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Deep learning models for classifying land cover types - used for aspen identification

This set of code generates predictive multiclass models of cover distributions based on VSWIR apparent surface reflectance collected by the NEON AOP. This code was forked from the confer classification mapping repository created as part of an effort to generate foliar trait maps throughout the Department of Energy (DOE) Watershed Function Scientific Focus Area (WF-SFA) site in Crested Butte, CO in association with NEON's Assignable Asset program.
This repository was developed to support aspen cytotype mapping across this same site.

A full description of the effort is in prep, led by Ben Blonder. Citation will be updated as available. When it is published use of this code should cite that manuscript.

For previous work utilizing these data, see:

K. Dana Chadwick, Philip Brodrick, Kathleen Grant, Tristan Goulden, Amanda Henderson, Nicola Falco, Haruko Wainwright, Kenneth H. Williams, Markus Bill, Ian Breckheimer, Eoin L. Brodie, Heidi Steltzer, C. F. Rick Williams, Benjamin Blonder, Jiancong Chen, Baptiste Dafflon, Joan Damerow, Matt Hancher, Aizah Khurram, Jack Lamb, Corey Lawrence, Maeve McCormick. John Musinsky, Samuel Pierce, Alexander Polussa, Maceo Hastings Porro, Andea Scott, Hans Wu Singh, Patrick O. Sorensen, Charuleka Varadharajan, Bizuayehu Whitney, Katharine Maher. Integrating airborne remote sensing and field campaigns for ecology and Earth system science. Methods in Ecology and Evolution, 2020. doi:10.1111/2041‐210X.13463

or visit: https://kdchadwick.github.io/east_river_trait_modeling/

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