Geomorphologists have more data and computational resources available than ever before, but lack tools to facilitate collaborations needed to integrate data from different modes of study (e.g., field, experimental, modeling). In this article, we discuss challenges to collaboration in geomorphology, and report a new schema for sharing data. The sandsuet schema is designed to accommodate most kinds of rasterized geomorphology data, and makes it easy to package, publish, and share those data.

The use of new artificial intelligence (AI) techniques to learn how landscapes evolve is demonstrated. A few “snapshots” of an eroding landscape at different stages of its history provide enough information for AI to ascertain rules governing its evolution. Once the rules are known, predicting landscape evolution is extremely rapid and efficient, providing new tools to understand landscape change.

pyTopoComplexity is an open-source Python tool for multiscale land surface complexity analysis. Applied to a landslide-affected area in Washington, USA, it accurately identified landform features at various scales, enhancing our understanding of landform recovery after disturbances. By integrating with Landlab’s landscape evolution simulations, the software allows researchers to explore how different processes drive the evolution of surface complexity in response to natural forces.