1.1. Digital for impact: digital capabilities as accelerators to support the transformation of agrifood systems 43
1.3.2. United Nations collaboration
United Nations Committee of Experts on Global Geospatial Information Management (UN-GGIM) Led by United Nations Member States, UN-GGIM aims to address global challenges regarding the use of geospatial information, including in development agendas, and to serve as a body for global policy-making in the field of geospatial information management. FAO played an active role in the UN-GGIM meeting in July, aiming to take a lead and contribute more to geospatial data federation and interoperability in the UN Geospatial Network, including but not limited to the One UN Geospatial Situation Room.
UN OpenGIS Geo-AI Working Group and Geo-AI challenge
FAO is a member of UN OpenGIS initiative, co-chairing the UN OpenGIS Working Group 5 on Geo-AI to promote artificial intelligence innovation and applications in geospatial IT. In 2022, FAO worked closely with the UN Geospatial Unit, Politecnico Milano, UN Global Pulse and the International Telecommunications Union (ITU) in the Geo-AI challenge on cropland mapping with satellite remote sensing, which was the first of the serial Geo-AI challenges covering different UN missions and mandates. Furthermore, Geo-AI benchmarking is planned.
Linking digital and nuclear: FAO-IAEA Joint Research Centre collaboration
Present and participating actively in the FAO Science and Innovation Forum, the International Atomic Energy Agency (IAEA) through the Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture, brought together new opportunities to forge nuclear and digital links. The team from the Soil and Water Management and Crop Nutrition Subprogramme of the Joint FAO/IAEA Centre is developing various combinations of nuclear and digital techniques to enhance the use and conservation of natural resources (soil and water), e.g. combining
cosmic ray neutron sensing (CRNS) with UAV (drone) and satellite imagery to monitor area-wide availability of water for agricultural purposes in order to improve water use efficiency. The team is also working closely with other divisions in FAO and its Members to use mid-infrared spectroscopy and artificial intelligence to improve the prediction of soil properties (e.g. exchangeable potassium) for the remediation of environmental pollution (e.g. radioactive contamination) in agriculture and soil fertility mapping.
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