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Processes in this service

Use case Name Description
Hello World An example process that takes a name as input, and echoes it back as output. Intended to demonstrate a simple process with a single literal input.
Daugava Group points by region Merge data points with the attributes of the study region the points fall into (R function 'points_att_polygon').
Daugava Group data to groups based on date This process groups the data into groups based on the date. If requested (by setting "year_starts_at_Dec1"), it adds December to the next year (i.e. all winter months together). In that case, in the result, every year starts at Dec-01 and ends on...
Daugava Return group average description: This function calculates and returns the average value for each defined group (for example per site, per year, per season and per HELCOM_ID) (R function 'mean_by_group').
Daugava Select and Interpolate Time Series This process selects time series with sufficient data for interpolation and returns continuous time series where missing values (NAs) are replaced using linear interpolation (R function zoo::na.approx). The result is a complete time series without...
Daugava Man-Kendall Trend Analysis on Time Series This process performs a Man-Kendall trend analysis to identify the presence or absence of significant trends in time series data. It returns statistical analysis coefficients (e.g., p-values, tau, and slope) for each defined group, allowing for...
Daugava Visualisation of statistical analysis results This process visualizes statistical analysis results, where the test value (stat.value) is plotted on the Y-axis and id are plotted on the X-axis. Bar color is determined by groups and is displayed in the legend. Bar opacity is controlled by the...
Daugava Spatial visualisation of regions and data points This process maps the trend analysis results onto a study region map, visually representing each region according to the statistical results (significant increase vs. significant decrease vs. insignificant trend). The map helps in understanding the...
Daugava Spatial visualisation of regions and data points This process maps the study region and data point locations on OpenStreetMap, providing a visual representation of the geographic distribution of in-situ data points within the defined study area (R function 'map_shapefile_points').
HEREON OWT Classification Optical Water Type classification for ocean, coastal and inland waters.
Catalunya Inland SWAT, Soil and Water Assessment Tool The Soil and Water Assessment Tool (SWAT) is a hydrological model used to simulate processes such as surface runoff, groundwater flow, and water quality across watersheds of varying scales. It evaluates the effects of land use, management practices,...
Catalunya Inland Land Use Land Cover Change for SWAT+ Models A lightweight tool for rapidly reassigning land use to selected Hydrological Response Units (HRUs) in a SWAT+ model. The user provides a CSV file specifying the target HRUs and their new land cover classes; the tool then updates the land_use field...
BOKU Retrieve biodiversity data from the web This process retrieves biodiveryity data, i.e. occurrences for various species, from the sources GBIF, iNaturalist and VertNet. For more details, please ask BOKU.
BOKU Combine and match biodiversity data from separate sources This process combines and matches biodiveryity data, i.e. occurrences for various species, from the sources GBIF, iNaturalist and VertNet, with data provided by the user or other sources. For more details, please ask BOKU.
BOKU Check species names in biodiversity data from separate sources This process XYZ HERE PLEASE, from the sources GBIF, iNaturalist and VertNet, with data provided by the user or other sources. For more details, please ask BOKU.
BOKU pred extract for extraction of environmnetal data pred_extract. For extraction of environmental data used for species distribution modeling.
BOKU Run multidetect and clean the data This process detects outliers using various methods and cleans the data: Ensemble multiple outlier detection methods to ably compare the outliers flagged by each method; then extract final clean data using either absolute or best method generated...
SYKE Compute River Load This process computes daily river loading values from input data which consists of: ((1)) TOC (Total Organic Carbon, mg/l) concentration values based on laboratory samples (in Syke's case coming from the VESLA database) ((2)) Daily discharge values...
SYKE Compute areas of CORINE classes within polygons (Finland version) This process computes the size of the area in hectares (ha) covered by CORINE Land Cover (CLC) classes within user-defined polygonal regions. The analysis is based on harmonized Finnish CORINE raster datasets for the years 2000, 2006, 2012, and 2018....
SYKE Compute areas of CORINE classes within polygons (Europe version) This process computes the size of the area in hectares (ha) covered by CORINE Land Cover (CLC) classes within user-defined polygonal regions within Europe. The analysis is based on harmonized European CORINE raster datasets for the years 2000, 2006,...
