Chapter two developed an algorithm for mapping tree species using airborne earth observation technologies, which was published in PeerJ: https://t.co/03TNUTMYsf https://t.co/VvePAQjufx
The best results for species classification were achieved by @earth_chris (team StanfordCCB), who's algorithm correctly classified 92% of stems and performed well for both common and rare species https://t.co/XmK9rilMCZ https://t.co/HcOitApObP
@TrevorCaughlin @sj_graves @C_barberab @JuanMi_Requena @andriizayac @aroopsind @thePeerJ @NEON_sci thanks for the shout out, @sj_graves! If you're interested in the paper, @TrevorCaughlin, you can find it here: https://t.co/oJ6TN40qmh
Happy New Year, we can map #trees from airplanes now! Chris Anderson lays out a method for identifying tree species using airborne remote sensing. Extra plus: it’s #OpenSource & designed for publicly available data: https://t.co/AqIhUJx5yB #NatCapHighlight2018 #YearInReview https://t.co/gsEVUoQGES