Ice, Ice Baby

Posted on May 16, 2016

Contributed by Wanda Wang. She  is currently in the NYC Data Science Academy 12 week full time Data Science Bootcamp program taking place between April 11th to July 1st, 2016. This post is based on her second class project - R Shiny (due on the 4th week of the program).


As the world's air conditioning unit, Glaciers keep our temperatures in check; they are the harbinger of climate change. To visualize the locations of our glaciers, and their dangerous negative progression, we will utilize a Shiny application to further explore this glaciological picture.

The Datasets

Data was retrieved from the World Glacier Monitoring Service(WGMS) and the Global Land Ice Measurements from Space(GLIMS). The GLIMS glacier database generously provided the geographic outlines of around 200, 000 unique glaciers. An active scientific collaboration network currently compiles the annual mass balance data for WGMS.


The expansive reach of glaciers on our planet is simply astounding. Here, we can visualize their specific geographic locations and name information by using Leaflet as a coordinate-friendly tool:

Screen Shot 2016-05-15 at 11.26.28 PM

Indicatively, glacier mass balances are highly sensitive to climate change, in the past and in the present. Mass balance is the difference between accumulation and ablation of a glacier. Various glaciers can be examined through selection the name dropdown in the Map tab of the Shiny application.

To examine the mass balance depletion over time, we can access an animation over time, representing the negative change, on a colored scale.

As an example, for the Freya Glacier located in Northeast Greenland, we can compare 2008 vs. 2014:

Screen Shot 2016-05-15 at 11.32.55 PMScreen Shot 2016-05-15 at 11.33.12 PM

The lighter color in 2014 represents the mass depletion over time. A perspective of urgency is meant to visually alarm.

To access the numerical mass balance measurements - the Time Series tab of the Shiny app allows the visualization of the negative trend over time for the desired location:

Screen Shot 2016-05-15 at 11.38.19 PM



Variables including temperature and sea levels will be included in the following update for this project. Additional glacier characteristics (elevation point,  altitude, shape) will also be further examined.

About Author

Wanda Wang

Wanda is excited about combining data science with compelling narratives to uncover new enterprise opportunities. With 5+ years of experience in the Investment Management field, including at both Citigroup and JPMorgan - Wanda thrives in demanding, client-driven environments...
View all posts by Wanda Wang >

Related Articles

Leave a Comment

No comments found.

View Posts by Categories

Our Recent Popular Posts

View Posts by Tags

#python #trainwithnycdsa 2019 2020 Revenue 3-points agriculture air quality airbnb airline alcohol Alex Baransky algorithm alumni Alumni Interview Alumni Reviews Alumni Spotlight alumni story Alumnus ames dataset ames housing dataset apartment rent API Application artist aws bank loans 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 boston safety Bundles cake recipe California Cancer Research capstone car price Career Career Day citibike classic cars classpass clustering Coding Course Demo Course Report covid 19 credit credit card crime frequency crops D3.js data data analysis Data Analyst data analytics data for tripadvisor reviews data science Data Science Academy Data Science Bootcamp Data science jobs Data Science Reviews Data Scientist Data Scientist Jobs data visualization database Deep Learning Demo Day Discount disney dplyr drug data e-commerce economy employee employee burnout employer networking environment feature engineering Finance Financial Data Science fitness studio Flask flight delay gbm Get Hired ggplot2 googleVis H20 Hadoop hallmark holiday movie happiness healthcare frauds higgs boson Hiring hiring partner events Hiring Partners hotels housing housing data housing predictions housing price hy-vee Income Industry Experts Injuries Instructor Blog Instructor Interview insurance italki Job Job Placement Jobs Jon Krohn JP Morgan Chase Kaggle Kickstarter las vegas airport lasso regression Lead Data Scienctist Lead Data Scientist leaflet league linear regression Logistic Regression machine learning Maps market matplotlib Medical Research Meet the team meetup methal health miami beach movie music Napoli NBA netflix Networking neural network Neural networks New Courses NHL nlp NYC NYC Data Science nyc data science academy NYC Open Data nyc property NYCDSA NYCDSA Alumni Online Online Bootcamp Online Training Open Data painter pandas Part-time performance phoenix pollutants Portfolio Development precision measurement prediction Prework Programming public safety PwC python Python Data Analysis python machine learning python scrapy python web scraping python webscraping Python Workshop R R Data Analysis 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 seafood type Selenium sentiment analysis sentiment classification Shiny Shiny Dashboard Spark Special Special Summer Sports statistics streaming Student Interview Student Showcase SVM Switchup Tableau teachers team team performance TensorFlow Testimonial tf-idf Top Data Science Bootcamp Top manufacturing companies Transfers tweets twitter videos visualization wallstreet wallstreetbets web scraping Weekend Course What to expect whiskey whiskeyadvocate wildfire word cloud word2vec XGBoost yelp youtube trending ZORI