Download the script raster_classifier.py from.The image below depicts the render type applied to the elevation raster. The image below depicts the elevation of the raster post-classification. The image below depicts the elevation raster prior to classification The solution I ended up using involved PyQGIS, python GDAL, and Numpy. I wanted a PyQGIS solution that could also generate the summary statistics as part of the classification legend. The statistics produced cannot be incorporated as part of the raster legend.If the raster layer is very big and the computer resources are low the process could take a very long time to complete. Vectorization is a CPU intensive process.It would require a user to pre-process the raster by using the raster calculator, reclassify algorithms from processing, or the r.recode command to allow zonal statistics.Calculation of the statistics from the vector layer either by using SQL (Virtual layers) or native QGIS algorithms.Īlthough the suggested solution was accepted as an answer it presents a couple of challenges.Recode the raster to simplify the raster classes.
The suggested solution involved a three-step approach:
Raster calculation how to#
I recently came across where a user asked how to calculate the area of each class in a raster. During my spare time, I am always on the lookout for interesting questions posed on. QGIS raster functionality has come a long way and continues to improve.
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