An Exploration of Satellites

Posted on Jul 29, 2018

Link to the Shiny app.


For my first shiny project, I was curious to explore this data set on the active satellites in orbit that I found on Kaggle. I wanted to learn about which countries use what satellites, what do we use satellites for, and where do we put the satellites in orbit? Here's what I found out.

Satellites by Country

Looking in the Map tab of the Shiny app, the first thing we notice is that the United States operates by far the most satellites. More than three times as many as China, the country that operates the second most. However, if we restrict to satellites run by military or government bodies launched within the last ten years, now China operates the most satellites, with USA second and Russia a close third. This is not so surprising given the different economic systems and rapid growth of the Chinese economy in recent years.

Purpose of Satellites

In the Purposes tab of the Shiny app, we see that more than half of all satellites are used for communications. If we restrict to the last 10 years though, we see that Earth Observation makes up significantly, and even overtakes communications as the primary purpose for non-commercial satellites. Digging deeper, I suspect that this is due to the fact that geosynchronous orbits are mostly used for communications, whereas low earth orbit is mostly used by earth observation, as we will see later. Geosynchronous orbits are more expensive to attain, so their satellites tend to have longer service lives.


Within the Orbits tab of the Shiny app, we see the big categories for orbit class are low earth orbit and geosynchronous orbit, with medium earth orbit and elliptical orbits being minor categories by comparison. As was said earlier, geosynchronous orbits are dominated by communications. This is not surprising since satellites in geosynchronous orbit always have line of sight with the same part of the earth. Earth observation is the top category in low earth orbit. Again not surprising since these satellites are mostly used for imaging and meteorology. The more interesting feature is that medium earth orbit is mostly occupied with satellites for navigation. Digging deeper, it turns out that these are mostly satellites for global positioning. Without diving too deep into how global positioning systems work, I do know that you need need line of sight to three or four satellites for the system to work. I suspect that despite being more expense to put the satellites in medium earth orbit, it is still more economical to do so since fewer satellites are required for the system to work at higher orbits.

Did you find something interesting within the Shiny app? If so, leave a comment about it below.

Link to the Shiny app.

Github link.

Link to Kaggle data set.

About Author

Simon Joyce

I grew up in Ireland, where I earned my BSc. and MSc. in Mathematics from NUI Maynooth. Then I moved to America where I earned my PhD. in Mathematics from Binghamton University. I taught college mathematics for roughly...
View all posts by Simon Joyce >

Leave a Comment

No comments found.

View Posts by Categories

Our Recent Popular Posts

View Posts by Tags

#python #trainwithnycdsa 2019 airbnb Alex Baransky alumni Alumni Interview Alumni Reviews Alumni Spotlight alumni story Alumnus API Application artist aws beautiful soup Best Bootcamp Best Data Science 2019 Best Data Science Bootcamp Best Data Science Bootcamp 2020 Best Ranked Big Data Book Launch Book-Signing bootcamp Bootcamp Alumni Bootcamp Prep Bundles California Cancer Research capstone Career Career Day citibike clustering Coding Course Demo Course Report D3.js data Data Analyst data science Data Science Academy Data Science Bootcamp Data science jobs Data Science Reviews Data Scientist Data Scientist Jobs data visualization Deep Learning Demo Day Discount dplyr employer networking feature engineering Finance Financial Data Science Flask gbm Get Hired ggplot2 googleVis Hadoop higgs boson Hiring hiring partner events Hiring Partners Industry Experts Instructor Blog Instructor Interview Job Job Placement Jobs Jon Krohn JP Morgan Chase Kaggle Kickstarter lasso regression Lead Data Scienctist Lead Data Scientist leaflet linear regression Logistic Regression machine learning Maps matplotlib Medical Research Meet the team meetup Networking neural network Neural networks New Courses nlp NYC NYC Data Science nyc data science academy NYC Open Data NYCDSA NYCDSA Alumni Online Online Bootcamp Online Training Open Data painter pandas Part-time Portfolio Development prediction Prework Programming PwC python Python Data Analysis python machine learning python scrapy python web scraping python webscraping Python Workshop R R language R Programming R Shiny r studio R Visualization R Workshop R-bloggers random forest Ranking recommendation recommendation system regression Remote remote data science bootcamp Scrapy scrapy visualization seaborn Selenium sentiment analysis Shiny Shiny Dashboard Spark Special Special Summer Sports statistics streaming Student Interview Student Showcase SVM Switchup Tableau team TensorFlow Testimonial tf-idf Top Data Science Bootcamp twitter visualization web scraping Weekend Course What to expect word cloud word2vec XGBoost yelp