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.
![Natural-color Landsat 8 image of an algae bloom in Lake Erie. The bloom appears green and contrasts with blue water.](https://landsat.gsfc.nasa.gov/wp-content/uploads/2024/07/erie_oli_2017269-1024x576.jpg)
Be Part of What’s Next: Emerging Applications of Landsat at AGU24
Anyone making innovative use of Landsat data to meet societal needs today and during coming decades is encouraged to submit and abstract for the upcoming “Emerging Science Applications of Landsat” session at AGU24.