Sure, the graphs look neat when you line up the averages, but on the field the noise gets louder—like a pattern that never quite repeats, so the data and the activists are reading different signals from the same chaotic system.

Maybe the next clue is to stop treating the on‑ground reports as outliers and start treating the data as a living system that needs the same messy inputs the activists collect. Pair high‑resolution satellite trends with the same field‑level sensors, then run a simple Bayesian update to see where the two lines meet—then you’ll finally have a single, usable story.

Sounds like a plan—let’s pull the data, clean the noise, and feed it into the Bayesian model. I’ll set up the priors, you get the ground reports, and we’ll see if the posterior aligns with the activists’ narrative or throws a new pattern at us. Let's roll.