SYKE Riverload Plot Analyse and plot results from the CORINE and Compute River Load -tools
NIVA Ferrybox Scripts Extract FerryBox data from NetCDF (THREDDS) to CSV Extract FerryBox environmental monitoring data from a THREDDS-hosted NetCDF file. Supports optional filtering by date interval and bounding box. Outputs a CSV containing datetime, latitude, longitude, value, unit, parameter, and derived time fields.
NIVA Ferrybox Scripts Scatterplot between two parameters (faceted by month) Reads FerryBox-style CSV and generates a scatterplot between two selected parameters, faceted by month. Outputs a PNG.
NIVA Ferrybox Scripts FerryBox tile plot (Hovmöller-style) for one or more parameters Reads a FerryBox CSV and generates one or more Hovmöller-style tile plots over time and latitude for selected parameters. Optional filters: date interval, latitude bounds, storm date marker. Outputs a PNG.
NIVA Ferrybox Scripts Scatterplot FerryBox against logger parameter Scatterplot FerryBox against logger based on the filtered parameter in joined dataframe. Option to summarise across specific waterbodies or latitudal transect of the FerryBox.
NIVA Ferrybox Scripts Join dataframes Join FerryBox and logger dataframe by date and specified parameters. Contains information for each latitudal sampling point.
NIVA Ferrybox Scripts Assessment area plot Plot FerryBox and Logger location on world map. Supports optional input with waterbodies of assessment area.
NIVA Ferrybox Scripts Extract river logger data from Baterod from NetCDF (THREDDS) to CSV Extract river logger environmental monitoring data from a THREDDS-hosted NetCDF file. Supports optional filtering by date. Outputs a CSV containing datetime, value, unit, parameter, and derived time fields.
SYKE Compute areas of CORINE classes within polygons (Finland version) This process computes the size of the area in hectares (ha) covered by CORINE Land Cover (CLC) classes within user-defined polygonal regions. The analysis is based on harmonized Finnish CORINE raster datasets for the years 2000, 2006, 2012, and 2018....
Catalunya MITgcm Plotting Tool Plot the results of the MITgcm runs. The plots are lat lon maps of the selected variable for the selected time and depth. This tool will only work with NetCDF files that were configured in a specific way (variables, ...), for example, with the output...
Catalunya MITgcm Preprocessing Preprocessing phase of the AquaINFRA marine modeling chain. Initial conditions, boundary conditions and atmospheric forcing files are generated from Copernicus data to be used as input to the MITgcm model in the Model Run phase.
Catalunya MITgcm Model Run Model Run phase of the AquaINFRA marine modeling chain. A simulation for the Catalan marine model is run, using the MITgcm modeling code, for the selected time period. Inputs are initial and boundary conditions files and atmospheric forcing files...
Malta Malta Groundwater Model (SEAWAT) This process runs a 3D variable-density groundwater flow and transport model (SEAWAT) for the Malta aquifer system. It is configured to simulate the effects of sea-level changes and groundwater recharge on aquifer salinity over a 30-year period. Users...
HELCOM HEAT HOLAS Reproducing HEAT HOLAS results: Generate the Assessment Units Generate the gridded assessment units to be used for reproducing the HOLAS assessment using HELCOM's HEAT assessment tool, covering the Baltic Sea, for a selected HOLAS assessment period. The area is gridded, the grid cells have different sizes. For...
HELCOM HEAT HOLAS Reproducing HEAT HOLAS results: Combine the samples Combine the various types of samples to be used for reproducing the HOLAS assessment using HELCOM's HEAT assessment tool, for a selected HOLAS assessment period. For every assessment period, the configation and the spatial grid are predefined. Default...
HELCOM HEAT HOLAS Reproducing HEAT HOLAS results: Compute Annual Indicators Compute the Annual Indicators (i.e. the calculated HEAT EQRS per indicator per year per assessment unit) using HELCOM's HEAT assessment code, for a selected HOLAS assessment period. For every assessment period, the configation and the spatial grid are...
