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Spatiotemporal phenology research with interpretable models


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What Springtime can do for you

The Springtime Python package helps to streamline workflows for doing machine learning with phenology data.

Phenology is the scientific discipline in which we study the lifecycle of plants and animals. A common objective is to develop (Machine Learning) models for the occurrence of phenological events, such as the blooming of plants. Since there is a variety of data sources and existing tools to retrieve and analyse them, project folders and code organization can quickly get messy.

With Springtime, we aim to provide a more streamlined workflow for working with a variety of datasets and (ML) models. You can run Springtime as a command line tool in a terminal or use it as a Python library e.g. in a Jupyter notebook.

Programming languages
  • Python 99%
  • Dockerfile 1%
  • AGPL-3.0-or-later
  • Apache-2.0
  • GPL-2.0-only
  • Open Access
</>Source code

Participating organisations

Netherlands eScience Center
University of Twente


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Spatiotemporal phenology research with interpretable models

Updated 8 months ago