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.

Above the Earth, Below the Surface: Landsat’s Role in Monitoring Water Quality
Safeguarding freshwater resources is crucial, and while scientists use a variety of ground-based techniques to gauge water quality, the Landsat program has provided water quality data from orbit for decades.