Wildfires Time Series

Inspiration

The 2020 wildfire season was one to remember. Amidst the devastating coronavirus pandemic and social justice issues, the 2020 wildfire season has burnt itself in our memory as one of the worst in history. In a span of 12 months, over 58 thousand fires raged throughout the country, burning through nearly 10.3 million acres. Threats of smoke inhalation led to mass evacuations and the loss of many homes, and it has forced families to move away in search of less fire-prone areas. My chemistry teacher in high school was one of those people, and his stories about Oregon’s wildfires were truly heartbreaking.

These health and social impacts inspired us to study the past history of wildfire seasons in America to get a sense of what could happen in the future.

What it does

Time-series visualization of wildfires and associated deaths and injuries from 1996-2022 in the United States.

How we built it

We realized it was important to take a look at past historical data to understand how an effect of climate change, wildfires, have raged through America. From the same source of data provided to us, we merged data from 1950 - 2021 with our current dataset from 2022. Wildfire data did not exist from 1950- 1996, so our visualizations began from 1996. We used python's builtin requests module and BeautifulSoup to extract the links to each dataset and download each of them. Then, using pandas, we decompressed each .csv file and then concatenated them together to create a singular, large dataset that we imported into Tableau for further analysis and visualizations.

We explored the impacts of wildfires throughout this period in terms of deaths, injuries, and value of property damaged.

Challenges we ran into

We learned Tableau as a group to come up with visualizations that best present the story in our dataset, overcoming the obstacles related with learning a new technology.

Accomplishments that we're proud of

We’re proud of our ability to come together and present a cohesive, data-augmented story about an ongoing effect of climate change that has real impacts on health, lives, and money, making it easy to contextualize the true consequences of climate change.

What we learned

Day-to-day effects of climate change can become muddled. Through our process, we were able to learn how to better use Tableau to our advantage to create powerful visualizations in this case particularly using the time-series.

What's next for Wildfires Time Series

The next step is to gather meteorological climate data across the US to build models that can predict the severity of future wildfire seasons in terms of count, acreage burned, and severity of fires, as well as predicting at-risk locations.