Guardian of The Monarch Butterfly

Our project, Is didecated to Homero Gómez González who dedicated his life in the protection and analisys of monarch butterflies. we leveraged advanced data analysis and machine learning

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Inspiration

Homero Gómez González’s (also knows as the Guardian of the Monarch butterfflys) dedication to protecting monarch butterflies was a powerful source of inspiration for our project. As a former logger turned environmental activist, he devoted his life to conserving the monarch butterfly's habitat in Michoacán, Mexico, one of the most important wintering grounds for this species. His passion and commitment demonstrated the critical role that individuals and communities play in protecting vulnerable species from environmental threats. It is believed that his murder is related to his activism work in the monarch butterfly sanctuary.

What it does

Our project creates an animated map illustrating the movement of monarch butterflies during their migration and provides an estimate of their population. Additionally, we analyze the impact of pollutants such as CO, Ozone, and PM2.5 to determine how these substances may affect their migration patterns and population levels.

How we built it

We collected data from Journey North using web scraping techniques, as well as from the EPA's Air Quality System Pre-generated Files. The data was then processed and analyzed using Python, with libraries such as Pandas and PySpark, to extract meaningful insights. The data from Journey North was utilized to create a detailed map using Matplotlib, Seaborn, and Cartopy, illustrating the concentration of monarch butterflies across various regions. The data from the EPA Air Quality System was employed to develop machine learning models. These models were designed to identify potential relationships between monarch butterfly populations, at the county level, and air quality parameters such as PM2.5, Ozone, and CO. This analysis was performed using Python and key libraries including Scikit-learn, Pandas, and NumPy.

Challenges we ran into

We run with the problem of retriving a lot data from API of the air quality system. The request where taking so long almost impossible to run but at the end we change our strategy and we download specific zip file to use them with a faste eficiency

Accomplishments that we're proud of

We are proud that we were able to adapt quickly and change the decision of stop using API calls and use the zip files

What we learned

We learn how to manipulate big data frames and how to made it meaninful for analysis, and how to retrive data by web scripting and API request

What's next for Guardian of The Monarch Butterfly

we want to implement more parameters such as pestecides

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