Using Automated Processes Using GES DISC API to Help Users Easily Access Data of Air Quality Events
The Canadian wildfires have notable impacts on air quality in the US and it led to a substantial decline in air quality levels. This event releases massive amounts of harmful particulate matter and pollutants into the atmosphere, leading to long-term consequences for both human and ecological well-being. To study and analyze the consequences of these events, air quality data from different sources such as satellites, in-situ, and airborne observations must be used. Currently, the retrieval of satellite data solely relies on a manual process, wherein each day necessitates individualized retrieval. This current approach is burdened with repetitiveness and demands a significant amount of time, posing substantial challenges. In the present research, an automated process was created using NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) Application Programming Interfaces (API) and a job scheduler application. With the use of APIs, data could be easily downloaded from NASA’s server filtering by cloud cover, acquisition date, resolution, spatial extent or any other relevant parameters. This code was finalized in Python and allowed users to easily access the data to help analyze various air quality events. The users will now be able to address the above-mentioned challenge more efficiently.
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