A new project collecting field plot data to identify High Carbon Stock forests (HCS) in Sumatera, Kalimantan and West Papua will start work in March. This is a collaborative initiative between the HCSA and Indonesian-based Participatory Mapping Network JKPP, supported with a grant from the German Development Agency, GIZ.
The research and data gathered will provide information about forest composition and structure and will be used to identify and verify the different categories of HCS forest – from High Density Forest to Cleared/Open Land.
The goal is to develop an open-source resource of field-validated indicative HCS forest/High Conservation Value maps covering the whole of Indonesia using a combination of remote sensing (satellite data), Artificial Intelligence (AI) and data gathered on the ground.
This field plot data will provide a validation dataset to test the accuracy of HCS maps going forward – providing a more accurate and reflective account of what is actually on the ground than the information from remote sensing and AI alone can offer. The new data and analysis will also be used to refine existing indicative HCS forest classifications.
The JKPP participatory mapping network leading this work is made up of NGOs, Civil Society Organisations and individuals. The data will be collected in partnership with specialist local mapping organisations, communities, public institutions and commodity producers and JKPP members have strong experience in participatory mapping, spatial conflict advocacy and community land rights. They have mapped a total area of 17.1 million hectares publicly accessible through Tanahkita online land portal.
We will also be working with our network of HCSA members including commodity producer companies and Technical Service Organizations in Indonesia to share expertise in conducting large-scale mapping data collecting and sourcing data from previous and ongoing field plot inventories.
By working with researchers and scientists at Universitas Gadjah Mada and Institut Pertanian Bogor, this project will continue to build technical capacity and ensure a stable platform to access both the training data and the algorithms to promote collaboration and open access to data and tools.
This project builds on the learning from previous and ongoing large-scale mapping efforts by HCSA members and collaborators and will provide a valuable resource for stakeholders to assess areas of conservation importance, develop land management plans at a local and regional level and overcome a significant hurdle to the widespread adoption of the HCS approach for farmers and communities.
