I don't know how effective the project was because I left before it finished but we were working on using the normalized difference vegetation index, normalized difference water index, and a bunch of other data points to try to predict crop yields.

Farmers might get that kind of stuff from flyovers for the extra resolution but that was cost prohibitive for our purposes except when validating data from the satellites.

Yeah good luck getting accurate NDVI measurements down to the square foot from satellites.

Luckily corn fields go on for miles so we didn’t need that resolution.

Fields vary wildly within relatively small spaces. Just because it looks uniform doesn't mean it is uniform.

Our 100 acre bottom field this year averaged 274 bushels of corn per acre. Some places were around 360, some were around 50.

If you're trying to predict crop yields to beat the market, granularity is wildly important.

This year in university I took a course where I had to imagine creating a startup and we ended up mocking up an agritech business that dealt with drones and satellites data. We discovered that Sentinel 2, a European satellite, has a resolution for ndvi that goes as low as 10/20m. This improves nasa's modis sitting at a resolution of ~250m.

Furthermore, this is free. There are companies providing paid images with higher resolution from their own satellites (Constellr comes to mind). I'm sure the resolution isn't going to be exact to the square foot, but for some cases you probably don't need such a high resolution