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Data attribution

World Resources Institute (WRI) is the source of the datasets LUC Analytics reads. The reference point for them is WRI's Data Explorer page, GNW Self-Hosted Monitoring. WRI's S3 bucket (s3://gnw-monitoring-data) is publicly accessible to anyone who accepts Requester Pays. It is not free to access: every request and every byte transferred is billed to the requester's own AWS account.

LUC Analytics contains no datasets. At run time it reads the datasets that WRI hosts for Global Nature Watch (GNW), as listed in WRI's published manifest (s3://gnw-monitoring-data/post2020-manifest.json; a pinned copy is in third_party/gnw-self-hosted-monitoring/manifests/). Each dataset keeps its own license.

When LUC Analytics reads WRI data, you are bound by WRI's Special Terms of Use for GNW Self-Hosted Monitoring. In particular, you must attribute the data in the form below, and you may not suggest that WRI endorses, sponsors, certifies or approves you or your use of the data.

Licenses, in short:

  • CC BY 4.0: all datasets below, except the two that follow.
  • JRC Global Forest Cover 2020: free of charge, without restriction of use, under the Copernicus Regulation of the European Commission.
  • LandMark (Indigenous and Community Lands): a separate agreement with the provider is required. LUC Analytics leaves LandMark off by default (see the README).

LUC Analytics adds this attribution to every CSV export and PDF report, with the access date filled in, and shows it in the app's "Data sources" panel. The single source for that text is app/results/attribution.py.

The text below is copied from WRI's page "Post-2020 Forest Loss & Alerts for SHM - Attribution" (SHM Datasets and Attributions), version dated Aug 25, 2026. Check that page for the current wording.

Attribution

Data sourced or extracted from the Zarr files must be attributed in accordance with WRI Terms of Use. This requirement encompasses all forms of sharing, including digital, printed paper, or photographic mediums, as well as derivative works or adaptations that build on the content obtained from GNW.

When providing attribution, lead with the citation format below for Global Nature Watch (GNW) and append on separate lines relevant citations for the datasets below that require explicit attribution when present in outputs or incorporated into derivative works to be shared with other parties.

GNW

  • "Global Nature Watch. [Current Year]. World Resources Institute. Accessed on (date)."

Datasets

Dominant Drivers of Forest Loss

  • Source:
  • Land and Carbon Lab
  • Website: WRI/Google DeepMind Global Drivers of Forest Loss 2001-2025 v1.3
  • DOI 10.1088/1748-9326/add606 Global drivers of forest loss at 1 km resolution
  • Dataset License: CC BY 4.0
  • GFW Pro Edition License: CC BY 4.0
  • Citation: Sims, M.J., R. Stanimirova, A. Raichuk, M. Neumann, J. Richter, F. Follett, J. MacCarthy, K. Lister, C. Randle, L. Sloat, E. Esipova, J. Jupiter, C. Stanton, D. Morris, C.M. Slay, D. Purves, and N. Harris. 2025. "Global Drivers of Forest Loss at 1 Km Resolution." Environmental Research Letters 20 (7): 074027. doi:10.1088/1748-9326/add606

