Presubmission Inquiry: GemGIS - Spatial Data Processing for Geomodeling

[AlexanderJuestel]

Submitting Author: Name (@AlexanderJuestel)
Package Name: GemGIS
One-Line Description of Package: GemGIS - Spatial Data Processing for Geomodeling
Repository Link (if existing): https://github.com/cgre-aachen/gemgis
Documentation: https://gemgis.readthedocs.io/en/latest/
JOSS Publication: https://joss.theoj.org/papers/10.21105/joss.03709
JOSE Publication (awaiting publication): openjournals/jose-reviews#185

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Description

GemGIS is a Python-based, open-source geographic information processing library. It is capable of preprocessing spatial data such as vector data (shape files, geojson files, geopackages,…), raster data (tif, png,…), data obtained from online services (WCS, WMS, WFS) or XML/KML files (soon). Preprocessed data can be stored in a dedicated Data Class to be passed to the geomodeling package GemPy in order to accelerate the model building process. Postprocessing of model results will allow export from GemPy to geoinformation systems such as QGIS and ArcGIS or to Google Earth for further use.

GemGIS uses and combines the full functionality of GeoPandas, rasterio, OWSLib, Pandas, Shapely, PyVista and NumPy to simplify, accelerate and automate the workflows used to preprocess spatial data for geomodeling.

From https://gemgis.readthedocs.io/en/latest/

In addition, almost 70 tutorials illustrate the different functionalities of GemGIS.

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• Pangeo
  • My package adheres to the Pangeo standards listed in the pyOpenSci peer review guidebook

Scope

• Please indicate which category or categories this package falls under:

Scope

• Please indicate which category or categories.
  Check out our package scope page to learn more about our
  scope. (If you are unsure of which category you fit, we suggest you make a pre-submission inquiry):

  • Data retrieval
  • Data extraction
  • Data processing/munging
  • Data deposition
  • Data validation and testing
  • Data visualization
  • Workflow automation
  • Citation management and bibliometrics
  • Scientific software wrappers
  • Database interoperability

Domain Specific & Community Partnerships

- [x] Geospatial
- [x] Education
- [ ] Pangeo
- [ ] Unsure/Other (explain below)

• Explain how and why the package falls under these categories (briefly, 1-2 sentences). Please note any areas you are unsure of:

Data extraction/processing: GemGIS uses the functionality of packages like GeoPandas, Shapely, or Rasterio to extract information from vector and raster data and to put it in a form that it can be used by the GemPy.

Data visualization: GemGIS uses the functionality of packages like matplotlib or PyVista to create static and dynamic plots of data and meshes. This includes digital elevation models or meshes of subsurfaces layers, boreholes geological cross sections or even seismic data.

Workflow automation: The entire purpose of GemGIS is to provide methods to accelerate the preparation of input data for GemPy. Over time, the package has also gained additional functionality to work with a variety of datasets utilized for subsurface applications, see Tutorials.

• Who is the target audience and what are the scientific applications of this package?

The target audience is the open-source Geosciences community, researchers, students but also industry. GemGIS provides functionality to accelerate the preparation of input data for the structural geological modeling package GemPy which has been used in numerous publications. For applications at universities, we are in the final stages of getting a JOSE publication approved with more than 20 structural geological models that are used at RWTH Aachen University for teaching purposes and where GemGIS and GemPy will be included in future courses.

• Are there other Python packages that accomplish similar things? If so, how does yours differ?

GemGIS does not reinvent the wheel but rather combines the functionality of already existing packages mentioned in the description above. The packages utilized the most in GemGIS are the well-known packages like GeoPandas, Shapely, Rasterio, Pandas, NumPy, PyVista, matplotlib, etc. We also decided against i.e. wrapping GeoPandas GeoDataFrames in our own class or creating many new classes so that users can still use the full functionality of the underlying packages. This is one big advantage in comparison to GemPy where i.e. the meshes of the resulting structural geological models cannot be extracted (GemGIS is capable of extracting them though). Another example is that raster data opened with GemGIS will be stored as PyVista PolyData datasets or as grids so that users can harvest the functionality of this amazing package.

• Any other questions or issues we should be aware of:

We are currently in the process of getting the API reference to work. It works locally but not on ReadTheDocs as of now....

Thank you for providing the opportunity to add GemGIS to your community!

P.S. Have feedback/comments about our review process? Leave a comment here

[NickleDave]

Welcome to pyOpenSci @AlexanderJuestel.
Thank you for filling out a very detailed presubmission inquiry.

GemGIS is definitely in scope for us.
We would be happy to provide a review.

Please go ahead and make a full submission, and be sure to link to this presubmission inquiry in the template where it asks.
When you do so, I will close this issue.

Note that we will need those API docs in before we start the review, see checklist here:
https://www.pyopensci.org/software-peer-review/how-to/author-guide.html#does-your-package-meet-packaging-requirements

But I'm quite sure we won't have trouble finding you an editor and appropriate reviewers, once you get that taken care of.

Thank you!

[AlexanderJuestel]

@NickleDave thank you for your swift and quick response! I will open a submission and hope that I can fix the issue with the API reference very soon!

[NickleDave]

Thank you @AlexanderJuestel. Closing this