Millions of pixels are created every day. We believe that millions of new pieces of music can be generated to allow a wider audience to appreciate the vast treasure trove of satellite data we have available today.
SongSAT is a global award-winning tool to share the beauty of the world in different mediums, expressing the wonders of satellite imagery through audio. This allows the beauty of satellite imagery to communicate to an audience with visual impairments to enjoy the wonders of the world from above too, or to be used by musicians to aid with musical writing blocks.
Our team produced an algorithm, SongSAT, to convert five distinct geographical areas (Arctic, Grasslands, Forest, Coastal/Water areas, and Mountainous regions) into songs with distinct, recognizable musical patterns that play back using MIDI.
SongSAT determines the most common landcover type in a LandSAT image to determine what style of music it generates.
For instance, if an image is mainly covered with agricultural fields and a small lake, SongSAT will translate the
image into rural-themed music. This is achieved by translating each pixel's (the small squares that make
up an image) digital number into notes. This process takes the remainder of the pixel's digital number (0-255) divided by the
number of notes in a scale. Hence, if the theme uses a C major scale, it would divide the pixel value by 8 and
take the remainder. If the remainder is 0, it would play a C. If the remainder is 1, it would play a D,
and so forth.
These generated outputs are converted into playable sheet music, which is then brought into a music software that can play the music back.
We're proud to announce that this algorithm is 100% open source, and you can view the code at: http://github.com/mcvittal/SongSAT
If our team chooses to pursue improving SongSAT, the next thing to do would be to add the remaining land classification themes to allow for global coverage of SongSAT, and to add more rhythm options to the songs to make it feel a bit less monotonous and repetitive, and possibly add in multiple sections to the songs generated. After these key parts to it are improved, the next step after that would be to make the program more user-friendly and accessible so that anyone can install and run it, or make it into a proper web application that generates the music on the fly.
Interested in learning more or having a chat with the team? Using the music from SongSAT for a project? We'd love to get in touch! Shoot us an email at firstname.lastname@example.org, and we'll get back to you shortly.
Graduated from the University of Waterloo's Faculty of Environment specializing in Geomatics. He now works full-time at SkyWatch Space Applications Inc. as a Platform Developer on the Image Processing Engineering team, designing cutting-edge remote sensing algorithms. In his spare time, he enjoys bicycle touring and writing music.
Expected to graduate from the University of Waterloo in August 2019. He is currently studying Geomatics as a major, with a minor in Computer Science. He has gained technical skills through working at the University of Waterloo (Mapping, Analysis, and Design Lab), York Region Planning department, and City of Toronto. He enjoys cooking and challenging himself in his free time.
Expected to graduate from the University of Waterloo in August 2019. She is currently pursuing Geomatics as a major, with a minor in Computer Science. During her studies, she has gained developer experience from working at CIBC, York Region, CGI, and Scotiabank. She hopes to pursuit a career in front-end development.