Global Integrated Disturbance Alerts

  • Source:
  • Global Nature Watch / Land and Carbon Lab
  • Website: Global Nature Watch
  • Dataset License: CC BY 4.0
  • GFW Pro Edition License: CC BY 4.0
  • Citation(s):
  • Integrated Alerts:
    • Reiche, J., J. Balling, A.H. Pickens, R.N. Masolele, A. Berger, M.J. Weisse, D. Mannarino, Y. Gou, B. Slagter, G. Donchyts, and S. Carter. 2024. "Integrating satellite-based forest disturbance alerts improves detection timeliness and confidence." Environmental Research Letters 19 (5): 054011.
  • GLAD-L:
    • Hansen, M.C., A. Krylov, A. Tyukavina, P.V. Potapov, S. Turubanova, B. Zutta, S. Ifo, B. Margono, F. Stolle, and R. Moore. 2016. "Humid tropical forest disturbance alerts using Landsat data." Environmental Research Letters 11 (3): 034008.
  • GLAD-S2:
    • Weisse, M., A. Berger, J. Webb, and A. Pickens. 2021. "Higher Resolution Alerts Offer More Detailed Picture of Forest Loss." Global Forest Watch (blog), May 12, 2021.
  • RADD:
    • Citation: Reiche, J., A. Mullissa, B. Slagter, Y. Gou, N.-E. Tsendbazar, C. Odongo-Braun, A. Vollrath, M.J. Weisse, F. Stolle, A. Pickens, G. Donchyts, N. Clinton, N. Gorelick, and M. Herold. 2021. "Forest disturbance alerts for the Congo Basin using Sentinel-1." Environmental Research Letters 16 (2): 024005.
  • DIST-ALERT:
    • Hansen, M. 2024. "OPERA Land Surface Disturbance Alert from Harmonized Landsat Sentinel-2 product (Version 1)." NASA Land Processes Distributed Active Archive Center. https://doi.org/10.5067/SNWG/OPERA_L3_DIST-ALERT-HLS_V1.001 .
    • Pickens, A.H., M.C. Hansen, Z. Song, A. Poulson, A. Komarova, A. Baggett, T. Kerr, A. Mikus, C. Ortiz Dominguez, A. Tyukavina, and A. Lima. 2025. "Rapid monitoring of global land change." Nature Communications 16 (1): 8948. https://doi.org/10.1038/s41467-025-64014-9.

Indigenous and Community Lands (Selective Access)

  • Source:
  • Landmark Indigenous and Community Lands – World Resources Institute
  • Website: https://www.landmarkmap.org/
  • Dataset License: https://www.landmarkmap.org/terms-of-use/
  • GFW Pro Edition License: Separate agreement with provider.
  • Citation: LandMark. "LandMark: The Global Platform of Indigenous and Community Lands." https://www.landmarkmap.org/.

JRC Global Forest Cover 2020

  • Source:
  • Joint Research Center, EU Forest Observatory
  • Website: https://forobs.jrc.ec.europa.eu/GFC
  • Dataset License: All data are provided free-of-charge, without restriction of use per Global forest cover 2020 - Data Access and the Copernicus Regulation of the European Commission.
  • GFW Pro Edition License: Pass through of the JRC License.
  • Citation: Bourgoin, C., A. Verhegghen, S. Carboni, I. Ameztoy, L. Degreve, S. Fritz, M. Herold, N. Tsendbazar, M. Lesiv, F. Achard, and R. Colditz. 2026. "GFC2020: a global map of forest land use for year 2020 to support the EU Deforestation Regulation." Earth System Science Data 18 (2): 1331-1365. https://doi.org/10.5194/essd-18-1331-2026.

SBTN Natural Forest

  • Source:
  • Science Based Targets Network (SBTN), World Resources Institute (WRI)
  • Website: SBTN Natural Lands
  • Dataset License: CC BY 4.0
  • GFW Pro Edition License: CC BY 4.0
  • Citation: Mazur, E., M. Sims, E. Goldman, M. Schneider, M. Daldoss Pirri, C.R. Beatty, F. Stolle, and M. Stevenson.
  • "Natural Lands Map – Technical Documentation Version 1.1." Science Based Targets Network. https://sciencebasedtargetsnetwork.org/wp-content/uploads/2025/02/Technical-Guidance-2025-Step3-Land-v1_1-Natural-Lands-Map.pdf.

Tree cover loss

  • Source:
  • University of Maryland (UMD) Global Land Analysis and Discovery (GLAD) Lab
  • Website: Global Forest Change
  • Dataset License: CC BY 4.0
  • GFW Open Data Portal: http://data.globalforestwatch.org/datasets/tree-cover-loss-hansen-umd-google-usgs-nasa
  • GFW Pro Edition License: CC BY 4.0
  • Citation: Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. "High- Resolution Global Maps of 21st-Century Forest Cover Change." Science 342 (15 November): 850–53.

Other data in this repository

  • app/ingest/assets/ne_10m_land.geojson: simplified land polygons derived from Natural Earth 1:10m Land (naturalearthdata.com), which is in the public domain.
  • Test and demo data are synthetic (generated for this project).