Data to replicate the experiment is available for download in two zipped files: "NEON_D17_TEAK_DP1QA_20170627_181333_RGB_Reflectance.zip" (Imagery) "CNN_LABELS_2019.zip" (Training Label Shapefiles) * Note: The imagery is 5.5 gb (zipped). All code used to run the analysis is located in a repository here: https://github.com/jonathanventura/canopy The only flightline you will need to repeat our results is called "NEON_D17_TEAK_DP1_20170627_181333". If you download your own NEON data, the raw HDF 5 files can be converted to a geotiff using R code found here: http://neonscience.github.io/neon-data-institute-2016//R/open-NEON-hdf5-functions/ Contact the National Ecological Observatory Network (NEON) to download the comparable imagery data files for all sites and collections: https://data.neonscience.org/home.

Digital Publication of the training data polygons and hyperspectral imagery used in the manuscript "A Convolutional Neural Network classifier identifies tree species in mixed-conifer forest from hyperspectral imagery". Code is available in a Jupyter Notebook and can be found here: https://github.com/jonathanventura/canopy National Ecological Observatory Network. 2018. Provisional data downloaded from http://data.neonscience.org on 22 June 2018. Battelle, Boulder, CO, USA