Are there any parameters that can control how Pix4D Mapper resolves classification - in order to control the accuracy of a DTM?
I’ve recently discovered that WebODM has a parameter that controls this - “feature-quality”. I was wondering if there might be something in Pix4D Mapper that has the same functionality.
reference: feature-quality — OpenDroneMap 3.3.4 documentation
Thank you for your question.
You can find more information about point cloud classification here:
To summarize, the point cloud classification is based on machine learning techniques which require training on labelled data. Both the geometry and the color information are used to assign the points of the densified point cloud in one of the predefined groups. The process performs well for environments similar to the ones of the datasets used for training the algorithm, such as rural, construction and vegetation areas. High vegetation and buildings are well-detected and classified.
You can find out more in this article:
Depending on the quality of the dataset and the type of terrain, there are areas where the classification is not expected to perform perfectly and there is a need for manual intervention. Mountains, quarries and concrete buildings might need further editing. In the future, more training data will be used to improve the algorithm and give more reliable classification results for different types of projects.
It is possible to edit the point groups to improve the results of the classification. Points can be reallocated among point groups. The points that are erroneously assigned to a point group can be moved to the correct point group using the Edit Densified Point Cloud option: