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  • Output file from the "1st stage Data-driven Classifier" service (step 4) of the Ailanthus Workflow within the Internal Joint Initiative: confusion matrix related to the validation dataset. File format: text file.

  • Output file from the "1st stage Data-driven Classifier" service (step 4) of the Ailanthus Workflow within the Internal Joint Initiative: accuracy measures as Overall Accuracy; User's Accuracy; Producer's Accuracy; F1-score. File format: text file.

  • 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.

  • Input file to the "1st stage Image Stacking" service (step 3) of the Ailanthus Workflow within the Internal Joint Initiative. It represents the winter multi-spectral (6 bands except thermal) image (vegetation at the pre-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. 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 "2nd stage Image Stacking" service (step 5) of the Ailanthus Workflow within the Internal Joint Initiative. It represents the summer multi-spectral (8 bands) image (vegetation at the dry season) 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.

  • Input file to the "2nd stage Splitter" service (step 6) of the Ailanthus Workflow within the Internal Joint Initiative. It contains the reference data for two classes: Ailanthus and other deciduous vegetation in the scene, as collected in-field. These data will be splitted into two different 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 "Extractor Resampler and Masking" service (step 8) and input file to the "2nd stage Data-driven Classifier" service (step 9) of the Ailanthus Workflow within the Internal Joint Initiative. It is a multi-layer file containing the two multi-season images each one with its 8 bands in which those pixels not classified as deciduous vegetation from first stage land cover mapping are masked. File format: raster geotiff.

  • Input file to the "1st stage Image Stacking" service (step 3) of the Ailanthus Workflow within the Internal Joint Initiative. It represents the autumn multi-spectral (6 bands except thermal) image (vegetation at the post 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 "2nd stage Splitter" service (step 6) 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 training of 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.