This dataset represents the Integrated biodiversity status assessment for fish used in State of the Baltic Sea – Second HELCOM holistic assessment 2011-2016. Status is shown in five categories based on the integrated assessment scores obtained in the BEAT tool. Biological Quality ratios (BQR) above 0.6 correspond to good status. The assessment is based on core indicators of coastal fish in coastal areas, and on internationally assessed commercial fish in the open sea. The open sea assessment includes fishing mortality and spawning stock biomass as an average over 2011–2016. Open sea results are given by ICES subdivisions, and are not shown where they overlap with coastal areas. Coastal areas results are given in HELCOM Assessment unit Scale 3 (Division of the Baltic Sea into 17 sub-basins and further division into coastal and off-shore areas) Attribute information: "COUNTRY" = name of the country / opensea "Name" = Name of the coastal assessment unit, scale 3 (empty for ICES open sea units) "HELCOM_ID" = ID of the HELCOM scale 3 assessment unit (empty for ICES open sea units) "EcoystemC" = Ecosystem component analyzed "BQR" = Biological Quality Ratio "Conf" = Confidence (0-1, higher values mean higher confidence) "Total_indi" = Number of HELCOM core indicators included (coastal assessment units) "F__of_area = % of area assessed "D1C2" = MSFD descriptor 1 criteria 2 "Number_of" = Number of open sea species included "Confidence" = Confidence of the assessment "BQR_Demer" = Demersal Biological Quality Ratio "F_spec_Deme" = Number of demersal species included "Conf_Demer" = Confidence for demersal species "BQR_Pelagi" = Pelagic Biological Quality Ratio "F_specPela" = Number of pelagic species included "Conf_Pelag" = Confidence for pelagic species "ICES_SD" = ICES Subdivision number "STATUS" = Integrated status category (0-0.2 = not good (lowest score), 0.2-0.4 = not good (lower score), 0.4-0.6 = not good (low score), 0.6-0.8 = good (high score, 0.8-1.0 = good (highest score))

NLS-FI INSPIRE View Service for Buildings Theme is an INSPIRE compliant Web Map Service. It contains the following harmonized INSPIRE map layers: Building. The service is based on the NLS-FI INSPIRE Buildings Dataset. The dataset is administrated by the National Land Survey of Finland.

NLS-FI INSPIRE View Service for Cadastral Parcels Theme is an INSPIRE compliant Web Map Service. It contains the following harmonized INSPIRE map layers: CadastralParcel, CadastralBoundary. The service is based on the NLS-FI INSPIRE Cadastral Parcels dataset. The dataset is administrated by the National Land Survey of Finland.

The EMODnet (European Marine Observation and Data network) Geology project collects and harmonizes marine geological data from the European sea areas to support decision making and sustainable marine spatial planning. The partnership includes 39 marine organizations from 30 countries. The partners, mainly from the marine departments of the geological surveys of Europe (through the Association of European Geological Surveys-EuroGeoSurveys), have assembled marine geological information at various scales from all European sea areas (e.g. the White Sea, Baltic Sea, Barents Sea, the Iberian Coast, and the Mediterranean Sea within EU waters). This dataset includes EMODnet seabed substrate maps at a scale of 1:50 000 from the European marine areas. Traditionally, European countries have conducted their marine geological surveys according to their own national standards and classified substrates on the grounds of their national classification schemes. These national classifications are harmonised into a shared EMODnet schema using Folk's sediment triangle with a hierarchy of 16, 7 and 5 substrate classes. The data describes the seabed substrate from the uppermost 30 cm of the sediment column. Further information about the EMODnet Geology project is available on the portal (http://www.emodnet-geology.eu/).

This dataset contains borders of the HELCOM MPAs (former Baltic Sea Protected Areas (BSPAs). The dataset has been compiled from data submitted by HELCOM Contracting Parties. It includes the borders of designated HELCOM MPAs stored in the http://mpas.helcom.fi. The designation is based on the HELCOM Recommendation 15/5 (1994). The dataset displays all designated or managed MPAs as officially reported to HELCOM by the respective Contracting Party. The latest related HELCOM publication based on MPA related data is http://www.helcom.fi/Lists/Publications/BSEP148.pdf The dataset contains the following information: MPA_ID: Unique ID of the MPA as used in HELCOM Marine Protected Areas database Name: Name of the MPA Country: Country where MPA is located Site_link: Direct link to site's fact sheet in the http://mpas.helcom.fi where additional information is available MPA_status: Management status of the MPA Date_est: Establishment date of the MPA Year_est: Establishment year of the MPA

NLS-FI INSPIRE Download Service (WFS) for Cadastral Parcels Theme is an INSPIRE compliant direct access Web Feature Service. It contains the following INSPIRE feature types: BasicPropertyUnit, CadastralParcel, CadastralBoundary. The service is based on the NLS-FI INSPIRE Cadastral Parcels dataset. The dataset is administrated by the National Land Survey of Finland.

