Maps of forests allow us to know the locations of a variety of different tree cover types. However, forests change over time, and updating maps involves an expensive process of data collecting.

We answer two questions: Can we instead predict tree cover types just from geographical features?
And can we identify the most essential feature to prioritize when collecting data?

We answer these questions with machine learning algorithms and topological data analysis.