The EO Dashboard has multiple global maps for air quality and greenhouse gases in GeoTIFF file format. Your challenge is to create a spatial analysis and time series plotting tool for EO Dashboard air quality and greenhouse gas GeoTIFF datasets.
The pandemic has caused an impact on everything, from society to the environment. Our team has planned to create a data-driven system checking the overall impact of the virus on air quality and other factors like population density change, mobility, and more. we have created a new indicator showing ratios of total deaths to total cases in five particular countries which could be extended to other countries in the future. Since we have discovered few more ways to study the areas of impact on society and atmosphere, the government can take measures to give more attention to areas having more death ratios due to COVID, and people, in general, could be more aware of their surroundings.
Our project addresses the "SPATIAL ANALYSIS AND TIME SERIES" challenge.
We have developed ways to better understand the impact of COVID-19 on the environment and people in different countries so as to 'analyze data more clearly and extend help' to more impacted ones by various indicators:
When the EARTH OBSERVING DASHBOARD HACKATHON was released, we were inspired to do something new and accepted the challenge.
We analyzed the data at EO Dashboard and came to know various parameters including that COVID-19 cases were increasing in a discontinuous manner despite high restrictions on mobility and gatherings. We were able to analyze the effect of lockdowns on air quality as well.
Finally, we gathered all the data from EO Dashboard, different sites at google and EDC and started working on ways to give a better understanding of the impact patterns for people and government.
We have used python to code for data and visualizations so as to make our idea interactive for the audience. We used a Powerpoint presentation to create a presentation for our project.
In this hackathon, our team faced a lot of challenges which are:-
However, besides all the problems faced, we had learned lots of new stuff and accomplished very interesting tasks as well like:-
We analyzed the EO Dashboard data and with the facility of CSV file downloads, we were able to extract data from it and use to create scatter charts, line charts, and other visualizations.
We took the data of different indicators for five countries from the dashboard and EURODATACUBE jupyter notebooks, using this data, we plotted charts for our project.
https://drive.google.com/file/d/1QdIy-U9u5KnNFV0-W58PF3M9Tn3xp9De/view?usp=sharing
We have created data in python coding which could be converted to the format to be integrated in the EARTH OBSERVING DASHBOARD. As per the information from resource guides and queries solved by experts, we haven't made the coding ready for integration.
https://github.com/Valdemirjr7/PowerOfSpaceScience
To create the model, the team collected data from:-
https://eodashboard.org/
https://eurodatacube.com/dashboard
#nasa #esa #jaxa #eodashhack #analyze #earth #covid #impact #solution
This project has been submitted for consideration during the Judging process.