This session explores methods of error assessment and error propagation in Land Change Science. Error assessment compares predictions to reference information. Propagation analysis quantifies how classification errors in land cover maps become magnified or muted in subsequent products. Conventions exist in various sub-fields, such as Remote Sensing and Simulation Modeling. Some conventions apply inappropriate metrics or poorly structured sampling designs, and may fail to account for various types of errors, such as those within the labels to train image classification. Other conventions have yet to address features in new data formats, such as object-oriented image analysis. The profession needs novel methods given new technologies, such as Virtual Globes and interfaces that allow volunteered information. This session focuses on methods to address existing challenges and to establish future practices.