Publications

Weinstein, B.G., S. Marconi, S. Bohlman, A. Zare, A. Singh, S.J. Graves, E.P. White. In press. NEON Crowns: a remote sensing derived dataset of 100 million individual tree crowns. eLife. [OA, Preprint]

Marconi, S. S.J. Graves, B.G. Weinstein, S. Bohlman, and E.P. White. In press. Rethinking the fundamental unit of ecological remote sensing: Estimating individual level plant traits at scale. Ecological Applications. [OA, Preprint]

Weinstein, B.G., S. Marconi, M. Aubry-Kientz, G. Vincent, H. Senyondo, E.P. White. 2020. DeepForest: A Python package for RGB deep learning tree crown delineation. Methods in Ecology and Evolution. https://doi.org/10.1111/2041-210X.13472 [OA, Code, Preprint]

Weinstein, B.G., Marconi, S., Bohlman, S.A., Zare, A. and White, E.P., 2020. Cross-site learning in deep learning RGB tree crown detection. Ecological Informatics, p.101061. https://doi.org/10.1016/j.ecoinf.2020.101061

Weinstein, B.G., Marconi, S., Bohlman, S., Zare, A. and White, E., 2019. Individual tree-crown detection in RGB imagery using semi-supervised deep learning neural networks. Remote Sensing, 11(11), p.1309. https://doi.org/10.3390/rs11111309

Preprint

Weinstein, B.G., S.J. Graves, S. Marconi, A. Singh, A. Zare, D. Stewart, S.A. Bohlman, E.P. White. 2020. A benchmark dataset for individual tree crown delineation in co-registered airborne RGB, LiDAR and hyperspectral imagery from the National Ecological Observation Network. bioRxiv 2020.11.16.385088; doi: https://doi.org/10.1101/2020.11.16.385088

Graves, S., Gearhart, J., Caughlin, T.T. and Bohlman, S., 2018. A digital mapping method for linking high-resolution remote sensing images to individual tree crowns. PeerJ Preprints, 6, p.e27182v1. https://doi.org/10.7287/peerj.preprints.27182v1

Websites

Web Visualization of the NEON Crowns data of 100 million individual tree crowns http://visualize.idtrees.org

DeepForest Tree Predictions Demo. http://tree.westus.cloudapp.azure.com/trees/

Software

DeepForest: Python Package for Tree Crown Detection in Airborne RGB imagery. [GitHub, Documentation, Demo Website]