A data science challenge for converting airborne remote sensing data into ecological information.

ABSTRACT: Ecology has reached the point where data science competitions, in which multiple groups solve the same problem using the same data by different methods, will be productive for advancing quantitative methods for tasks such as species identification from remote sensing images. We ran a competition to help improve three tasks that are central to converting images into information on individual trees: (1) crown segmentation, for identifying the location and size of individual trees; (2) alignment, to match ground truthed trees with remote sensing; and (3) species classification of individual trees. Six teams (composed of 16 individual participants) submitted predictions for one or more tasks. The crown segmentation task proved to be the most challenging, with the highest-performing algorithm y

SUBMITTER: Marconi S 

PROVIDER: S-EPMC6397763 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature