Eumap is a library to enable easier access to several spatial layers prepared for Continental Europe (Landsat and Sentinel mosaics, DTM and climate datasets, land cover and vegetation maps), as well the processing classes and functions used to produce them.

It implements efficient raster access through rasterio, multiple gapfiling approaches, spatial and spacetime overlay, training samples preparation (LUCAS points), and Ensemble Machine Learning applied to spatial predictions (fully compatible with scikit-learn).

The spatial layers can be also accessed through ODSE Viewer.




The best way to install eumap is using Docker. Check the official documentation to get Docker running in your environment.

JupyterLab Container

The image opengeohub/pygeo-ide provides access to all eumap dependencies and to JupyterLab IDE. The follow instructions are specific for Intel CPUs, which supports MKL, for other CPUs it’s recommend to use the openblas version.

First, download the image:

docker pull opengeohub/pygeo-ide:v3.8.6-mkl-gdal314

Then create the container:

docker run -d --restart=always --name opengeohub_pygeo_ide -v /mnt:/mnt -p 8888:8888 -e GRANT_SUDO=yes --user root opengeohub/pygeo-ide:v3.8.6-mkl-gdal314 jupyter lab --LabApp.token='opengeohub' --ServerApp.root_dir='/'

As last step access the JupyterLab through http://localhost:8888 using the password opengeohub, open a terminal and install the eumap last version:

pip install -e 'git+[full]'


To install eumap using conda, first it’s necessary download the file conda_env.yml:

curl > ./conda_env.yml

Then use this file to create new a environment and activate it:

# It will take a while
conda env create --quiet --name eumap --file conda_env.yml
conda activate eumap

As last step install the eumap:

pip install -e 'git+[full]'


The eumap library has been developed and used by a group of active community members. Your help is very valuable to make the package better for everyone. Check our contribution guidelines and open issues


© Contributors, 2020. Licensed under an Apache-2 license.


This work is co-financed under Grant Agreement Connecting Europe Facility (CEF) Telecom project 2018-EU-IA-0095 by the European Union.