HELCOM HEAT HOLAS Reproducing HEAT HOLAS results: Compute Assessment Indicators Compute the Assessment Indicators (i.e. EQRS per assessment period per assessment unit) using HELCOM's HEAT assessment code, for a selected HOLAS assessment period. The calculation is based on the Annual Indicators (i.e. the calculated HEAT EQRS per...
HELCOM HEAT HOLAS Reproducing HEAT HOLAS results: Compute Assessment Compute the Assessment (i.e. EQRS per assessment unit, grouped by overall and criterial level indicators) using HELCOM's HEAT assessment code, for a selected HOLAS assessment period. The calculation is based on the Assessment Indicators (i.e. EQRS per...
HELCOM HEAT Assessing Eutrophication: Generate the Assessment Units Generate the gridded assessment units to be used for the eutrophication assessment using HELCOM's HEAT assessment tool. The area is gridded, the grid cells have different sizes. The spatial units and configuration (e.g. grid size) have to be provided....
HELCOM HEAT Assessing Eutrophication: Combine the samples Combine the various types of samples to be used for the eutrophication assessment using HELCOM's HEAT assessment tool. Please provide input data for at least one of the three sample types (bottle, pump/ferrybox, CTD). Of course you can also provide...
HELCOM HEAT Assessing Eutrophication: Compute Annual Indicators Compute the Annual Indicators (i.e. the calculated HEAT EQRS per indicator per year per assessment unit), as part the eutrophication assessment using HELCOM's HEAT assessment tool. As input, please provide a file containing combined and filtered...
HELCOM HEAT Assessing Eutrophication: Compute Assessment Indicators Compute the Assessment Indicators (i.e. EQRS per assessment period per assessment unit), as part the eutrophication assessment using HELCOM's HEAT assessment tool. The calculation is based on the Annual Indicators (i.e. the calculated HEAT EQRS per...
HELCOM HEAT Assessing Eutrophication: Compute Assessment Compute the Assessment (i.e. EQRS per assessment unit, grouped by overall and criterial level indicators), as part the eutrophication assessment using HELCOM's HEAT assessment tool. The calculation is based on the Assessment Indicators (i.e. EQRS per...
Elbe Attach human population statistics to EU NUTS3 regions. Attach EU human population statistics for chosen year to EU NUTS3 regions using temporally matching NUTS3 version.
Elbe Calculating human population density-derived weights for CORINE CLC classes. Mapping CORINE CLC raster to Eurostat 2021 Census Grid to calculate human population density-derived weights for significant urban CLC classes.
Elbe Validate geometries (e.g. river catchments) Validate geometries and save them as multi-polygons (R function 'preprocess_catchment_geometry')
Elbe Align extents of three datasets (D1=NUTS3 regions; D2=LAU regions; D3=river catchments) including validation steps. Clip three overlapping datasets (D1=NUTS3 regions; D2=LAU regions; D3=river catchments) to the same analysis extent defined as the overlap of D1 and D3 and validate the geometries of the clipped D2.
Elbe Visualising final outputs of dasymetric refinement process. Visualising final urban significant CLC-class specific dasymetric refinement input weights in table (output 1), error map of dasymetric refinement process at LAU (Local Areal Unit) level (output 2), and estimated human population density for target...
Elbe Dasymetric refinement of human population from NUTS3 regions to significant urban CORINE CLC polygons. Dasymetric refinement of human population from NUTS3 regions to significant urban CORINE CLC polygons using CLC-class-specific input weights.
Elbe Measure precision of human population dasymetric refinement by comparing observed and estimated human population for EU LAU regions. Estimate annual human population for Eurostat LAU (Local Areal Units) regions based on area-weighted ancillary data and compare with observed LAU human population values.
Elbe Area-weighted interpolation of ancillary data to calculate human population in target regions Area-weighted interpolation of ancillary data to calculate human population in target regions. The ancillary dataset should contain a polygon ID column called 'nuts_cor_int_id' and an estimated human population numeric column called 'estPopCor'. The...
