Climate Data Visualization

Strong typhoon Hagibis attacked northern Japan in the early morning of October 13 Prior to this, the capital Tokyo was hit by heavy rains, strong winds and earthquakes. The river was soaring and the streets were empty. There are currently four deaths in Japan, 80 injuries and 17 missings, nine of whom were missing during mudslides and floods. Volcanic eruptions, earthquakes, tsunamis, and tornadoes all invaded Japan. People could not help but be afraid of it. How to quantify the damage and loss caused by various disasters, and how to understand the specific situation of the disaster. A lot of complicated disaster data often makes you unable to get started, however, if you have the help of data visualization, everything will be a lot easier.

I will give you a few examples below.

Real-time Disaster Data Visualization

The following two figures are the heat maps of this Hagibis attack on Japan. Although they are also heat maps, the content is completely different.

From Twitter

You can clearly see from this picture the area from the hurricane center to the periphery of the hurricane and the temperature distribution. With such a large wind, it is hard to imagine how much damages the typhoon power brought.

From Twitter

This heat map can be said to be a miniature version of the previous heat map, you can see the direction of the hurricane from this picture. On the evening of October 12, the typhoon can be said to be direct to Tokyo.

Heat maps are a common type of chart used to represent natural disasters. The following is a heat map of the July Indonesia earthquake. From this heat map, you can clearly see the range of the area affected by the earthquake and the magnitude of the earthquake.

From Twitter

Post-disaster Data Visualization

Before natural disasters and during disasters, data visualization is more inclined to the prediction of disaster routes and the prediction, notification of real-time damage. At this time, the data is often incomplete and many of them are directly obtained data that are not clear in data. It is often difficult to achieve a clear data visualization effect.

Therefore, data after the disaster is often processed and the quality is relatively high. After the data visualization tools (Tableau、FineReport、PowerBI processing, the visualization effect will tend to be more diverse, and the effect is better.

Hurricane Trend Map

You can refer to the previous article: I Made a Dynamic Hurricane Map with Excel！

Made by Excel

You can’t imagine that it is made by Excel, right?

If you are interested in this map, you can check the link to know how to use Excel to make such a hurricane map, it can detect the direction of the hurricane and the real-time wind level of it.

You can clearly see from this picture the route of the hurricane, which area has the greatest impact, this is the intuitive feeling that simple data can’t bring you, the processed data can convey more beautiful and direct information, which is a good solution to the problem that data cannot be displayed dynamically.

Yale Climate Opinion Map 2019

Made by Tableau

You can’t imagine how much information is in this picture. You can find out the views of people in all states of the United States on climate warming through parameter queries.

On the left, you can choose from national, states, congressional districts, metro areas and countries. Dynamic display is also very smooth.

You can also select the questions from the top and learn more.

When you click into a specific regional module, there will be specific Public Opinion Estimates for the area, such as beliefs, risk perceptions, policy support and behaviors.

By means of parameter linkage, the time for viewing multiple sets of data is omitted.

You can view multiple sets of corresponding data for a region with a simple selection.

Earthquake Heatmap

China Earthquake Heat Map Made by FineReport

The Earthquake heat map in Southeast Asia Made by FineReport

Talking about climate data visualization, heat map is the most common form. Thermal maps are generally used to indicate the weight of various points within a geographic area, and are generally displayed in a special highlight. FineReport supports a variety of map forms and thermal range modifications to maximize your design freedom. The above picture is the heat distribution map of China’s earthquake distribution made with FineReport. If you are interested in it, you can refer to Pure report-operated heat map tutorial without one line of code!

In addition to the classic heat map, the streamline diagram is also a disguised heat map, which is not the weight of a single point but the weight of a line. The above picture shows the New York taxi route map. The thickness of the route shows the congestion of the route. The reason why the streamline diagram is not common is that the streamline diagram template is not common and the production is difficult. However, FineReport supports the design of streamline heat maps, which greatly improves the drawing efficiency.

Conclusion

Human beings often appear to be very weak in the face of disasters, but it is from every disaster that we have grown. From the data brought by the disaster, we can understand the form of the disaster and the damage caused by the disaster through data analysis and data visualization, so as to find a better way to deal with the disaster.

More examples of data visualization can be found here.

Follow FineReport Reporting Software on Facebook to learn more about data visualization!