EarthNet2021 Toolkit: Download, Evaluation, Plotting
Project description
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()
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