Estimation of Air Pollution with Remote Sensing Data: Revealing Greenhouse Gas Emissions from Space, presented at Tackling Climate Change with Machine Learning workshop at ICML 2021.
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Updated
Dec 3, 2021 - Python
Estimation of Air Pollution with Remote Sensing Data: Revealing Greenhouse Gas Emissions from Space, presented at Tackling Climate Change with Machine Learning workshop at ICML 2021.
This is a COVID-19 Air Pollution tracking program that looks at the correlation between COVID-19 Lockdowns and the overall pollution impact in certain European cities. The program utilses graphs and other visual stats to allow visual representations of significant or minimal difference in pollution levels with as a result to the on going pandemic.
This Python script processes nitrogen dioxide (NO2) satellite data by extracting relevant information based on geographical conditions, interpolating values using a KD-tree algorithm, and aggregating monthly averages. The resulting data is stored in NetCDF files for further analysis.
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