Land, carbon and biodiversity data for supply chain impact calculation
This repository contains global gridded data for estimating supply chain impacts relating to deforestation, related greenhouse gas emissions, conversion of natural ecosystems, and loss of intact or high integrity ecosystems. These data were originally prepared for the LandGriffon service (https://landgriffon.com) following international standards and guidelines for reporting and target setting in the agriculture, forestry, and land use sector. In particular, they employ a spatial adaptation of the Statistical Land Use Change (sLUC) by land occupation accounting method in which responsibility for impacts are allocated across a 50km radius instead of across a jurisdiction.
Methodology and usage notes: https://www.biorxiv.org/content/10.1101/2023.11.01.565036v1
Code: https://github.com/Vizzuality/lg-landscape-indicators-processing
Five indicators are included, with two layers per indicator: the impact, and annualized impact per hectare of human land use.
Impact layers (100m)
Annualized impact per hectare of human land use (1000m)
Of note, these datasets are not constrained to areas of current human land use, e.g. such that land use in remote wilderness may be assigned a maximum impact score.
See https://landgriffon.com/methodology for techniques for combining these results with land footprint data and production data to calculate the impacts of raw materials sourced from for local, regional, or national supply-sheds. For example, to calculate the deforestation footprint of sourcing 100 tons of soy from Argentina, a user could first calculate the average hectares of deforestation per hectare of land use for all soy producing areas in Argentina, and then multiply that value by the land footprint of 100 tons of soy production.
License
(c) Vizzuality 2023 CC-BY. This data is made available under a Creative Commons Attribution 4.0 International license.
Suggested citation
Francis Gassert, Biel Stela, Elena Palao Martinez, and Michael Harfoot. 2023. “Land, Carbon and Biodiversity Data for Supply Chain Impact Calculations.” Preprint. BioRxiv, 2023.11.01.565036. https://doi.org/10.1101/2023.11.01.565036.