We are excited to share the ReforesTree dataset! 🎉
We introduce the ReforesTree dataset in hopes of encouraging the fellow machine learning community to take on the challenge of developing low-cost, scalable, trustworthy and accurate solutions for monitoring, verification and reporting of tropical reforestation inventory.
In alphabetical order
For each site the data we publish consists of four components free for use:
Thanks to the torchgeo team, you can download the dataset through the ReforesTree data loader
from torchgeo.datasets import ReforesTree
ds = ReforesTree(root="data/reforestree/", download=True, checksum=True)
You can download the raw data from dropbox and put the "data" folder in the main repo. All processed data is available directly to use, but if you want to process it yourself, feel free to only download "www_ecuador" and "field_data.csv" and follow the tutorial below.
Alternatively, we are hosting a version of the dataset in zenodo.
In the tutorial you'll find the steps to recreate (and hopefully improve) the dataset and how to use it.
Please read our paper here. For any questions, please reach out to gyri.reiersen@tum.de or david.dao@inf.eth.ch