The service aims at splitting the input shapefile for each FAO-LCCS taxo code. Within the Ailanthus workflow of the Internal Joint Intiative, it represents the step 6 and 7 of the second stage (where a 2 classes problem is considered). The algorithm is run by considering training and test data allowing to map the FAO-LCCS classes into the corresponding numerical classes.

The service, starting from a multi-class shapefile containing the land cover classes in the scene, expressed in FAO-LCCS taxonomy, aims to generate a series of shapefiles, one for each different class. A numeric code is also associated to each class. The algorithm uses as input training and test data used to obtain the multi-class land cover mapping of the scene by a supervised, pixel-based classification. Within the Ailanthus workflow of the Internal Joint Intiative, it represents the step 1 and 2 of the first stage (where a multi-class problem is considered).