A remote sensing derived data set of 100 million individual tree crowns for the National Ecological Observatory Network

• DOI: 10.7554/elife.62922
• Publication Date: 2021-02-19T13:01:34Z
• Authors: Ben G Weinstein; Sergio Marconi; Stephanie A Bohlman; Alina Zare; Aditya Singh; Sarah J Graves; Ethan P White
• Keywords: Tree canopy; Tree (set theory); Data set

Forests provide biodiversity, ecosystem, and economic services. Information on individual trees is important for understanding forest ecosystems but obtaining individual-level data at broad scales challenging due to the costs logistics of collection. While advances in remote sensing techniques allow surveys unprecedented extents, there remain technical challenges turning sensor into tangible information. Using deep learning methods, we produced an open-source set crown estimates 100 million 37 sites across United States surveyed by National Ecological Observatory Network’s Airborne Observation Platform. Each canopy tree represented a rectangular bounding box includes information height, area, spatial location tree. These have potential drive significant expansion research facilitating both regional analyses cross-region comparisons encompassing types from most States.