiDAR and PALSAR metrics using gradient boosting machines (GBM) to predict spatially explicit forest aboveground biomass and uncertainties for the entire focal areas. The PALSAR data across the three focal areas was combined and used in a GBM model to predict forest aboveground biomass across the entire Paragominas municipality.

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%2F1648
21 This link allows direct data access via Earthdata login https://daac.ornl.gov/cms/Estimated_Biomass_Stock_Amazon/
21 ORNL DAAC Data Set Documentation https://daac.ornl.gov/CMS/guides/Estimated_Biomass_Stock_Amazon.html
21 Data set Landing Page DOI URL https://doi.org/10.3334/ORNLDAAC/1648
34 Assimilated predictions of forest aboveground biomass (megagrams of carbon per hectare) across the Paragominas Municipality, Brazil. (Source file: paragominas_predicted_agb.tif) https://daac.ornl.gov/CMS/guides/Estimated_Biomass_Stock_Amazon_Fig1.png
33 LiDAR and PALSAR-Derived Forest Aboveground Biomass, Paragominas, Para, Brazil, 2012: Estimated_Biomass_Stock_Amazon.pdf https://data.ornldaac.earthdata.nasa.gov/public/cms/Estimated_Biomass_Stock_Amazon/comp/Estimated_Biomass_Stock_Amazon.pdf
21 This link allows direct data access via Earthdata login https://daac.ornl.gov/daacdata/cms/Estimated_Biomass_Stock_Amazon/data/
57 Collection bundle https://data.ornldaac.earthdata.nasa.gov/protected/bundle/Estimated_Biomass_Stock_Amazon_1648.zip
57 Collection bundle https://data.ornldaac.earthdata.nasa.gov/protected/bundle/Estimated_Biomass_Stock_Amazon_1648.zip

Tags

  • ecosystems
  • biosphere
  • spectral-engineering
  • vegetation
  • lidar
  • earth-science

Topics

Categories