Human Population Attach legend to CORINE CLC raster Attaches the official CORINE Land Cover legend (class codes, labels, and colors) to a CORINE CLC raster, and derives the list of urban CLC codes (R function 'get_raster_for_geometry' / D2K wrapper 'attach_legend_to_corineCLC')
Human Population Calculate dasymetric weighting table Calculates population-density-based weights per CORINE Land Cover class by overlapping the Eurostat census grid (human population) with the CORINE CLC 2018 raster, treating continuous urban fabric (111) and discontinuous urban fabric (112) classes...
Human Population Create evaluation visualisations for dasymetric population mapping Creates ten interactive HTML visualisations (histograms and maps) evaluating the dasymetric refinement results against observed census grid and LAU population data, including weight distribution, CORINE class coverage, observed/estimated population...
Human Population Crop and mask raster to analysis extent Crops and masks an existing CORINE CLC raster to a given spatial analysis extent (e.g. a catchment or country boundary), returning only the raster cells within that geometry (R function 'get_raster_for_geometry')
Human Population Dasymetric refinement of LAU population to raster cells Performs dasymetric refinement of LAU (Local Administrative Unit) human population for a chosen focus year, redistributing population to finer CORINE Land Cover raster cells (approx. 1 km2) within a catchment. With refinement type 'weighted',...
Human Population Intersect data with spatial analysis extent Calculates a spatial intersection between an input dataset (e.g. LAU polygons, census grid) and a spatial analysis extent (e.g. a catchment boundary), keeping only the features that intersect the extent. Reprojects the input to match the extent's CRS...
Human Population Evaluate dasymetric refinement results Evaluates dasymetric refinement results by comparing weighted and simple refinement rasters against observed census grid population (reference year 2021, treated as ground truth). Produces two evaluation datasets (one per refinement type) with...
Human Population Get spatial analysis extent Calculates the overall spatial analysis extent as the union of LAU (Local Administrative Unit) polygons selected within the catchment for the focus year. If no focus-year LAU polygons are found, the union of the reference-year LAU polygons is used...
Human Population Get Eurostat census grid Fetches the Eurostat/GISCO 1 km population census grid for the given countries directly from the GISCO web service, builds 1 km x 1 km grid cell polygons (EPSG:3035) from the cell corner coordinates, and validates the resulting geometries (R function...
Human Population Get CORINE CLC raster for focus year Selects and fetches the CORINE Land Cover (CLC) raster covering the European Union for the CORINE release year closest to the given population focus year, loading it directly from a remote Cloud-Optimized GeoTIFF (COG). Focus years 2015-2024 resolve...
Human Population Get ECRINS catchment Queries the EEA ECRINS (European Catchments and Rivers Network System) ArcGIS REST service for a specific functional elementary catchment by ID, fixes invalid geometries, reprojects to EPSG:3035, and looks up the list of countries that catchment...
Human Population Get EUBUCCO building footprints for catchment Fetches building footprint data from the EUBUCCO v0.2 dataset (https://eubucco.com) for all NUTS2 regions overlapping a given catchment, combines and deduplicates results, and returns them as a single spatial object with attributes including...
Human Population Get Hydrography90m basin catchment by ID (live GISCO country lookup) Queries the aqua.igb-berlin.de pygeoapi 'get-basin-polygon' process (Hydrography90m / GeoFRESH) for a single drainage basin by basin_id, fixes invalid geometries, reprojects to EPSG:3035, and determines the list of countries that catchment overlaps by...
Human Population Get HydroBASINS level 07 catchment (via Ramsar WFS) Queries the Ramsar Sites Information Service (RSIS) WFS for a single HydroBASINS (HydroSHEDS) level 07 catchment by HYBAS_ID, fixes invalid geometries, reprojects to EPSG:3035, and looks up the list of EU countries that catchment overlaps from a fixed...
Human Population Get LAU population data Fetches Eurostat LAU (Local Administrative Unit) human population data for the given countries and focus year via GISCO, reprojected to EPSG:3035 (R function 'get_lau_population'). This process is used for both the population focus year and the...
Human Population Keep only valid CORINE CLC classes Restricts a CORINE CLC raster to only the urbanised classes present in the supplied weight table, masking out (setting to NA) any raster cells whose CORINE class code does not have an assigned weight (R function 'get_only_valid_corine_categories_raster')