dataforgood-fb-forests.yaml

Name: High Resolution Canopy Height Maps by WRI and Meta
Description: |
  Canopy Height maps for a selection of regions. Created using machine learning models on high-resolution worldwide Maxar satellite imagery. 
Documentation: "[Project overview](https://dataforgood.facebook.com/dfg/docs)"
Contact: dataforgood@meta.com
ManagedBy: "[Meta](https://dataforgood.fb.com/)"
UpdateFrequency: TBD
Tags:
  - aws-pds
  - cog
  - earth observation
  - climate
  - land cover
  - agriculture
  - machine learning
  - aerial imagery
  - satellite imagery
  - image processing
  - geospatial
License: |
  https://creativecommons.org/licenses/by/4.0/
Citation:
  Meta and World Resources Institude (WRI) - 2023. High Resolution
  Canopy Height Maps (CHM). Source imagery for CHM © 2016 [Maxar](https://www.maxar.com/products/imagery-basemaps).
  Accessed DAY MONTH YEAR.
Resources:
  - Description: Cloud-optimized GeoTIFF files and Geojson files with observation date
    ARN: arn:aws:s3:::dataforgood-fb-data/forests/v1/
    Region: us-east-1
    Type: S3 Bucket
DataAtWork:
  Tutorials:
  Tools & Applications:
  Publications:
    - Title: "Every tree counts: Large-scale mapping of canopy height at the resolution of individual trees"
      URL: https://research.facebook.com/blog/2023/4/every-tree-counts-large-scale-mapping-of-canopy-height-at-the-resolution-of-individual-trees/
      AuthorName: Jamie Tolan, Camille Couprie, and Tracy Johns
    - Title: Sub-meter resolution canopy height maps using self-supervised learning and a vision transformer trained on Aerial and GEDI Lidar
      URL: https://doi.org/10.48550/arXiv.2304.07213
      AuthorName: Jamie Tolan, Hung-I Yang, Ben Nosarzewski, Guillaume Couairon, Huy Vo, John Brandt, Justine Spore, Sayantan Majumdar, Daniel Haziza, Janaki Vamaraju, Theo Moutakanni, Piotr Bojanowski, Tracy Johns, Brian White, Tobias Tiecke, Camille Couprie