Visualization 1 – Analyzing Nuclear Plants around the world

For my first visualization, I chose to plot the location of nuclear plants all over the world. The source of the dataset is from the Socioeconomic Data and Applications Center (SEDAC). I acquired it from the official SEDAC website that provides the population exposure estimates in proximity to Nuclear Plants. The data provides information about the location of nuclear plants all over the world. The information covered about the nuclear plants includes the region, country, the type of reactor, the year it was built among other information. It is interesting to me as I wanted to get an idea of the number and type of nuclear reactors that are built by countries around the world. Now that we are moving to a world that relies on renewable sources of energy, it is interesting to note that a lot of developed countries are relying on nuclear reactors for energy purposes. It was especially good to observe the most popular types of nuclear reactors in different countries.
This map showed me that the USA is heavily invested in the Nuclear reactors that are based on pressurized or boiling water. Most of these reactors are concentrated on the east coast of the USA. While Europe seems heavily invested in reactors as well, South America, Africa, and Russia are nowhere in comparison when it comes to the count of nuclear reactors. Overall, Pressurized water and Boiling water reactor are the most popular type of reactors all over the world.
The audience for my visualization are people who are interested in energy generation by nuclear reactors. From a quick glance, these people can get a quick understanding of the countries that have invested in this technology and the types of reactors they have invested in.
My process with building with CartoDB was hard initially because I was finding it hard to find datasets with latitude and longitude information. But ultimately, it was rewarding when I had finally developed the visualization. I wanted to have a dark visualization background hence I went with ‘Dark Matter’ as a basemap. I chose the category map layer as I knew I wanted to categorize the type of the nuclear reactors. I changed the color of some of the reactor types in Carto CSS to group similar reactors in the same color. I also customized the marker width according to the zoom of the map so that the user can easily view the nuclear reactor location while zooming in/out. I added labels and hover over functionality so that the Wikipedia link of the reactor and plant name could easily be viewed.

Visualization 2 – Analyzing the Hazard and Exposure rating of countries

For my second visualization, I wanted to identify the countries at a high risk of humanitarian crisis. I got the from the Humanitarian Data Exchange website that indexes humanitarian data for countries. The model is split into different levels to provide a quick overview of the underlying factors leading to humanitarian risk.
The model is based on risk concepts published in scientific literature and envisages three dimensions of risk: Hazards & Exposure, Vulnerability, and Lack of Coping Capacity. It is interesting to note and observe countries that are indexed safer than others for humans to live in.
The map shows that countries such as Mexico, Colombia among others have a high hazard and exposure rating whereas, Belgium and Netherlands are indexed lowest on the hazard rating. The audience for these visualizations is anyone who wants to analyze ‘high’ and ‘low’ risk countries to understand which countries are likely to get international assistance. These visualizations are important since the viewer gets a better understanding of countries that are struggling with crisis and disaster management efforts. The countries with a higher indexed can be targeted first to improve conditions of people residing there.
I chose to go with the Choropleth map layer as I wanted to depict the index range number with the color intensity. The buckets helped in easily distinguishing hazard index values for different countries. I modified the range of the intensity to have additional buckets for my visualization. The labels and hover over functionality provides the rank and index value of the country.