The Challenge
Many impacts of COVID-19 are reflected in socio-economic and epidemiologic data (e.g. unemployment statistics, infection rates, and mobility and transportation data). However, combining socio-economic data with Earth Observation (EO) data can enhance our understanding of and generate new insights regarding the effects of COVID-19.
Socio-economic data in general and those specifically related to COVID-19 are abundantly available and can be integrated with EO analyses in geospatial analysis environments (e.g., Geographic Information Systems (GIS), Jupyter notebooks). Your challenge is to integrate various EO-derived features with available and/or derived socio-economic data in various ways in order to discover or enhance our understanding of COVID-19 impacts.
Considerations:
- How can the integrated analysis of socio-economic data and EO-based data lead to enhanced insights into the impacts of COVID-19?
- Which impact dynamics can possibly be discovered on a local or regional basis?
- Consider multi-temporal features, such as max/min/median Normalized Difference Vegetation Index (NDVI), Short Wave Infrared (SWIR) reflectance for different time windows, specific absorption rate (SAR) backscatter statistics, or changes in brightness or temperature.
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