Skip to main content

Label and track unique geospatial features from gridded datasets

Project description


Build Status codecov Conda Version pypi downloads Documentation Status License:MIT DOI

Ocetrac is a Python 3.6+ packaged designed to label and track unique geospatial features from gridded datasets. The package is designed to accept data that have already been preprocessed, meaning that the data only contain values the user is interested in tracking. Ocetrac operates lazily with Dask so that it is memory uninhibited and fast through parallelized execution. We provide examples and demonstrate best practices as developed by the Climate Data Science Lab at Columbia University / Lamont-Doherty Earth Observatory.

When using this package, please cite the original software.



To install the core package from conda-forge run: conda install -c conda-forge ocetrac


To install the core package run: pip install ocetrac.


  1. Clone ocetrac to your local machine: git clone
  2. Change to the parent directory of ocetrac
  3. Install ocetrac with pip install -e ./ocetrac. This will allow changes you make locally, to be reflected when you import the package in Python.

How you can contribute

  • You can get involved by trying ocetrac, filing issues if you find problems, and making pull requests if you make improvements.


  • We rely heavily on scikit-image and its community of contributors.
  • This work grew from a collabortion with NCAR during the ASP Graduate Visitor Program attended by Hillary Scannell. This project recieved continued support from the Leonardo DiCaprio Foundation, Microsoft, and the Gordon and Betty Moore Foundation.

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ocetrac-0.1.4.tar.gz (936.6 kB view hashes)

Uploaded source

Built Distribution

ocetrac-0.1.4-py3-none-any.whl (6.9 kB view hashes)

Uploaded py3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page