Lesson 1Unstable Inputs and Model DriftHow small changes in data or assumptions can destabilize spatial models over time.Start2 Micro-lessonsMicro lesson 1Assumption Drift in Dynamic EnvironmentsMicro lesson 2Overfitting to Recent Data
Lesson 2Scaling and Hidden Feedback LoopsWhen scaling up spatial models, hidden feedbacks can amplify errors or create new risks.Start2 Micro-lessonsMicro lesson 1Scaling Up: Compounding Small ErrorsMicro lesson 2Hidden Feedback: Self-Fulfilling Maps
Lesson 3When Not to Model: Recognizing LimitsKnowing when spatial modeling adds confusion or risk instead of clarity.Start2 Micro-lessonsMicro lesson 1Recognizing When Not to ModelMicro lesson 2Withdrawing the Model: Accepting Uncertainty