Trees cover a large part of the earth and can sometimes be quite annoying when you are trying to classify any other land cover than forest. In my case I was looking for a dataset I could use to mask out the forest areas so I don’t have to worry about them producing false positives in my classification therefore making the whole process simpler, faster and more accurate. Unfortunately there aren’t a whole lot of options to choose from if you are looking for something global with a resolution not less than MODIS (250m). One quite prominent and easy to use dataset is the Global Forest Change 2000 - 2013 by Hansen et al.. The problem now is: How do you get such a large dataset into an easy to use vector dataset?