Data Sources & Attribution

CommodityMap uses publicly available datasets. Discovery the source and attribution of each of these datasets below.


Spatial Agricultural Production Models

These models are used by CommodityMap to identify where agricultural crops are produced.

Category Descripton Dataset name Attribution License
Argricultural Production Data (USA) USDA-NASS Cropland Data Layer (CDL) is an annual raster, geo-referenced, crop-specific land cover data layer. Year: 2022 USDA Cropland Data Layer Originator: United States Department of Agriculture (USDA) National Agricultural Statistics Service (NASS) Publication_Date: 20240131 Title: 2023 Cropland Data Layer Edition: 2023 Edition Geospatial_Data_Presentation_Form: raster digital data Publication_Information: Publication_Place: USDA NASS Marketing and Information Services Office, Washington, D.C. Publisher: USDA NASS Public Domain
Argricultural Production Data (World) A spatial production allocation model designed to provide detailed information about the geographic distribution of major crops. Year: 2020 Spatial Production Allocation Model(MAPSPAM) International Food Policy Research Institute (IFPRI), 2024, "Global Spatially-Disaggregated Crop Production Statistics Data for 2020 Version 1.0, https://doi.org/10.7910/DVN/SWPENT , Harvard Dataverse, V3 Creative Commons Attribution-NonCommercial 3.0 Unported License

Environmental and Social Issue Models

These models are used by CommodityMap to identify where environmental and social issues are occuring.

Environmental Issues
Category Descripton Dataset name Attribution License
Biodiversity Biodiversity Hotspots are regions where at least 1,500 vascular plants as endemics and must have 30% or less of its original natural vegetation. Year: 2016 Conservation International - Biodiversity Hotspots Hoffman, Michael; Koenig, Kellee; Bunting, Gill; Costanza, Jennifer; Williams, Kristen J., Biodiversity Hotspots, 2016, Conservation International/Zendo, version 2016.1, Retrieved from https://zenodo.org/record/3261807#.YvqLKS7MJtT Creative Commons Attribution Share Alike 4.0 International
Biodiversity This dataset represents a set of priority terrestrial areas identified for conservation based on their rich biodiversity and ecological significance. Year: 2004 World Wildlife Fund Global 200 Ecoregions World Wildlife Fund - Global 200 (terrestrial) Ecoregions Credits: World Wildlife Fund - US Publication Date: 2004 Publisher: World Wildlife Fund Other Citation Info: Olson, D.M., E. Dinerstein, E.D. Wikramanayake, N.D. Burgess, G.V.N. Powell, E.C. Underwood, J.A. D'Amico, H.E. Strand, J.C. Morrison, C.J. Loucks, T.F. Allnutt, J.F. Lamoreux, T.H. Ricketts, I. Itoua, W.W. Wettengel, Y. Kura, P. Hedao, and K. Kassem. 2001. Terrestrial ecoregions of the world: A new map of life on Earth. BioScience 51(11):933-938. Use Contraints
Category Descripton Dataset name Attribution License
Water The Aqueduct™ water risk framework combines 13 water risk indicators—including quantity, quality, and reputational risks—into a composite overall water risk score Year: 2023 Aqueduct 4.0 Current and Future Global Maps Data Kuzma, S., M.F.P. Bierkens, S. Lakshman, T. Luo, L. Saccoccia, E. H. Sutanudjaja, and R. Van Beek. 2023. “Aqueduct 4.0: Updated decision-relevant global water risk indicators.” Technical Note. Washington, DC: World Resources Institute. Available online at: doi.org/10.46830/ writn.23.00061. Creative Commons Attribution Share Alike 4.0 International
Category Descripton Dataset name Attribution License
Deforestation This dataset shows shows the dominant driver of tree cover loss from 2001-2022 using these two categories: commodity-driven deforestation: Large-scale deforestation linked primarily to commercial agricultural expansion.Shifting agriculture: Temporary loss or permanent deforestation due to small- and medium-scale agriculture. Year: 2022 Tree Cover Loss by Dominant Driver Curtis, P.G., C.M. Slay, N.L. Harris, A. Tyukavina, and M.C. Hansen. 2018. “Classifying Drivers of Global Forest Loss.” Science. Accessed through Global Forest Watch on 2023. www.globalforestwatch.org." Creative Commons Attribution Share Alike 4.0 International

Social Issues
Category Descripton Dataset name Attribution License
Forced and Child labor The Bureau of International Labor Affairs (ILAB) maintains a list of goods and their source countries which it has reason to believe are produced by child labor or forced labor in violation of international standards. Data only available outside the USA and listed at the country level. Year: 2022 List of Goods Produced by Child Labor or Forced Labor United States Department of Labor (USDOL) Public Domain (Disclaimer: The opinions expressed in this application are not the opinions of the U.S. Department of Labor (USDOL).)
Governamce The Worldwide Governance Indicators (WGI) aim to assess and measure the quality of governance in countries worldwide by providing a comprehensive set of indicators capturing various aspects of political, economic, and institutional governance. Year: 2022 Worldwide Governance Indicators Daniel Kaufmann and Aart Kraay (2023). Worldwide Governance Indicators, 2023 Update (www.govindicators.org), Accessed on 2024 Creative Commons Attribution Share Alike 4.0 International

Trade and Production Statistics

Category Descripton Dataset name Attribution License
Crop and Livestock Production Provides information on the international trade in agricultural products. Year: 2022 Crops and livestock products FAO.Crops and livestock products. License: CC BY-NC-SA 3.0 IGO. Extracted from: https://fenixservices.fao.org/faostat/static/bulkdownloads/Production_Crops_Livestock_E_All_Data.zip. Date of Access: 2023. Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO (CC BY-NC-SA 3.0 IGO)
Trade Data The FAO Trade Matrix is a database managed by the Food and Agriculture Organization, offering comprehensive information on international trade in agricultural products, facilitating analysis of trade patterns and movements of various food and agricultural commodities globally. Year: 2022 Detailed trade matrix FAO.Crops and livestock products. License: CC BY-NC-SA 3.0 IGO. Extracted from: https://fenixservices.fao.org/faostat/static/bulkdownloads/Trade_DetailedTradeMatrix_E_All_Data.zip. Date of Access: 2023. Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO (CC BY-NC-SA 3.0 IGO)

Administrative Boundaries

Category Descripton Dataset name Attribution License
Administrative Boundaries The database of global administrative areas (GADM) provides the adminstrative delination of all countries and sub-divisions. Year: 2022 GADM dataset 4.1 Global Administrative Areas 2022. University of California, Berkely. [digital geospatial data]. Available online: http://www.gadm.org [2022]. The data are freely available for academic use and other non-commercial use.