The longer human activities are changed due to the COVID-19 pandemic, the more visible, wider, and longer lasting the scope of environmental impacts may be. Your challenge is to tell a visual story about the impacts of the pandemic using Earth observation data and other complementary information.
India best succeeded in curbing the spread of the virus, was not necessarily those with more resources, but rather those who did not hesitate to implement aggressive measures to contain the virus or eventually control its spread as early as possible. However, some of its states have recently broken world records for number of new daily infections or deaths per capita. The entire world population currently faces enormous challenges (i.e., social, environmental, health, and economic) due to the impact of COVID-19. It is important to know about the environment we live in, by knowing the AQI of the area. The team aims to analyze the air quality during the pandemic.
Storymap demonstrates the AQI (Air Quality Index) of India during the pandemic.The entire world population currently faces enormous challenges (i.e.,social, environmental,health, and economic) due to the impact of COVID-19. Even though the pandemic has a darker side, it is interpreted and identified, decreased in the rate of air pollution in many cities across India. The project gives us an overview of the AQI since the onset of pandemic in India.The work has analyzed the air quality condition during the lockdown using data from NASA – OMI, India Pollution Board,Kaggle and Ministry of Health and Family Welfare to derive a correlation between AQI and anthropogenic activity.
From an article that was published in business-standard.com entitled, “India breathes easy in lockdown: 90 cities record dip in air pollution” on March 29, 2020 depicts the tremendous decrease in the rate of air pollution across the country during the lockdown motivating the team to carry out an analysis on the air quality index for the country. The team was inspired with this article and produced her as an evidence spatially. The team used arcgis storymap, vuejs, javascript files for the development of the project.
The work has utilized NASA – OMI (EO Dashboard) for NO2 where as PM2.5, PM10, NO, NOx, NH3, CO, SO2 O3, Benzene, Toluene, Xylene from India pollution board and also Kaggle. Whereas the covid details were picked from Ministry of Health and Family Welfare, Government of India and Covid19Data (EO Dashboard).
The Covid data was mapped using point density analysis and later GIF (animations) for phases of lockdown. Whereas AQI was calculated based on the above parameters for the available station individually and later Inverse Distance Method was applied for understanding the spatial pattern of India's air quality.
It was quite evident that during the lockdown there was a positive correlation between India's closure and air quality. Though India suffered in this pandemic, she also healed in air quality scenario. The study spatially proves this with an evidence.
https://drive.google.com/drive/folders/1gVKUTPoQ2Vxo7hZB4ZyMKxFZVpvxVx5L?usp=sharing
The above link consists of project ppt, and a readme file with links for the storymap and github repository.
Steps to integrate the tool into earth Observing Dashboard:
1."Covid 19 Room" was added as a tab/button in the Dashboard.vue
2.Also CovidIndia.vue and Analysis.vue was attached with .vue file
3.Set an object for rendering arcgis story map in AppConfig.js
4.Append the iframe object to CovidIndia.vue to visualize the storymap in the dashboard.
5.Default settings to be added for the iframe.
6.Define html structure for analysis page in Analysis.vue
Currently we have added a new tab in EODashboard. the storymap can be added in the air quality indicator for Country India.
The work has utilized NASA – OMI (EO Dashboard) for NO2 where as PM2.5, PM10, NO, NOx, NH3, CO, SO2 O3, Benzene, Toluene, Xylene from India pollution board and also Kaggle. Whereas the covid details were picked from Ministry of Health and Family Welfare, Government of India and Covid19Data (EO Dashboard).
The Covid data was mapped using point density analysis and later GIF (animations) for phases of lockdown. Whereas AQI was calculated based on the above parameters for the available station individually and later Inverse Distance Method was applied for understanding the spatial pattern of India's air quality.
It was quite evident that during the lockdown there was a positive correlation between India's closure and air quality. Though India suffered in this pandemic, she also healed in air quality scenario. The study spatially proves this with an evidence.
#covid19India #airquality #AQI #lockdowns #spatial pattern #storymap
This project has been submitted for consideration during the Judging process.