About this book

About this book#

Contributing#

If you’d like to contribute to this book, please start a discussion or raise an issue in the GitHub repository.

Citation#

If you use this material, please consider including the following citation:

Plain text
Marshall et al., (2025). Cloud-native geospatial data cube workflows with open-source tools. Journal of Open Source Education, 8(89), 267, https://doi.org/10.21105/jose.00267

Bibtex

@article{Marshall2025, 
        doi = {10.21105/jose.00267}, 
        url = {https://doi.org/10.21105/jose.00267}, 
        year = {2025}, 
        publisher = {The Open Journal}, 
        volume = {8}, number = {89}, pages = {267}, 
        author = {Emma Marshall and Deepak Cherian and Scott Henderson and Jessica Scheick and Richard Forster}, 
        title = {Cloud-native geospatial data cube workflows with open-source tools}, 
        journal = {Journal of Open Source Education} }

Acknowledgements#

This book is the product of many discussions and developments within the open-source community. All of the workflows demonstrates throughout these tutorials are made possible by open-source developers and maintainers. Below is a full list of all open-source libraries used in this book:

cf_xarray [10], Dask [58], Folium [59], GeoPandas [28], Holoviz [45], Jupyter Notebook [30], Matplotlib [6], NumPy [23], Pandas [51], Planetary_Computer [48], PyPROJ [47], SciPy [21], Shapely [19], RioXarray [46], Xarray [25], Zarr [40], Xvec, contextily, PySTAC, PySTAC Client, Rich, stackstac.

This book was made using Jupyter Book [11] which uses a number of tools developed by the Executable Books project.

Contents