I am working on a project where we have made a RGB orthomosaic using a drone which I want to classify using QGIS. I am not a fan of unsupervised classification, and I started exploring the possibilities of object-based classification. I tried the trial of eCognition; just a wonderful workflow.
the rasters pixels are 1.5 cm x 1.5 cm. The total area is around 3 hectares. So a lot of data. I exported the raster to a raster pixel width/height of 5.0 x 5.0 cm,
classify the image using object-based analysis of the (I suspect) the Orfeo toolbox
Workflow: segmentation (meanshift) OTB:
This works fine. I want to classify the image using the polygons from the segmentation mean-shift; just like in eCognition.
Maybe make a sort of ruleset like an ROI in the semi-automatic classify plugin for QGIS? Steps:
- add fields and rule polygons in certain classes
Does anyone know a good workflow? To give a feeling for the data; I uploaded an image with the image and the segmentation output.