Raster processing and modeling python package for Earth Observation data.
This package contains general functions to download, process and model Earth Observation/Remote Sensing datasets. The goal is to provide a set of functions to create image processing pipelines and offer additional functionality for analyses and modeling of Earth Observation data. The package contains the following functionalities:
- processing: download from STAC and procesing function for COGS and more
- plotting: plotting categorical and continous raster, time series
- modeling: applying sklearn and tensorflow models to raster with ease
- timeseries: creating stack of raster for timeseries analyses
Create a virtual environment
python -m venv venv
source venv/bin/activate
To use this package you will need to use GDAL:
if on ubuntu 22.04
sudo apt-get install libgdal-dev gdal-config
export CPLUS_INCLUDE_PATH=$(gdal-config --cflags | sed 's/-I//')
export C_INCLUDE_PATH=$(gdal-config --cflags | sed 's/-I//')
pip install GDAL==$(gdal-config --version)
Then you can install the packages:
pip install -r requirements.txt
- To install locally do:
pip install -e .
python -m pip install --user --upgrade setuptools
python setup.py sdist
python setup.py sdist bdist_wheel
pip install twine
twine upload --repository testpypi dist/*
useful links:
For the versions available, see the tags on this repository.
See also the list of contributors who participated in this project.
This project is licensed under the MIT License - see the LICENSE file for details
- Inspiration from working with rasterio and wanting to extend functionalities
- etc