Demo Video in Loom: https://www.loom.com/share/f5a468a0482a466f815a704daacb1b29
Inspiration
Land degradation is intertwined with multiple critical factors, including drought effects and population impacts. However, global geospatial and socioeconomic is vast and disparate, resulting in complex data analysis requiring advance technical expertise to generate actionable insights. With the acceleration in AI capabilities, we're hoping to apply new methods to analyze relationships between land degradation, drought, and socioeconomic factors in order to unlock insights and empower policymakers to advise and monitor policy.
What it does
The Green Policy Agent is an AI-powered analysis and visualization tool that allows UN policy analysts to analyze geospatial and socioeconomic data in a friendly chat interface with a visual map to demonstrate change over time.
Challenges we ran into
Finding relevant datasets and importance of data management
What we learned
From this project, we took away how difficult current methods of analysis are for policy analysts and data scientists due to the vast amount of disconnected datasets and complex network effects of land degradation and socioeconomic factors.
What's next for Green Policy Agent
Iteration would entail expanding the Green Policy Agents coverage to include datasets from more countries, more socioeconomic data, and additional land degradation indicators.
Built With
- css
- deckgl
- flask
- h3
- html
- javascript
- python
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