This service aims to reformat and produce final output in variuos formats for human and machine2machine reading. It represents the Step 9 of the ARMS Workflow within the Internal Joint Initiative.

This service allows to choose which column of the MasterARMS file contains the specific data to process. Moreover, it permits to provide additional files or arguments as parameters. It represents the Step 4 of the ARMS Workflow within the Internal Joint Initiative.

This service aims at creating a stack of coregistered multi-spectral raster images. It groups four multi-seasons images and stack them to obtain a unique image at native resolution (30 meters) by using the Landsat 5 sensor. It represents the Step 3 of the Ailanthus Workflow within the Internal Joint Initiative.

It is a Support Vector Machine classifier trained for a 2-classes problem. It represents the Step 9 of the Ailanthus Workflow within the Internal Joint Initiative.

This service aims at creating a vector from the coordinates in the “Pop_troph_SIA.csv” file and convert it into a shapefile. It represents the Step 3.1 of the Crustaceans Workflow within the Internal Joint Initiative.

It is a Support Vector Machine, pixel-based, classifier trained for a multi-class problem. It represents the Step 4 of the Ailanthus Workflow within the Internal Joint Initiative.

This service aims at checking which taxa detected and identified from eDNA metabarcoding sequences are listed as NIS and which taxa are not (i.e. native or unrecorded NIS). This service uses available GBIF (Global Biodiversity Information Facility) records of NIS for each Country provided by the Invasive Species Specialist Group (ISSG). it checks if a species is present in the checklist and if this is the case, the species is flagged as being invasive for that country by adding 1 (yes) or 0 (no) to the column isInChecklist of the data frame, and the checklist key or a note to the ref_checklistKey column, for the corresponding cases. It represents the Step 3 of the Metabarcoding Workflow within the Internal Joint Initiative.

This service aims at extracting the Deciduous Vegetation Layer from multiclass land cover map at 30 meters, resampling it at 2 meters and masking all the pixels, of the 2 meters stack, not overlaid by the deciduous vegetation layer. It represents the Step 8 of the Ailanthus Workflow within the Internal Joint Initiative.

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).

This service aims at modeling trophic positions as a function of environmental drivers (e.g., through GAMs, etc.) by using the "Bioclim_predic.csv" file. It represents the final step (Step 5) of the Crustaceans Workflow within the Internal Joint Initiative.