CBAS Delegation Visits UNEP Headquarters in Nairobi
May 30, 2024
A delegation from the International Research Center of Big Data for Sustainable Development Goals (CBAS) visited the headquarters of the United Nations Environment Programme (UNEP) in Nairobi, Kenya on May 24, 2024.
The delegation participated in a roundtable meeting focusing on the potential applications of Big Earth Data in monitoring and assessing the Sustainable Development Goals (SDGs), as well as enhancing cooperation between CBAS and UNEP.
In the meeting, LIU Jian, Director of UNEP’s Early Warning and Assessment Division, pointed out the division’s commitment to providing policy-relevant environmental assessments and early warnings for emerging environmental threats, with geospatial and Big Earth Data playing a crucial role. Liu also expressed UNEP’s readiness to sign a new Memorandum of Understanding with CBAS to deepen their collaboration and jointly advance sustainable development efforts.
The delegation presented their achievements in utilizing Big Earth Data to promote SDG monitoring and implementation. They highlighted their collaborative efforts with various UN agencies, particularly their contributions to the UNEP’s measuring progress series reports on the environment-related SDGs. UNEP commended the CBAS’ work and invited the Center to continue contributing to the upcoming measuring progress reports.
In addition, both sides explored potential cooperation in environmental monitoring, capacity building, decision-making support, and artificial intelligence projects. Participants unanimously agreed that CBAS could leverage data from the SDGSAT-1 satellite to support decision-making in vulnerable regions for sustainable development, such as the Global South, in terms of early warning and environmental pollution monitoring.
This visit further strengthened the partnership between CBAS and UNEP, laying a solid foundation for both parties to advance the achievement of environment-related SDGs.
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CBAS Delegation Visits UNEP Headquarters in Nairobi