The 1:250 000 data on the soft and hard areas of the seabed supplements the seabed substrate data produced by the Geological Survey of Finland (GTK) for areas for which actual survey data is unavailable. The data covers two categories; hard and soft seabed areas. The substrate types categorised as hard seabed areas cover types ranging from gravel to boulders and exposed rock, and the substrate types for soft seabed areas cover types from silt to sand. The model is based on the marine geological survey data of GTK, the substrate observations made by the Finnish Environment Institute (SYKE) and Metsähallitus, and on the environment variable data produced by the Finnish Inventory Programme for the Underwater Marine Environment, VELMU, particularly on depth and seabed openness models. The data has undergone statistical evaluation and the ultimate model is based on expert estimates and modelling. At its most precise, the data is at a scale of 1:250 000 and the areas with a size less than 0.3 square kilometres have been removed. The substrate type information pertaining to restricted areas has been removed from the final data. A permit (AK15246) for publishing data with a similar scale, i.e. the EMODnet data, was received from the Defence Command of the Finnish Defence Forces on 28 July 2014.

Tämän aineiston tarkemmat metodikuvaukset löytyvät artikkeleista (Holmberg et al. 2023, Junttila et al. 2023). Tässä on kuvattu aineistoa ja sen valmistelua. Tarkoituksena on ollut tuottaa alueellista tietoa maanpeitteen merkityksestä kasvihuonekaasupäästöihin Suomessa. Lähtöaineisto ja metodit rajoittavat tarkkuutta, mutta aineisto soveltuu paikallisten, esimerkiksi maakuntatason ilmiöiden tarkasteluun. Aineisto edustaa lyhyttä ajanjaksoa. Maanpeiteaineisto perustuu rekisteritietoihin ja kaukokartoitusaineistoon vuosilta 2015-2020, lukuun ottamatta maaperäaineistoa, jokia ja järviä. Aineisto on rasterimuotoista ja tallennettu GeoTiff-formaatissa, joka on yhteensopiva useimpien paikkatieto-ohjelmistojen kanssa. Greenhouse gas net emission intensities by land cover category in Finland The methods related to the data published herein are described in detail in the associated publications (Holmberg et al. 2023, Junttila et al. 2023). This file describes the datasets and the data preparation steps. The aim of this data publication is to provide regional assessments of the role of land cover in greenhouse gas emissions in Finland. The results in the publications are reported for the large administrative divisions, the NUTS 3 regions of mainland Finland (Statistics Finland 2023a). While limited by the accuracy of the methods and source data involved, these data can also be used for more local assessments, e.g., at the scale of municipalities. The data represent a temporal snapshot of land cover. Except for the soil maps, rivers and lakes, all land cover data are from the period 2015-2020 and are based on registry data or remote sensing. Data format. The data are distributed as GeoTiff raster files, which can be read using most GIS-software.

This dataset contains points of information describing the location and size of spills of mineral oil observed during aerial surveillance flights by HELCOM Contracting Parties during 1998-2023. The data covers detections from fixed-wing aircraft only. Since 2014 Contracting Parties have also reported spills of other substances and unknown substances. The purpose of the regional aerial surveillance is to detect spills of oil and other harmful substances and thus prevent violations of the existing regulations on prevention of pollution from ships. Such illegal spills are a form of pollution which threatens the marine environment of the Baltic Sea area. Further information on detected spills in the Baltic Sea area and HELCOM aerial surveillance activities can be found at http://www.helcom.fi/baltic-sea-trends/maritime/illegal-spills/ and https://helcom.fi/action-areas/response-to-spills/aerial-surveillance/ The dataset contains the following information: Country Year Spill_ID = A unique code which will enable each individual spill to be individually identified FlightType = The type of flight the detection was made during: National = "N", CEPCO = "C", Super CEPCO = "SC", Tour d’Horizon = “TDH” Date = The date of the detection (dd.mm.yyyy) Time_UTC = The time of the detection in UTC (hh:mm) Wind_speed = The wind speed at the time of the detection (m/s) Wind_direc = The wind direction in degrees at the time of the detection (degrees) Latitude = The latitude of the detection (decimal degrees, WGS84) Longitude = The longitude of the detection (decimal degrees, WGS84) Length__km = The length of the detection (km) Width__km = The width of the detection (km) Area__km2_ = The area of the detection (km2) Spill_cat = Spill/pollution category: Mineral Oil = “Oil", Other Substance = "Other substance" , "Unknown substance" = “Unknown” EstimVol_m = If Spill_cat="Oil", then estimated min. volume of oil spill. Volume of the detection confirmed/observed as mineral oil as calculated using the Bonn Agreement Oil Appearance Code using the lower figure (BAOAC minimum) in m3. Vol_Category = Category of the detection: <0,1m3 = “1”, <0,1-1m3 = “2”, 1-10 m3 = “3”, 10-100 m3 = “4”, >100 m3 = “5” Type_substance = If Spill_cat="Other substance" or "Unknown. Product name or type of OS or GAR substances that could be identified (in case of known polluter, or via visual identification - cf. BAOAC Atlas). - Examples for OS: vegetable oils (palm oil sun flower oil, soya oil etc.), fish oil, molasses, various chemicals (methanol, biodiesels/FAME, toluene, paraffines etc.); Examples of GAR: solid cargo residues (e.g. coal residues), plastics, fish nets, … OR "Unknown" (in case the type of substance could not be identified) Polluter = Type of polluter source: Offshore Installation = “Rig”, Vessel = “Ship”, Other Polluter or source (e.g. land based source) = “Other”, Unknown = “Unknwon” (in case of an “orphan” spill that cannot be linked to a polluter) Remarks = Any additional information to inform on particular situations Description of marine litter sightings