A Brief History of Hurricanes:

From the big pictures to individual storms

MY ROLES

Designer

Analyst

PROCESS

Data Interpretation

Visual Exploration

TOOLS

Photoshop / Illustrator

P5.JS / Excel

This design is a combination of information design, graphic design with personal analysis. Based on the data set from the National Hurricane Center provided by  Northeastern University. I grouped 10 years to make it easier to calculate and view larger maps.  I tried to find the connection between storm/hurricane days and time. Then I restarted this project based on the following questions:

 

1. Does the length of days have a relationship with time?

2. Do we have more hurricane/ storm days through time?

3. Does the percentage of hurricane days change through time?

 

*Wind speed might change several times a day. Once they reached 64km/h (hurricane wind speed) anytime in a day, I calculate that day as a hurricane day.

 

The results were not what I expected. Here are something I learned from this project:

 

1. Different visualizations for the same information shows different results.

2. Data analysis is a process from a simple idea to a piece of complex information break down and end with simple output.

3. Suitable data visualization helps people see how different data sets are.

hurrican8.jpg

Through generations, charts are still the wildest used data analysis form. The power of a group of beautiful, simple charts is stronger than we thought.

 

In the design below, the bar chart shows the total number of days, and the line chart focuses on the change of each day. The two represent a set of data and are presented in different ways. The bar chart is more useful for analyzing the change of the number of days, and the line chart is useful for analyzing the relationship between the intensity and time of the hurricane.

hurrican11.jpg
hurrican12.jpg

When we visualize the exact same data but in the different chart forms, it results in a totally different visual solution. How to find a good model for data visualization is very important, and different focus of the same data sets create many interesting visual languages. To find more information, please download the book.

© Siyue Tan 

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