Temporal Integrity

Temporal integrity matters when you use EO products for monitoring, alerting, or training predictive models. If a product uses future observations to fill earlier gaps, it can look cleaner but it can also leak information backward in time.

That leakage can inflate accuracy in retrospective evaluations and cause models to fail in real deployment. It can also create unrealistic change patterns that never could have been known at the time.

If you need real-time behavior, check whether the product is strictly causal (past-only) or whether it is a retrospective reconstruction that may incorporate future data.