[Qgis-user] Use Case: Segmentation (for photo-interpretation) without Classification?

celati Laurent laurent.celati at gmail.com
Mon Jun 30 03:16:51 PDT 2025


Hello,
i’m taking the liberty to post a message in order to share an use case.
Our need/purpose is to find existing methods/tools that would allow to
perform segmentations with the aim of helping botanists for pre-map
physiognomic units before to go on the field. In other words : to produce a
delineation (polygonal layer) of physiognomic units. In my humble opinion,
this is an unusual need/use case because the segmentation is NOT
intended/aimed as a first step before classification. The goal is to
reproduce as closely/faithfully as possible the botanist’s
photo-interpretation. We need to find the right balance/parameters between
the number of segments, their sizes, and their compactness (shape). The
idea would be to perform relevant segmentation across the entire area being
processed, neither over-segmented nor under-segmented.
With optimal parameters/configuration and input variables/data that can
vary depending on the environment (urban, agricultural, wooded, herbaceous).

I’ve done some tests, notably via Qgis with OTB Approaches Region Merging:
https://www.orfeo-toolbox.org/CookBook-7.0/Applications/app_GenericRegionMerging.html
I haven’t really tested other traditional approaches (such as cluster mean
shift or watershed, for example). Until now, I haven’t tested AI/DL because
I thought there wouldn’t be any segmentation models trained on IRC ortho DB
images that could meet our needs.
This is why I prioritized “traditional” segmentation tools/approaches.

My tests were done using satellite spot6/7 images and Infrared Colour
aerial orthographic databases (franch mapping agency). Tests with the
aerial orthographic database are more resource-intensive and
time-consuming. Furthermore, this OTB tool tested (GRM) is not suitable for
large images. The results are quite good, particularly for agricultural and
urban areas.
For forested areas, it’s more complicated. And in order to improve the
results, it may be necessary to consider integrating textures or indicators
(NDVI or other) ?

if you have any comments or suggestions for guidance regarding
methods/tools/data, I would be happy to read you.

Thank you in advance.

Best regards,
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