Outputs of the Jupyter Notebook - Tree crown detection using DeepForest

The dataset contains the outputs of the notebook "Tree crown detection using DeepForest" published in The Environmental Data Science Book.

Contributions

Notebook

• Alejandro Coca-Castro (author), The Alan Turing Institute, @acocac

• Matt Allen (reviewer), Department of Geography - University of Cambridge, @mja2106

Modelling codebase

• Ben Weinstein (maintainer & developer), University of Florida, @bw4sz

• Henry Senyondo (support maintainer), University of Florida, @henrykironde

• Ethan White (PI and author), University of Florida, @weecology

• Other contributors are listed in the GitHub repo

Modelling publications

• Ben G Weinstein, Sergio Marconi, Mélaine Aubry-Kientz, Gregoire Vincent, Henry Senyondo, and Ethan P White. Deepforest: a python package for rgb deep learning tree crown delineation. Methods in Ecology and Evolution, 11:1743–1751, 2020. URL: https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.13472, doi:https://doi.org/10.1111/2041-210X.13472.

• Ben G Weinstein, Sergio Marconi, Stephanie Bohlman, Alina Zare, and Ethan White. Individual tree-crown detection in rgb imagery using semi-supervised deep learning neural networks. Remote Sensing, 2019. URL: https://www.mdpi.com/2072-4292/11/11/1309, doi:10.3390/rs11111309.

• Ben G Weinstein, Sergio Marconi, Stephanie A Bohlman, Alina Zare, and Ethan P White. Cross-site learning in deep learning rgb tree crown detection. Ecological Informatics, 56:101061, 2020. URL: https://www.sciencedirect.com/science/article/pii/S157495412030011X, doi:https://doi.org/10.1016/j.ecoinf.2020.101061.