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All Projects → carpentries-incubator → geospatial-python

carpentries-incubator / geospatial-python

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Introduction to Geospatial Raster and Vector Data with Python

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Introduction to Geospatial Raster and Vector Data with Python

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The Lesson

Check out https://carpentries-incubator.github.io/geospatial-python/ to view the lesson as it currently stands. Episodes 1-7 and Episode 12 are currently complete. Epsiodes 1-7 have been taught previously in workshop settings, read more about that experience and feedback here. Other episodes still need to be fleshed out and we welcome contributions!

Contributing

We welcome all contributions to improve the lesson! Maintainers will do their best to help you if you have any questions, concerns, or experience any difficulties along the way.

Please see the current list of issues for ideas for contributing to this repository. For making your contribution, we use the GitHub flow, which is nicely explained in the chapter Contributing to a Project in Pro Git by Scott Chacon. Look for the tag good_first_issue. This indicates that the mantainers will welcome a pull request fixing this issue.

We are looking for more active developers of this lesson. Edits to existing lesson episodes or additions to new episodes are welcome. If you are interested in contributing a new episode, you can either start by creating a new Github Issue to start discussion or dive in and submit a new Pull Request.

Check out the Contribution Guide and more detailed guidelines on proper formatting, how to preview the lesson locally, and how to write new episodes.

️💚️ Thanks Contributors! 💚


Ryan Avery
Kunal Marwaha
Alex Pakalniskis
Brendan McAndrew
Sean McCartney

Acknowledgements

Funding

The data and lessons in this workshop were originally developed through a hackathon funded by the National Ecological Observatory Network (NEON) - an NSF funded observatory in Boulder, Colorado - in collaboration with Data Carpentry, SESYNC and CYVERSE. NEON is collecting data for 30 years to help scientists understand how aquatic and terrestrial ecosystems are changing.

Thanks Geospatial R Authors!

This lesson would not be possible without the many contributions from the authors of the Introduction to Geospatial Raster and Vector Data with R and Introduction to Geospatial Concepts lessons. These lessons have served as templates for this geospatial python lesson.

Data Carpentry Introduction to Geospatial Raster and Vector Data with R Leah Wasser; Megan A. Jones; Jemma Stachelek; Lachlan Deer; Zack Brym; Lauren O'Brien; Ana Costa Conrado; Aateka Shashank; Kristina Riemer; Anne Fouilloux; Juan Fung; Marchand; Tracy Teal; Sergio Marconi; James Holmquist; Mike Smorul; Punam Amratia; Erin Becker; Katrin Leinweber Editors: Jemma Stachelek; Lauren O'Brien; Jane Wyngaard https://doi.org/10.5281/zenodo.1404424

Data Carpentry Introduction to Geospatial Concepts Leah Wasser; Megan A. Jones; Lauren O'Brien; Jemma Stachelek; Tom Wright; Tracy Teal; Dev Paudel; Jane Wyngaard; Anne Fouilloux; Bidhyananda Yadav; Chris Prener; Tyson Swetnam; Erin Becker; Katrin Leinweber Editor(s): Tyson Swetnam; Chris Prener https://doi.org/10.5281/zenodo.1404414

Maintainer(s)

The current maintainer of this lesson is

  • Ryan Avery

Citation

To cite this lesson, please consult with CITATION

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].