Through this project, we will demonstrate the outcome of the project analysis carried during the hackathon on variation of economic impact of Covid-19. The project will investigate the followings:

1.) What are the after effect impact of social and economic of Covid-19 between three selected regions: Asia Europe and US compared over the same time?

2..) What are the pre-Covid-19 effect and impact on social and economic of pre-Covid-19 between three selected regions: Asia Europe and US compared over the same time?

3.) What are the lessons learn based on this project investigation during the hackathon?

4.) How can our project be used as tools/resource that can by government, agency, local government, etc....

5.) What are future tell us about Covid-19, human activities and environment issues.

Having gone through available resources, tools and satellite materials, we will provide a project documentation, outcome and references/links

1. Research were conducted on eodashboard.org
2. Most of our data input come from eodashboard: indicators, countries, maps and tables
3. Tables data were exported and imported into our jupyter-lab uisng a free 3 months account from Euro Data Cube @ eurodatacube.com
4. Area of interest (AOI): were from Transport, Industrial, Health and Retails (We selected these four areas as we believe that most urban activities were position within these four(4) sectors of areas of economic and social. Each sector usually associated with people movements, income per capital(GDP), labour (e.g. industrial, human activity, haulage, trading (buying/selling, commerce); ports of entry/exit) and many more...
5. Our focus for those areas of interest within the urban in USA, Europe and Asia. These are industrialised part of World that mostly active 24 hours, 7 days always.
6. We wanted to see the impact of Covid-19 pre-Covid-19 lock-down data from selected time-series (our time series are based on Monthly data from Sentinel-2 , AJAX). During Covid-19 lock down then follow by analysis of some pattern that deviate from normal (value of 1). value of 1 is used as datum line(point). Below value of 1 is low while above value of 1 is for high.
7. We also interested in how covid-19 impact

As we are analysing the environment , socio-economic impact of the pandemic we get a opportunity to see things from the satellite view and the database information about the changes over the time . we have looked into the information retrieved from the Sentinel -1, GOSAT, TROPOMI, ALOS-2 sensors and satellites map and indicators.

We looked at the Air quality of three different regions ,Tokyo, Milan and London and they all have similar drop of NO2 in the air changes after the national lockdown announced around 2oth April 2020. As the lockdown eased in Roam the percentage of NO2 starts slowly increasing in Roam . where at the same time period in New York the lockdown didn't lift and NO2 percentage average remain consistent level.

We have also looked at the transport activities like Car Density change in Nagoya Port, Japan time laps between 2019-2020 and Los Angeles, Activity cars/ container

EAGLE EYE PROJECT DEMO

https://docs.google.com/presentation/d/17-dNntyjQShSrhpA2344Da54qpND_-geswL0NibyQb0/edit?usp=sharing

We thought it carefully out the up-scaling mode of our project in what we could call continuous integration and continuous development in Agile development framework.

1. We made use of Python pandas data library using the EuroDataCube.
2. For this project we registered at EuroDataCube
3. All our data analysis are carried out using JupyTer-Lab on EuroDataCube platform (see our presentation slide page)
4. All our project and its' resource are contained on eodashboardhackathon website (see our presentation slide page)
5. We examine, study deeply and adapted AOT Covid-19 sample on EuroDataCube Jupyter lab for use in our project (mentioned on our presentation slide page)
6. We sincerely believe that our project is already is ready for integration into Earth Observation Dashboard and could upscaling as needed

Open Street Map https://www.openstreetmap.org/

LeafLet Map: https://leafletjs.com/

Euro Data Cube: https://eurodatacube.com/marketplace/

EODashboardon github: https://github.com/eurodatacube/eodash

Our World Data: https://ourworldindata.org/covid-vaccinations

ESA: https://race.esa.int/?poi=GG-GG

This project has been submitted for consideration during the Judging process.