Sorry that it’s been so quiet on the blog this summer. We’ve been busy analyzing all the data you have helped produce and we’ve written and published the first Season Spotter paper!
In the paper, which was published in the science journal Remote Sensing, we describe the project and the data produced, and we show that the data is of good quality and useful. You can read the abstract (scientific summary), the whole paper, or a plain language summary I wrote about the paper. And you can find yourself on our list of contributors.
We now know which type data from Season Spotter is good quality and we have created the post-processing software to turn your classifications into that data. We have also learned what doesn’t work so well (e.g. identifying grass seedheads) and what has been less than ideal (e.g. not taking advantage of the fact the images are in sequences).
So we’ve got two major next steps:
- We’re going to revamp the classification interface. When we launched in July 2015, the Zooniverse Project Builder was still pretty simple. Now it’s more sophisticated and I think we can make many of the classification tasks much more efficient by asking questions about multiple images at a time, instead of just one or two at a time. To create the new classification interface, I’d love to have your feedback. I’ve put together a project called Season Spotter Sandbox, where we can try out different ways of doing classifications. Tell me what you like and what you don’t like in its attached Talk forum.
- We’re going to identify the science question(s) we’d like to address next with Season Spotter data. I’m personally leaning towards tree-circling classifications, so we can figure out how to connect different types of phenology data at different scales. In other words, we have data from ground observers, from PhenoCams, and from satellites, but it’s not always clear how to use them together. If we could calculate individual tree phenology from the PhenoCam images, we could connect the first two. But there are other possibilities. If you have questions you think we should ask with the Season Spotter data, please leave a comment below.
Thank you again for all your classifications. I’m looking forward to the next season of Season Spotter.