Over the past few years, machine learning techniques have been increasingly used to analyze the vast amount of data collected by the Landsat mission, which has been circling the globe for over 50 years. The data has been used to classify different types of land cover, detect changes to landscapes over time, and map the impact of human activity on the environment. With the field constantly evolving, researchers are developing new deep learning models to improve the accuracy and efficiency of the analysis and extract even more information from the data. Here are just a few examples of how the combination of Landsat data and machine learning is providing a better understanding of our planet's past, present, and future.

Music Credits:

“One Hundred Days” Florian Moenks[ GEMA ] Matthew Anderson[ PRS ] Volta Music
“Natural Response” Jonathan Elias[ ASCAP ] Sarah Trevinop [ASCAP] EVO
“Artificial Intelligence” Mateo Pagamici [SUISA] Max Molling [SUISA] Nuvotone Stratos

Credit: NASA's Goddard Space Flight Center/Scientific Visualization Studio
Chris Burns [KBRWyle]: Lead Producer
Chris Burns [KBRWyle]: Lead Writer

This video can be freely shared and downloaded at https://svs.gsfc.nasa.gov/14336. While the video in its entirety can be shared without permission, the music and some individual imagery may have been obtained through permission and may not be excised or remixed in other products. Specific details on such imagery may be found here: https://svs.gsfc.nasa.gov/14291. For more information on NASA’s media guidelines, visit https://nasa.gov/multimedia/guidelines.

If you liked this video, subscribe to the NASA Goddard YouTube channel: https://www.youtube.com/NASAGoddard

Follow NASA’s Goddard Space Flight Center
· Instagram http://www.instagram.com/nasagoddard
· Twitter http://twitter.com/NASAGoddard
· Twitter http://twitter.com/NASAGoddardPix
· Facebook: http://www.facebook.com/NASAGoddard
· Flickr http://www.flickr.com/photos/gsfc