This analysis reminds me of the big interest in the use of hyperspectral imaging for agriculture. The idea was the greater spectral resolution (greater than Landsat) would result in more interesting information. Agriculture was one of the applications. But, once you did find the interesting stuff, you no longer needed a hyperspectral sensor. You could just look at one spot with a much lower cost sensor.

So hyperspectral, like big data, is useful up front. But in the end, much simpler tools and algorithms will solve the problem on a continuing basis.