Bias-variance decomposition of errors in data-driven land cover change modeling

摘要

Careful model evaluation is essential for using the results of data-driven land cover change (LCC) models. A useful evaluation should help the analyst understand model behavior and improve model performance. Conventional error analysis methods provide limited insights on these two issues.