New paper and two blogs asking "how much data is enough?"

My new paper (Impact of satellite imagery spatial resolution on land use classification accuracy and modeled water quality) is essentially an analysis for the Camboriú water fund of how the choice of input data impacts the decision you'd make as a result. We compared a relatively quick analysis on free 30 m resolution data to a more complex analysis using 1 m data. I'd recommend most people skip most of the paper (which is quite technical) and skip to the discussion, or even the two blogs I wrote about it.

The first blog explains the overall project and the paper at a high level here:
Camboriú Conservation Field Test: How Much Data is Enough?

I also wrote a second blog aimed specifically at people who actually do spatial analysis to guide them in picking the right source of remotely sensed imagery:
How much data is enough? Investigating how spatial data resolution impacts conservation decision making

In short, we found that the simpler analysis would have led us to the same decision in Brazil, but that for other water funds the choice of data could be critical. The return on investment was over 1 with 1m data, but below 1 with 30m data, meaning if financial return was the dominant factor this distinction would be critical.

Table 5 and the discussion have several guidelines to consider in how to select whether relatively low or high resolution data is most appropriate for a given context. I'm pretty excited about that part of the paper, and I'd really welcome feedback on it from anyone so inclined.