Al Accelerated Human-in-the-Loop schools and land use and land cover mapping for climate actions
2021-09-29, 15:30–16:00, Group on Earth Observations

AI isn’t perfect when it comes to learning about complex satellite imagery and real-world features. On the other hand, only relying on humans to map complex features and objects is too tedious and slow. AI accelerated human-in-the-loop methods provide new approaches to quickly create map objects and features for climate actions with scalable cloud computing power and growing EO data. At Development Seed, we’ve been proudly working with two partners, UNICEF and Microsoft Planetary Computer, to bring AI accelerated human-in-the-loop methods to the hands of policymakers, scientists, and mappers for SGD and climate actions.
In this talk, we would like to present:
What are AI accelerated human-in-the-loop methods for SDG and climate action?
How can we leverage the scalable methods in the era of growing EO data and cloud computing?
How fast and scalable we can create accurate school and LULC maps for policymakers, scientists, and mappers.

Please see the abstract above

Authors and Affiliations

Development Seed


Open data


FOSS4G implementations in strategic application domains: land management, crisis/disaster response, smart cities, population mapping, climate change, ocean and marine monitoring, etc.


1 - Principiants. No required specific knowledge is needed.

Language of the Presentation


Dr. Zhuang-Fang NaNa Yi is GeoAI Lead and Machine Learning Engineer at Development Seed, who has a Ph.D. in Ecological Economics and has applied geospatial analysis and satellite imagery processing in her various academic works since 2010. Before DevSeed, she was a research scientist in quantitative ecology.

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