Submitting Author: Raphael Quast (@raphaelquast)
All current maintainers: @raphaelquast
Package Name: EOmaps
One-Line Description of Package: EOmaps is a python package to visualize, analyze and compare geographical datasets.
Repository Link: https://github.com/raphaelquast/EOmaps
Version submitted: 7.3
Editor: @banesullivan
Reviewer 1: @yeelauren
Reviewer 2: @jhkennedy
Archive:
Version accepted: 8.0.2
Date accepted (month/day/year): 03/14/2024

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Description

EOmaps is a python package to visualize, analyze and compare geographical datasets.

It is intended to simplify the process of geospatial data visualization and to provide a straight forward way to turn the maps into interactive widgets for data analysis.

EOmaps is based on matplotlib and cartopy and extends cartopy's capabilities with the following features

• Multi-layer capabilities (compare/combine/overlay multiple layers)
• North-arrows, scalebars, gridlines on arbitrary projections, ...
• A PyQt5 GUI widget that can be used to quickly fetch webmaps, switch layers, check data-values etc.
• Capabilities to visualize datasets as ellipses, rectangles, geodesic circles, voronoi diagrams, contour plots ...
• Integration with datashader to visualize extremely large datasets
• A flexible API to quickly turn the maps into fully customizable interactive data-analysis widgets
• ...and many more features...

It is extensively documented, unit-tested, citable via a zenodo and installable via conda or pip.
(However using pip is discouraged since dependencies like GDAL and PYPROJ can be difficult to install, especially on windows)

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 visualization¹
  • Workflow automation
  • Citation management and bibliometrics
  • Scientific software wrappers
  • Database interoperability

Domain Specific & Community Partnerships

- [x] Geospatial - [ ] Education - [ ] Pangeo 

Community Partnerships

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

• For all submissions, explain how the and why the package falls under the categories you indicated above. In your explanation, please address the following points (briefly, 1-2 sentences for each):

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

    The target audience for EOmaps are scientists and researchers working with geospatial datasets.
    EOmaps can be used to quilkly visualize structured (or unstructured) geo-spatial datasets, compare multiple datasets with each other or compare maps to an extensive list of open access webmap services. Since EOmaps is based on matplotlib, the created maps can also be connected to ordinary matplotlib axes to analyze multi-dimensional (e.g. timeseries) data.

    In addition to the interactive capabilities, maps created with EOmaps can be exported as high-resolution images or vector-graphics to create publication-ready plots.

    Finally, I believe that EOmaps also has great potential to be used in education to teach about projections, distortions, spatial resolution, rasterization of data, the subtleties of big-data visualization etc.

  • Are there other Python packages that accomplish the same thing? If so, how does yours differ?

    EOmaps is based on cartopy. While cartopy provides similar functionalities in terms of data
    visualization, EOmaps greatly extends these capabilities (especially for large datasets),
    adds multi-layer support, a basic GUI, easy-access to webmaps, and many more features.

    There exist other packages that focus on interactive geo-data visualization, but to my knowledge
    none that focusses on local use in pure python.

    • folium (wrapper for javascript-library leaflet)
    • geemap (wrapper for google-earth-engine)
    • geoviews (provides an api for matplotlib, but it is a much more high-level plotting library than EOmaps)

  • If you made a pre-submission enquiry, please paste the link to the corresponding issue, forum post, or other discussion, or @tag the editor you contacted:

    EOmaps #137

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• contains a README with instructions for installing the development version.
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• contains a tutorial with examples of its essential functions and uses.
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