Computer Science: Images of Arctic ice

Haiyan Cheng, Willamette; Penny Rowe, NorthWest Research Associates; and Steven Neshyba, University of Puget Sound

Author Profile
Initial Publication Date: August 3, 2023


Students learn image-processing techniques and apply them to images of the Arctic in this intermediate-level module. They learn about climate change and its impacts on melting of polar sea ice, and explore satellite-based images of the polar regions. Students download a satellite-based image of the Arctic and learn about how images are stored, apply image-filtering techniques such as noise removal and edge detection, and explore scene identification using true- and false-color images.

Used this activity? Share your experiences and modifications

Learning Goals

  1. Learn about images of Arctic sea ice taken by the MODIS instrument.
  2. Examine annual and long-term trends in Arctic and Antarctic sea ice.
  3. Understand how images are stored and represented in Python and how to load, resize (crop), and save an image.
  4. Learn how to convert a color image to a black and white image and how to extract the red, green, and blue components from an image.
  5. Apply colormaps to an image.
  6. Know how to use median filtering to remove noise from an image.
  7. Be familiar with how to use the function "medflt" from scipy's signal processing module.
  8. Apply Edge Detection to detect the sea ice edge.
  9. Gain experience with true and false-color images.

Context for Use

This activity is designed to be used in an upper-level Computer Science course. Students must have in-class access to computers with internet access and with Jupyter Notebook installed. A computer lab with pre-loaded software can be used or, as in successful pilots, students can download the software onto personal laptops before class (instructions are provided). Problems can be mitigated by having students work in pairs and having an extra laptop or two available as needed, equipped with the software. The activity has successfully been taught in both classes and lab sections of 11 students or less, and is appropriate for up to 30 students. Application in large classes can be fostered by additional support, if available; e.g. through teaching assistants. The activity typically takes 3 to 5 hours and includes homework assignments. No previous computational or coding experience is required. The instructor will give an introductory lecture on the image-processing concepts, assign pre-module homework, guide the students in working through the module, and facilitate group discussions. The module is adaptable – either of the parts can be used or modified.

Description and Teaching Materials


In this module, students work actively with polar data through computer programming in Jupyter with Python. The instructions and notebook are designed so that no prior coding experience is necessary on the part of the student. The notebook and all other materials needed to implement the activity are provided below. The following describes materials, instructor preparation, and the workflow of student activities.


  • Student materials ( (Zip Archive 22.3MB Aug3 23). After unzipping, this includes:
    • arctic-ice-images-1.ipynb
    • arctic-ice-images-2.ipynb
    • arctic-ice-images-3.ipynb
    • finding_moving_files_mac.docx, finding_moving_files_pc.docx: File management on your computer
    • installing_running_jupyter_mac.pdf, installing_running_jupyter_pc.pdf
    • Introduction_to_python3.ipynb: Python3 tutorial, to be run in Jupyter Notebook
    • input: a folder with additional material the student will need:
      • august9_arctic_worldview_500mres.jpg
      • IceImage.jpg
      • IceImage2.jpg
      • N_198111_extn_v2.1_edited.png
      • Willamette_colors.png
      • Willamette_colors2.png
      • WillametteMap
      • WillametteMapInd
  • Assessment materials ( (Zip Archive 11.3MB Aug3 23). After unzipping, this includes:
    • arctic-ice-images-1-key.ipynb
    • arctic-ice-images-2-key.ipynb
    • arctic-ice-images-3-key.ipynb
    • rubric.pdf
    • my-images: a folder with additional material needed to run the keys
      • myImage.jpg

Instructor Preparation

1. Download the materials above and unzip all zipped files.
2. Work through the student tasks in the workflow below.
3. Compare the completed notebooks to the provided keys and compare answers to those in the rubric (see Assessment).
4. Modify the notebooks as desired and/or include only a portion of them.


  1. The instructor makes the Student Materials available to students on the platform used by their institution. To use the files in Jupyter, students will need to keep all files in the Student Materials in the same directory on their computers.
  2. Students work through the setup guides. They follow the instructions for installing Jupyter on a Mac or PC and work through Introduction_to_python3.ipynb in Jupyter. (Alternatively, the instructor ensures the software is available in a computer lab that will be used). Students then follow instructions for finding and moving files on a Mac or PC. These tasks have been found to bog down class time for students who are not experienced in them, so we suggest assigning them as homework and reserving some class time afterward to follow up as needed.
  3. Optionally, the students watch climate change videos to help transition to the topic (see Reference and Resources below).
  4. Students work through each notebook. After each, the instructor brings the class together for a group discussion about the "Pause for Analysis" questions.
  5. After the final notebook, the instructor brings the class together for a final wrap-up.

Teaching Notes and Tips

Computer lab vs personal laptops

While students can use a computer lab or work on individual laptops, we suggest the latter. Installing Jupyter Notebooks on laptops is straightforward, gives the students a valuable experience, and allows them to complete work at home, if needed. Furthermore, the student has the computational tool available to them after completion of the activity.


Successful completion of the CGI module is expected to be indicative of meeting the learning objectives. Assessment includes in-class assessment of the module as students work as well as grading of completed notebooks and Pause for Analysis responses. A rubric for the Pause for Analysis questions and keys to the Jupyter notebooks are provided.

References and Resources

Climate change videos:

  • Climate Change: Lines of Evidence, from the National Academies of Science, Engineering and Medicine. Options include a 26 minute video or any of 7 videos of about 4 minutes each. To allow for varying levels of available class time, video content was ranked as follows, from most to least relevant:
    • Chapter 1: From the 18 second mark to the 1 minute mark
    • Chapter 3
    • Chapter 5 (8 minutes total).
    • Chapters 1-5 (about 20 minutes).
  • Climate Change in 60 Seconds from The Royal Society.
  • Effect of climate change on hurricanes, by Vox, 3 minutes 22 seconds.