EarthNet Toolkit

The EarthNet2021 Toolkit.

Documentation

Find more information on https://www.earthnet.tech.

Install

pip install earthnet

Downloading new dataset EarthNet2023 - Africa

Ensure you have enough free disk space! We recommend 1.5TB.

import earthnet as entk
entk.download(dataset = "earthnet2023", split = "all", save_directory = "data_dir")

Where data_dir is the directory where EarthNet2023 - Africa shall be saved and split is "all" or a subset of ["train", "test].

When using EarthNet2023 - Africa, please for now cite the DOI 10.5281/zenodo.10659371, until there is an original publication on the dataset.

Vitus Benson, Christian Requena-Mesa, Jeran Poehls, Lazaro Alonso, Claire Robin, Nuno Carvalhais, Markus Reichstein. (2024). 
EarthNet Toolkit for accessing the EarthNet2023 - Africa dataset.
Zenodo. https://doi.org/10.5281/zenodo.10659371

This work has received funding from the European Union’s Horizon 2020 Research and Innovation Project DeepCube, under Grant Agreement Numbers 101004188.

Downloading new dataset EarthNet2021x / GreenEarthNet

Ensure you have enough free disk space! We recommend 1TB.

import earthnet as en
en.download(dataset = "earthnet2021x", split = "train", save_directory = "data_dir")

Where data_dir is the directory where EarthNet2021 shall be saved and split is "all"or a subset of ["train","iid","ood","extreme","seasonal"].

Scoring new dataset EarthNet2021x

Save your predictions for one test set in one folder in the following way: {pred_dir/region/cubename.nc} Name your NDVI prediction variable as "ndvi_pred".

Then use the data_dir/dataset/split as the targets.

Then compute the normalized NSE over the full dataset:

import earthnet as en
scores = en.score_over_dataset(Path/to/targets, Path/to/predictions)
print(scores["veg_macro_score"])

Alternatively you can score a single minicube:

import earthnet as en
df = en.normalized_NSE(Path/to/target_minicube, Path/to/prediction_minicube)
print(df.describe())

Download

Ensure you have enough free disk space! We recommend 1TB.

import earthnet as en
en.Downloader.get(data_dir, splits)

Where data_dir is the directory where EarthNet2021 shall be saved and splits is "all"or a subset of ["train","iid","ood","extreme","seasonal"].

Alternatively if package was installed locally:

cd earthnet-toolkit/earthnet/
python download.py -h
python download.py "Path/To/Download/To" "all"

For using in the commandline.

Use EarthNetScore

Save your predictions for one test set in one folder in one of the following ways: {pred_dir/tile/cubename.npz, pred_dir/tile/experiment_cubename.npz} Then use the Path/To/Download/To/TestSet as the targets.

Then use the EarthNetScore:

import earthnet as en
en.EarthNetScore.get_ENS(Path/to/predictions, Path/to/targets, data_output_file = Path/to/data.json, ens_output_file = Path/to/ens.json)

Get Coordinates for a cube

Getting Lon-Lat-coordinates for a cube or tile is as simple as:

import earthnet as en
en.get_coords_from_cube(cubename, return_meso = False)
en.get_coords_from_tile(tilename)

Plotting a cube

Creating a gallery view for a cube is done as follows:

import earthnet as en
import matplotlib.pyplot as plt
fig = en.cube_gallery(cubepath, variable = "ndvi")
plt.show()

Creating a NDVI timeseries view for a cube is done as follows:

import earthnet as en
import matplotlib.pyplot as plt
fig = en.cube_ndvi_timeseries(predpath, targpath)
plt.show()