For my final data visualization project, I chose to work with a data set about California Wildfires (2013-2019). This data set contains information about each wildfire including the name, number of acres burned, archive year, and location. The source for this data set is Kaggle (https://www.kaggle.com/datasets/ananthu017/california-wildfire-incidents-20132020).
I wanted to create a visualization that would allow users to see wildfires based on the year. This would enable the user to compare the different years and their respective wildfire rate. I am curious about whether there are any patterns regarding the number of wildfires as the years go on. I am also interested in seeing if there are specific regions in California where wildfires occur the most.
In my visualization, the data is represented as dots on a map based on the latitude and longitude of the city in California where the wildfire occurred. The color of the dot indicates the number of acres burned in the wildfire. As shown in the image below, if the dot is red, the wildfire burned 100,000 acres, whereas if the dot is yellow, the wildfire burned less than 20,000 acres of land.
To interact with the visualization, try pressing on one of the buttons: 2013, 2014, 2015, 2016, 2017, 2018, 2019, or Total. The program will show you the map of the wildfires from that specific year. The "total" button shows all wildfires from 2013 to 2019.
One interesting thing I noticed during this project is that 2017, 2018, and 2019 are the years in which the most wildfires occurred in California.
Something I still wonder about is: Given the current data about California Wildfires, can we predict what the visualization would look like in 2023? If so, does it follow the trend which we have seen before that wildfires worsen each coming year?