Undergraduate Research & Scholarships

Peter Flo Grinde-Hollevik L&S Social Sciences

Applying Satellite-Based Geospatial Embeddings for Predictive Tasks

The advent of satellite-based geospatial embedding data has allowed for a new opportunity to explore an unforeseen set of capabilities in environmental predictive tasks. In this project, I first establish the predictive relationship between census block-level in-situ measurements of median NO2 concentrations derived from the Google Street View Car and geospatial embeddings sourced from the Sentinel-2 satellite and the Earth Genome Project. 

This hypothesized relationship is then extended into the construction of a generalizable and robust predictive modeling framework. I then hope to deploy this framework on 4 counties of the Bay Area, seeking to accurately predict median concentrations of the set of census block-level NO2, NO, Black Carbon (BC), and Ultra Fine Particle Count (UFP) concentrations. 

With the goal of minimizing the final model’s prediction error, this paper also suggests a replicable framework for carefully diagnosing spatially distributed model-induced bias.

Message To Sponsor

I'd very much like to thank my donors for facilitating an awesome research experience over the summer. Since I learned about geospatial embeddings a year ago, I've wanted to spend a significant amount of time delving deeper into the incredible potential they may have in environmentally-focused predictive tasks. Your kind support allows me to do just that!
Major: Data Science (B.A), EEP (B.Sc)
Mentor: Sofia Villas-Boas
Sponsor: CACSSF
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