Our Planet

Charts & Graphs, Final Projects, Maps, Visualization


Agriculture is the practice of science and farming, including the cultivation of soil for the growing of crops and the raising of livestock for human consumption. You are probably thinking, “Hmm well if this is what agriculture is, then this is good, right? Since people are being provided with food.” The answer to this is both yes and no, if agriculture continues to rise then so does the levels of CO2 emissions on our planet.

David Attenborough aka Father Nature released a documentary on Netflix called A Life On our Planet. David, who is 95 years old, dedicated his entire life to studying our natural world. In this documentary he expresses and stresses his concerns by mapping out for the viewers his observations on what he has noticed happening on our planet from the time he’s been here. He is also very optimistic for our future, and tells us how we can coexist with what we have taken advantage of.     

For my final project I’ll be showing the meat consumption rate from 7 highly populated countries. My primary focused countries are Australia, Brazil, Canada, China, India, Russia, and America. My visuals focus on these countries, along with their population, and the CO2 emissions that these countries release from grazing alone. 


The term “Industrial Agriculture” is known to be the primary system for food production mainly in places of high population. Industrial agriculture is a type of farming that raises grazing animals and cultivates large numbers in high density environments. Modern technology is used to enhance organisms’ growth and plague illnesses and decrease the death rate of livestock, to bring about large numbers of meat on a mass scale. Cattle, Pigs, and Poultry consist of livestock, they are the organisms that are affected by rapid reproduction and weight gain. 

People such as investors and business owners consider industrial farming to be one of the worlds greatest innovations. Why? Because their pockets are fed while they’re asleep. Others believe that this practice is both harmful to our environment, as well as to the health of both humans and animals. We do need to eat in order to survive, some of us hunt and the rest of us go to grocery stores. 

Now, you have several agricultural farms in a country, housing livestock. Each animal has the same normal digestive system, and are living in high density living areas. You have to ask yourself, is that safe? The short answer is no, why you ask, we have hundreds, even thousands of organisms living in factory farms. Each one produces an immense amount of waste that harms our atmosphere known as GHG (Green House Gases). The gas that these organisms release is known as CH4 (Methane). In the US 10% of GHG emissions come from agricultural farming. The ball is in our court, we can continue to help support agricultural farms, or you can make the decision to use other alternatives such as hunting for your own food or creating a micro farm on your own property and raising your own quality meat, eggs, milk, and more.  

 According to the EPA in the USA as of 2018 10% of CO2 emissions came from agriculture. Combined with Transportation, Electricity, Industry, Commercial and Residential the total amount of CO2 emitted from the USA was 6, 677 million metric ton. A million metric ton is equivalent to 2.2 billion pounds. Grazing animals produce NH4 known as Methane, which is a part of their normal digestion process. 


When searching for data I used Kaggle and Our world in data. Link to data ⇒ Meat Consumption, and Data on CO2 and Green House Gases. The first data set Meat consumption covers information such as Country, Meat Type, Meat Consumption Measure, Year, and Value. The second covers Country, Year, Population, and Methane. The second dataset covers much more but those are the only sets I needed to focus on to make my visualizations.

Now that I had all the data I needed to complete my visualization it was time to get to work on my visuals. To be fair, at first I didn’t know how I wanted my data to look, or how it should look. I did find some inspiration through Tableau’s Gallery.  

UX Research

For user research I chose Remote User Testing. Remote user testing is a method of remote research for participants as they interact with your product or experience in their natural environment—at home, in their office, or a specific location. I had my user first answer a Pre – Test Questionnaire, then gave them a scenario, along with a task. The participants feedback was then reviewed and used to help make a better visualization 

Pre – Test Questionnaire

  1. What is your occupation?
    • Data Scientist (Healthcare Industry)
  2. Please Describe your background, experience, or interest in design? 
    • Passing interest in design as related to Analytics decks, and how to make them approachable to less Analytics-savvy audiences (less is more + memes)
  3. Please describe your background, knowledge, or interest in climate change?
    • I worked on an NSF-funded project meant to research the power of figurative framing as relates to advertising for climate change (undergrad psychology department) 

Scenario: You are a high school science teacher. The topic you are teaching in class the next day is climate change and the causes. Your main focus is showing how agriculture of grazing animals such as Sheep, Cows, Pigs, and Chicken is a big part of CO2 emissions on the rise. You want to know which country contributes the most CO2 emissions based on the consumption of grazing animals. 


1. Go to youtube.com in the search bar type “livestock create major methane problem” 

– Click on the first video from Discovery

2. Explore the graph. Link to Graph

3. Find the following information from the graph:

– Which country consumes the most pig? China?

– Which country consumed the most chicken? USA?

– Which country consumes the least amount of sheep? China?

