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  • Input file to the "2nd stage Image Stacking" service (step 5) of the Ailanthus Workflow within the Internal Joint Initiative. It represents the autumn multi-spectral (8 bands) image (vegetation at the post peak of biomass) acquired from Worldview-2 satellite at 2 meters spatial resolution. The data needs to be georeferenced and a surface reflectance product. These data will be stacked with coregistered images from the other season to be used as input to the supervised data-driven classifier. File format: raster geotiff.

  • Output file from the "2nd stage Data-driven Classifier" service (step 9) of the Ailanthus Workflow within the Internal Joint Initiative: confusion matrix related to the validation dataset. File format: text file.

  • Output file from the "2nd stage Data-driven Classifier" service (step 9) of the Ailanthus Workflow within the Internal Joint Initiative. It represents the final output map from the whole workflow: binary mapping Ailanthus/other deciduous vegetation. File format: raster geotiff.

  • Output file from the "1st stage Data-driven Classifier" service (step 4) and input file to the "Extractor Resampler and Masking" service (step 8) of the Ailanthus Workflow within the Internal Joint Initiative. It represents the output multi-class land cover map obtained from the SVM classifier at 30 meters spatial resolution. It is a multi-class map with a numeric code associated to each different class. File format: raster geotiff.

  • Input file to the "1st stage Splitter" service of the Ailanthus Workflow within the Internal Joint Initiative. It contains the reference data for all the classes in the scene, as collected in-field, labelled according to FAO-LCCS taxonomy. These data will be splitted into multiple files (each one for each land cover class) to be used for the training of the supervised data-driven classifier. File format: shapefile.

  • Output file from the "1st stage Splitter" service (step 1) and input file to the "1st stage Data-driven Classifier" service (step 4) of the Ailanthus Workflow within the Internal Joint Initiative. It represents the reference data for the training of the supervised multi-class data-driven classifier. There is a file for each class in the scene labelled according to FAO-LCCS taxonomy. A numeric code is associated to each FAO_LCCS label. File format: shapefile.

  • Output file from the "2nd stage Splitter" service (step 7) and input file to the "2nd stage Data-driven Classifier" service (step 9) of the Ailanthus Workflow within the Internal Joint Initiative. It represents the reference data for the validation of the lancd cover mapobtained by the supervised two-classes data-driven classifier. There is a file for two different classes in the scene. A numeric code is associated to each class. File format: shapefile.

  • Input file to the "1st stage Image Stacking" service (step 3) of the Ailanthus Workflow within the Internal Joint Initiative. It represents the spring multi-spectral (6 bands except thermal) image (vegetation at the peak of biomass) acquired from Landsat 5 satellite at 30 meters spatial resolution. The data needs to be georeferenced and a surface reflectance product. These data will be stacked with coregistered images from the other seasons to be used as input to the supervised data-driven classifier. File format: raster geotiff.

  • Output file from the "1st stage Data-driven Classifier" service (step 4) and input file to the "Extractor Resampler and Masking" service (step 8) of the Ailanthus Workflow within the Internal Joint Initiative: look-up table to identify the correspondence between numeric and FAO-LCCS codes. File format: text file.

  • Input file to the "1st stage Data-driven Classifier" service (step 4) of the Ailanthus Workflow within the Internal Joint Initiative. Parameters to be setted for the training of the SVM classifier: Kernel function; Regularization parameter; penalty parameter. File format: text file.