OEMC project use case: Large-area estimation of forest carbon emissions
Description
We provided a disaggregated estimation of carbon loss and related GHG emissions (C and CO2) for commodity crop on a national and regional scale. This study combined forest/land change data, recent biomass datasets EO products, and agricultural census and crop data from national partners to produce high-resolution maps of deforestation and commodity expansion across four countries along the pantropical region. These disaggregated carbon emission factors and total emissions for different crop types at a national level contributed to a better understanding of the environmental impacts of agricultural expansion and support efforts to achieve a more sustainable and low-carbon future. This study evidences that disaggregated estimations of GHG emissions from land-use change for agricultural production offer significant improvements over current approaches. This information would allow stakeholders to enhance the accuracy and relevance of emissions estimates, support targeted policy interventions and sustainable land-use practices and contribute to global efforts to mitigate climate change and promote sustainable development.
Stakeholder needs:
- Up to date global biomass data and change analysis (to feed into environmental indicators).
- Land cover and land cover change data to inform SEEA accounting; as part of this, forest carbon stock change data.
- In both cases, downloadable global gridded datasets.
Implementation steps include:
- Updated country 'profiles' on low-emission food system transformations, providing tailored results for actionable recommendations to national contexts, aligned with national priorities and policies to advance on low-emission, climate-integrated food systems.
- Mapping of post-deforestation land change events on a pantropical scale, focusing on commodity crops relevant to the EUDR, providing insights into the complex interplay between deforestation and food systems at national, regional and pantropical scales.