Awards & Nominations
Blaze has received the following awards and nominations. Way to go!
Spot That Fire V3.0
Spot that Fire 3.0
Summary
Creation of data model which correlates both wildfire spread and economic data. This project analyzes the causes of wildfires and predicts the economic impact in the future. Based on various machine learning models, it's accompanied by visuals.
How We Addressed This Challenge
We created a system correlating economic data and wildfire data because we felt it's the best representation of the real world aftermath. Our purpose was to clearly represent these changes with a trend and general consensus.
How We Developed This Project
We aimed to draw a connection between wildfires and economic effects. We jointly analyzed economic effects in noting growth and decline trends. Completing this allows us to communicate trends in this data to understand where more time, energy and funds need to be directed after a wildfire. We began by researching what datasets to acquire. This was specific to geostationary data and high frequency economic data. The MODIS dataset was our main source for geostationary data, whilst the Weekly Economic Index (WEI) information sufficed for our economic data. After acquiring these datasets, we worked on code to process and analyze them. After this, we used various libraries to create visual representations of this data.
How We Used Space Agency Data in This Project
Our project utilized data from Terra, one of NASA' s earth based satellites. Terra monitors current fires. Using this data, we were able to isolate factors which influenced economic growth and the succession of wildfires. This data set - MODIS - was crucial to our project.
Project Demo
https://www.canva.com/design/DAEJkgipoXY/VNSrQeznGP-0HIhZi6hqyg/view?utm_content=DAEJkgipoXY&utm_campaign=designshare&utm_medium=link&utm_source=sharebutton
Project Code
Data & Resources
- NASA FIRMS fire data
- US Weekly Economic Index
- Washington Quarterly GDP