weitsicht submission - Tool to work/automate workflows base on already georeferenced images.

[MartinW-S2M]

Submitting Author: (@MartinW-S2M)
All current maintainers: (@MartinW-S2M)
Package Name: weitsicht
One-Line Description of Package: A Python package that enables further use of georeferenced images for mapping (plane, raster, mesh) and projection between image space and 3D.
Repository Link: https://github.com/MartinW-S2M/weitsicht
Version submitted: v0.0.2
EiC: @kysolvik
Editor: TBD
Reviewer 1: TBD
Reviewer 2: TBD
Archive: TBD
JOSS DOI: TBD
Version accepted: TBD
Date accepted (month/day/year): TBD

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Description

weitsicht is a Python package designed to be easy to use and to enable the community to work with georeferenced imagery—especially the growing volume of drone/UAS data used in environmental science, geomatics, and GIS workflows. It provides a focused set of functions and classes that map 2D image points to 3D coordinates and also project 3D world points back into image space (to find images based on 3D points). Core features include mapping image footprints, center points, and user- or AI-derived image points (e.g., segments), while abstracting coordinate reference system transformations. At its core, Weitsicht provides accurate camera models and ray–surface intersection algorithms for monoplotting (single-image ray intersection with a ground/3D model) and projecting 3D data back into the pixel space, as well it provides functionality around image metadata (EXIF/XMP) to extract georeference information. The package is highly modular by design, making it straightforward to extend with additional models and libraries.

Scope

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  • 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

• Geospatial
• Education

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  • Who is the target audience and what are scientific applications of this package?
    Targets users are researcher, students, hobbiests and small companies working with single/batches of georeferenced imagery. Such as WISDAMapp users (https://github.com/WISDAMapp/WISDAM) or used in research workflows like the University of Vienna’s INDIGO project—across environmental science, geomatics, GIS, and UAS/drone applications.

  • Are there other Python packages that accomplish the same thing? If so, how does yours differ?
    Visual odometry/SfM packages also relate images to 3D, they have a different scope and are often too complex for users outside the geomatics/computer-vision community; Weitsicht instead focuses on straightforward workflows with minimum knowledge required to be able to use your imagery for other scientific tasks (e.g. envrionmental monitoring of animals).

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[kysolvik]

Hi @MartinW-S2M! I'm Kylen, a member of our EiC team 👋

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Editor comments

Looks good @MartinW-S2M! Just a few things before we move forward with the review process:

1. With the increasing use of LLMs in open source software, pyOpenSci has adopted an open approach to the use of generative AI in submissions. In light of this, we require a full disclosure of all locations in the code where generative AI has been used. We're still updating our templates to reflect this, but if AI was used in the development process could you discuss how and where? Thanks!
2. Regarding the JOSS submission, there doesn't seem to be a paper.md or a DOI from a long-term repository (e.g. Zenodo). You can add these at a later date during the review process, but just a heads up that they would be required for consideration by JOSS.
3. Note that JOSS has different requirements for packages than pyOpenSci. A couple that might be relevant are their scholarly significance/research impact requirement and development history, which requires at least 6 months of development history among other things. For the latter, since weitsicht was recently split off from WISDAM, there isn't 6 months of history in weitsicht's repo. I think JOSS could look at WISDAM's history, but I can't speak for them. Just something to think about if it gets to that stage.

Once you answer 1, we'll go forward with finding an editor to manage the review process. Thanks!

[MartinW-S2M]

Hallo Kylen, thanks for the quick response.

(1) Disclosure of generative AI:
generateive AI was used for following tasks:

• Documentation and readme.md: spelling and grammar correction and for polishing my English style (reducing German-influenced phrasing)
• Docstrings: harmonization, and adding of :type XX:; :rtype XX: and :raises XX: (also for recursive search whats raised by calls inside weitsicht's methodes and functions)
• brainstorming on the newest function _estimate_gsd_for_mapped_points and to create tests for that function.
• Assistence how to use .rst syntax and how sphinx extension are working (like autodoc)
• Assistence on the github actions workflow files for testing and creating badges.
• Asked for explenations why pyright static type checker marked elements when the reason was not obvious to me

Tool used: ChatGPT with model GPT-5.2
Did not use generative AI before the end of January 2026.

(2 and 3) Thanks for the hints. Will check that out.

[kysolvik]

Hi Martin! Thanks for your response. I think that's all the info needed to kick-off the review process! Next step is to assign an editor. We'll let you know when that happens! We're playing catch up on submissions right now, so it might not happen right away but I'll keep you posted.