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Brief Methodology for WWF Discussion Paper: Using Public Data Platforms To Assess Deforestation Risks Within Jurisdictions I January 2017

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Countless companies, governments, NGOs, and Indigenous Peoples’ organizations have collectively committed to eliminate deforestation from major agricultural commodity production. While this global ambition shows great promise, considerable challenges lie ahead. In particular, these challenges include both a lack of transparency and traceability within commodity supply chains and the issue of illegality across production landscapes, which can leave stakeholders vulnerable to a number of economic, social, and environmental risks.

World Wildlife Fund-US, with support from Global Forest Watch, developed the Jurisdictional Risk Assessment to explore potential applications of public data platforms (such as Global Forest Watch) that allow companies, governments, and other end-users to assess certain jurisdictions and their potential association with illegal deforestation. This tool can help companies and governments prioritize and strengthen their traceability and due diligence efforts. Using palm oil and Indonesia as a pilot geography, we developed a set of key indicators that approximate deforestation risks at the district level based on the extent and rate of deforestation in areas where deforestation is not permitted to occur (i.e., in primary forests, protected areas, peatland, Forest Estate) and through deforestation activities that are considered illegal (e.g., use of fire) in Indonesia. 

Among other important considerations, the JRA is based primarily on historical remote sensing data and does not quantify social risks (e.g., land insecurity, labor rights). It is not intended to be used as a standalone tool with regard to procurement and sourcing decisions. However, the JRA can complement other sources of information (in particular, local knowledge and consultations) to paint a broader picture of deforestation risks that may be associated with illegal deforestation.

Full Report and detailed methodology is here

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