Post Test Questionnaire: 

  1. What are your overall impressions of the dashboard? 
    • The overall impression is visually appealing, but misleading upon further inspection
      • The colors are misleading; they don’t seem to add value to the visualization. In fact, they confuse me, because when I try to follow one line horizontally across the plot, it gets lost in a tangle of overlapping gradients. It seems like the color is determined by the data point’s x-axis value, which is not only superfluous but actively misleading.
    • HOWEVER, the size of the nodes reflecting the y-value axis (amount) is not bad at all. It’s a compounded, redundant effect, but not bad. Can be perceived as fun once color issue is fixed. 
  1. How did completing the task on the dashboard make you feel? 
    • It was hard to complete it because of the misleading coloring. So it made me feel frustrated 🙁 The only reason I managed to ascertain the right answers was thanks to the detailed information box that appeared when I hovered over a specific node. 
  2. If you could change anything about the dashboard, what would it be and why? 
    • The coloring of the individual graph lines (type of animal) is terribly misleading. Colors should help us distinguish elements in the visualization, i.e. a different color for each line and/or a gradient for that color that reflects the y-axis value perhaps. 
      • The audience should be able to trace individual graph lines (type of animal) with no trouble. So maybe make the edge/line part (as opposed to the node part) a particular color for a particular animal 
      • Individual nodes should reflect solid colors, which reflect specific countries
      • X-axis county categories should be ordered in some fashion; maybe from smallest to largest population, so that the audience can get a sense of human vs animal population per country.
  3. Would you recommend this dashboard to others who are interested in this topic? 
    • No. Only if the color problem was addressed. 

Findings from participant

  1. Colors were misleading/confusing
  2. Detail box was the only helpful thing
  3. Individual graph lines are misleading and confusing
  4. Colors should help distinguish elements in visualization 
  5. Nodes should be a different color as well

Findings from professor (feedback) – was not a user tester

  1. interesting opportunity here to use symbols/colors that are intuitive for each type of meat
  2.  let’s not connect those countries with a line, since they could be put in any order. Bars or maybe stacked bars (with color for meat type) would be an interesting alternative to try.
  3. consider normalizing — maybe % of meat type by country, or dividing those figures by population


As a designer I really considered the feedback that was given to me. I wasn’t feeling 110% about the first visualization. Also as a designer I work better when I receive constructive criticism. Based off the findings from my user research participant and professor I took their suggestions and went back to the drawing board. 


Based on the feedback received from my user test and professor. I wanted to make my visual as clear as possible. The feedback I also received from my user test participant was that my visual should be so simple that a kindergarten student can understand it. I first had only one visual, and after my feedback I created three. 

  1. Stacked Bar Graph 
  2. Line Graph 
  3. Map Graph

First Visual

Orginal Line Graph

This was the first graph that I created. Playing with the measure and Values until I saw something that was visually beautiful. As you can see this line graph looks beautiful but it was hard for users to follow and understand the information I was trying to display.

Final Visuals

Stacked Bar Graph

The stacked bar graph idea was much better than what I tried to show in the line graph. Information is more clear and understandable. Colors were not misleading and confusing, also the colors helped the viewer distinguish the elements in the visualization.

Line Graph

The line graph was added so viewers can see what the population increase in these countries looks like.

Map Graph

The map helps viewers with understanding how much CO2 is being emitted into the atmosphere from each country’s agricultural sector.

Final Dashboard


To view/interact with my final visualizations click here! What I wanted from this was a visual that was informative and relevant to what’s important right now, for our future. All the information that viewers need is right here. We can’t ignore science when it’s being presented and visualized, anyone can look at these visualizations and see who each visual correlates and intertwines with one another. This can be used in classrooms, documentaries, and textbooks. Now more than ever our planet needs us, and we need it.


For this visualization I had to really buckle down and think about what I wanted to show, who I wanted to share this with, and to put myself in the shoes of the viewer. In order to achieve this visual I had to have empathy. I had to put aside my emotions and focus on my viewers, and trust in the data to get me there. This final project meant everything to me, I proved to myself that I can do anything that I put my mind to. Along, with gaining knowledge and inspiration from my peers and professor. I was hesitant about doing my first final project by myself but this opened the door to confidence within myself. I pushed through and preserved. In addition to this final project report I would like to turn this into an actual poster board that can be used in schools. Nature has been a part of me since I was in the fourth grade, for as long as I could remember I had a passion for animals. In my undergrad I remember my professor asked what I wanted to do with an environmental studies degree. I responded, “I want to merge it with some form of visual art”. I was able  to do that in this report and I’ll be forever thankful.

People must feel that the natural world is important and valuable and beautiful and wonderful and an amazement and a pleasure. – David Attenborough 


Our World In Data

Mossy Oak