What environmental impacts does LandGriffon measure?

LandGriffon helps companies strategize the sustainable transformation of their supply chains by using technology, data and scientific-based analysis to manage environmental impacts. This blog is part of our methodology series. You can find more blogs on our methodology here, or head to our website and download the complete paper.

Baseline indicators

LandGriffon calculates indicators of environmental impacts such as water use, land use, deforestation, greenhouse gas emissions, and biodiversity loss associated with agricultural production. These indicators are calculated by combining company sourcing data with global environmental datasets, such as Copernicus Global Land Service, Global Forest Watch and Aqueduct.

LandGriffon’s baseline indicators are focused on the impacts of agricultural production. The LandGriffon software and framework are designed to readily integrate additional indicators.

Water use

The water resources consumed to produce the material. Water consumption impact calculated using product blue water footprint estimates from the period 1996–2005.

• Mekonnen, M.M. & Hoekstra, A.Y. (2011) The green, blue and grey water footprint of crops and derived crop products, Hydrology and Earth System Sciences, 15(5): 1577–1600.
• Mekonnen, M.M. & Hoekstra, A.Y. (2012) A global assessment of the water footprint of farm animal products, Ecosystems, 15(3): 401–415.

Unsustainable water use

The water consumption in regions with a baseline water stress (BWS) ratio of more than 0.4, as identified by Aqueduct. BWS measures the ratio of total water withdrawals to available renewable surface and groundwater supplies.

• Hofste, R., S. Kuzma, S. Walker, E.H. Sutanudjaja, et. al. 2019. “Aqueduct 3.0: Updated Decision Relevant Global Water Risk Indicators.” Technical Note. Washington, DC: World Resources Institute. Available online at: https://www.wri.org/publication/aqueduct-30

Aqueduct by WRI.

Land use

The total land area required to produce the material. Land impact is calculated using material production and yield data from the global 2010 MapSPAM and 2010 Gridded Livestock of the World v3 (GLWv3) datasets.

• International Food Policy Research Institute, 2019, “Global Spatially-Disaggregated Crop Production Statistics Data for 2010 Version 2.0”, https://doi.org/10.7910/DVN/PRFF8V, Harvard Dataverse, V4
• Yu, Q., You, L., Wood-Sichra, U., Ru, Y., et. al. 2020. A cultivated planet in 2010: 2. the global gridded agricultural production maps, Earth Syst. Sci. Data Discuss. https://doi.org/10.5194/essd-2020-11
• Gilbert, M., Nicolas, G., Cinardi, G., Van Boeckel, T.P., et. al. 2018. Global distribution data for cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in 2010. Scientific data, 5(1), pp.1–11. https://doi.org/10.1038/sdata.2018.227

A global gridded agricultural production map of Maize, by Yu et al.

Greenhouse gas emissions

The amount of greenhouse gas (GHG) emissions arising from the production of the material. GHG impacts are calculated using impact factors from published assessments of materials’ environmental impacts throughout their entire lifecycle.

• Poore, J. and Nemecek, T., 2018. Reducing food’s environmental impacts through producers and consumers. Science, 360(6392), pp.987–992. https://doi.org/10.1126/science.aaq0216

Climate risk from land use change

The GHG emissions associated with forest loss near agricultural production areas. The general equation for landscape-level impacts is adjusted for the mean annual gross emissions of GHGs associated with forest change from 2001 to 2019.

• Harris, N.L., Gibbs, D.A., Baccini, A. et al. Global maps of twenty-first century forest carbon fluxes. Nat. Clim. Chang. 11, 234–240 (2021). https://doi.org/10.1038/s41558-020-00976-6

A global map of twenty-first century forest carbon fluxes, by Harris et al.

Deforestation risk

Forest loss occurring near material production areas. Deforestation is either calculated using Satelligence models trained to identify transitions from forest to non-forest states in satellite imagery, or using global tree cover loss data from Global Forest Watch.

• Reiche, Johannes, Rob Verhoeven, Jan Verbesselt, Eliakim Hamunyela, Niels Wielaard, and Martin Herold. 2018. ‘Characterizing Tropical Forest Cover Loss Using Dense Sentinel-1 Data and Active Fire Alerts’. Remote Sensing 10 (5): 777. https://doi.org/10.3390/rs10050777
• Satelligence, 2020: https://satelligence.com/news/2020/1/30/from-millions-of-satellite-images-to-your-deforestation-alert-answering-the-3-most-frequent-questions
• Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, et al. 2013. “High-Resolution Global Maps of 21st-Century Forest Cover Change.” Science 342 (6160): 850–53. https://doi.org/10.1126/science.1244693.

Example map from Satelligence.

Biodiversity risk from land use change

The potential impact on biodiversity associated with forest loss near agricultural production areas. To align with previous analysis and with guidance from the Science-Based Targets for Nature, the indicator is calculated at two different levels:

Species: Rarity-weighted richness serves as a measure that can be used to modify indicators. It combines species richness with the endemism of the species occurring in a given grid cell to reflect the importance of the habitat being lost for the species occurring in that location.

Ecosystem: The change in ecosystem quality and structure associated with the sourcing of a material. This indicator expresses the average degree of intactness due to factors and indices such as habitat loss or the change in ecosystem structure as a result of deforestation.

• Integrated Biodiversity Assessment Tool. https://www.ibat-alliance.org/the-data?locale=en
• Rarity-weighted richness: a simple and reliable alternative to integer programming and heuristic algorithms for minimum set and maximum coverage problems in conservation planning, PLoS ONE, 10 (2015), pp. 1–7, https://10.1371/journal.pone.0119905
• Beyer, H.L., Venter, O., Grantham, H.S. and Watson, J.E., 2020. Substantial losses in ecoregion intactness highlight urgency of globally coordinated action. Conservation Letters, 13(2), p.e12692. https://doi.org/10.1111/conl.12692

Ecoregion intactness map, by Beyer, Venter, Grantham, and Watson.

To learn more about the science and technology of LandGriffon, you can download the full methodology from our website.

Interested in LandGriffon and our services?

Contact us now at hello@landgriffon.com

LandGriffon is developed by Satelligence and Vizzuality, and advised by the Stockholm Environment Institute and their Trase Initiative.

Thank you Mike Harfoot, Elena Palao, Francis Gassert and Rens Masselink for preparing the methodology.