This repository contains a few tools based on PyQGS that help classififying polygon layers (buildings, parcels, buildingblocks) according to a reference table of RGB-values.
The tools were developed for 'urban_geodata' - a project dealing with digitizing old thematic map stock on the institute for urban and regional research (ISR) on the Austrian academy of sciences (ÖAW) and was funded by Internet Privatstiftung Austria. The categories of these maps that are rendered as monochromatic signatures can be classified using euclidean distance calculation in the RGB colorspace and propabilities based on sampling points - hence the name.
In order to make good use of the scripts here the following prerequisites are necessary:
- a georeferenced thematic map, using monochromatic area fills
- a suitable polygon layer that fits the map's areas
- QGIS 3.16 or later
After the area signatures of a map's legend are digitized,
sampling_points.model3 or its python equivalent is applied and sampling points are beeing generated that contain the RGB values of the signature's icons. The average rgb values are grouped by the digitized legend features using an sql expression such as in legend_rgb_values.sql. The result serves as reference value table for the classification of a polygon layer.
The same model can be used to generate the sampling points for the poygon layer, however its functionality is also incorporated into rgb_sampling_distances.py This file also contains an overview of the filterparameters such as point density, distance threshold etc.
A more detailed description (in german) can be found here.
