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  • This dataset contains the ship accidents in the Baltic Sea during the period 1989 to 2017. It is constructed from the annual data collected by HELCOM Contracting Parties on ship accidents in the Baltic Sea. The accident data has been compiled by the HELCOM Secretariat. According to the decision of the HELCOM SEA 2/2001 shipping accident data compilation will include only so called conventional ships according to the Regulation 5, Annex I of MARPOL 73/78 - any oil tanker of 150 GT and above and any other ships of 400 GT and above which are engaged in voyages to ports or offshore terminals under the jurisdiction of other Parties to the Convention. According to the agreed procedure all accidents (including but not limited to grounding, collision with other vessel or contact with fixed structures (offshore installations, wrecks, etc.), disabled vessel (e.g. machinery and/or structure failure), fire, explosions, etc.), which took place in territorial seas or EEZ of the Contracting Party irrespectively if there was pollution or not, are reported. The dataset contains the following information: Country Year Latitude = Latitude (decimal degrees) Longitude = Longitude (decimal degrees) Cause_details = Details on the accident cause Offence = Offence against Rule Damage = Damage Assistance = assistance after the accident Pollution = Pollution (Yes/No) Date = Date (dd.mm.yyyy) Time = Time (hh:mm) Location = Location of the accidents (open sea / port approach / at port) Sh1_Categ = Ship 1 type (according to AIS category) Sh1_Type = Ship 1 more detail ship type category Sh1_Hull = Ship 1 hull construction Sh1Size_gt = Ship 1 GT Sh1Sizedwt = Ship 1 DWT Ship1Draug_m = Ship 1 draught in meters Sh2_Categ = Ship 2 type (according to AIS category) Sh2_Type = Ship 2 more detail ship type category Sh2_Hull = Ship 1 hull construction Sh2Size_gt = Ship 2 GT Sh2Sizedwt = Ship 2 DWT Ship2Draug_m = Ship 2 draught in meters Acc_type = Type of accidents Colli_type = Type of collisions Acc_Detail = More information on the accident Cause_Sh1 = Cause of accidents from ship 1 Cause_Sh2 = Cause of accidents from ship 2 HumanEleme = Reason of human error IceCondit = Ice conditions CrewIceTra = Crew trained for ice conditions Pilot_Sh1 = Presence of pilot on ship 1 Pilot_Sh2 = Presence of pilot on ship 2 Pollu_m3 = Pollution in m3 Pollu_t = Pollution in t Pollu_type = Type of pollution RespAction = Response actions after the accidents Add_info = Additionnal information Ship1_name = Ship 1 identification Ship2_name = Ship 2 identification Cargo_type = cargo type ship 1 For more information about shipping accidents in the Baltic Sea, see the HELCOM annual reports: http://www.helcom.fi/action-areas/shipping/publications/

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    The Finnish Forest Research Institute (Metla) developed a method called multi-source national forest inventory (MS-NFI). The first operative results were calculated in 1990. Small area forest resource estimates, in here municipality level estimates, and estimates of variables in map form are calculated using field data from the Finnish national forest inventory, satellite images and other digital georeferenced data, such as topographic database of the National Land Survey of Finland. Nine sets of estimates have been produced for the most part of the country until now and eight sets for Lapland. The number of the map form themes in the most recent version, from year 2019, is 45. In addition to the volumes by tree species and timber assortments, the biomass by tree species groups and tree compartments have been estimated. The first country level estimates correspond to years 1990-1994. The most recent versions are from years 2005, 2007, 2009, 2011, 2013, 2015, 2017 and 2019. The maps from 2019 is the fifth set of products freely available. It is also the fourth set produced by the Natural Resources Institute Finland. A new set of the products will be produced annually or biannually in the future. The maps are in a raster format with a pixel size of 16m x 16m (from 2013) and in the ETRS-TM35FIN coordinate system. The products cover the combined land categories forest land, poorly productive forest land and unproductive land. The other land categories as well as water bodies have been delineated out using the elements of the topographic database of the Land Survey of Finland.

  • Potential cumulative impacts on benthic habitats is based on the same method than <a href="http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/9477be37-94a9-4201-824a-f079bc27d097" target="_blank">Baltic Sea Impact Index</a>, but is focused on physical pressures and benthic habitats. The dataset was created based on separate analysis for potential cumulative impacts on only the benthic habitats, as these are particularly affected by physical pressures. In this case the evaluation was based on pressure layers representing <a href="http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/ea0ef0fa-0517-40a9-866a-ce22b8948c88" target="_blank">physical loss</a> and <a href="http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/05e325f3-bc30-44a0-8f0b-995464011c82" target="_blank">physical disturbance</a>, combined with information on the distribution of eight broad benthic habitat types and five habitat-forming species (<a href="http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/363cb353-46da-43f4-9906-7324738fe2c3" target="_blank">Furcellaria lumbricalis</a>, <a href="http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/f9cc7b2c-4080-4b19-8c38-cac87955cb91" target="_blank">Mytilus edulis</a>, <a href="http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/264ed572-403c-43bd-9707-345de8b9503c" target="_blank"> Fucus sp.</a>, <a href="http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/822ddece-d96a-4036-9ad8-c4b599776eca" target="_blank">Charophytes</a> and <a href="http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/ca327bb1-d3cb-46c2-8316-f5f62f889090" target="_blank">Zostera marina</a>). The potential cumulative impacts has been estimated based on currently best available data, but spatial and temporal gaps may occur in underlying datasets. Please scroll down to "Lineage" and visit <a href="http://stateofthebalticsea.helcom.fi/cumulative-impacts/" target="_blank">State of the Baltic Sea website</a> for more info.

  • This dataset represents the Integrated biodiversity status assessment for seals (grey seal, harbour seal and ringed seal). Status is shown in five categories based on the integrated assessment scores obtained in the tool. Biological quality ratios (BQR) above 0.6 correspond to good status. The status of the seals was assessed using four core indicators: population trends and abundance of seals, distribution of Baltic seals, nutritional status of seals, and reproductive status of seals. In the latter two only grey seals are considered for the 2018 State of the Baltic Sea report. The assessment is based on the one-out-all-out approach, i.e. the species reflecting the worst status in each assessment unit. This dataset displays the result of the integrated biodiversity status in HELCOM Assessment unit Scale 2 (Division of the Baltic Sea into 17 sub-basins). Attribute information: "HELCOM_ID" = ID of the HELCOM scale 2 assessment unit "level_2" = Name of the HELCOM scale 2 assessment unit "EcosystemC" = Ecosystem component analyzed "BQR" = Biological Quality Ratio "Conf" = Confidence of the assessment "Total_indi" = Number of indicators used "% of area assessed" = Share of the total assessed area "D1CX" = MSFD descriptor 1 criteria X "conf_D1CX" = Confidence for MSFD descriptor criteria X "Confidence" = Conifdence of the assessment ("high"/ "moderate"/ "low") "STATUS" = Status of the assessment (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))

  • This dataset contains points of information describing the location and size of other discharges than illegal oil discharges observed during aerial surveillance flights by HELCOM Contracting Parties 2014-2017. Further information about illegal discharges of oil in the Baltic Sea area and HELCOM aerial surveillance activities can be found at http://www.helcom.fi/baltic-sea-trends/maritime/illegal-spills/ The dataset contains the following information: Country Year Spill_ID= Spill ID FlightType= The type of flight the detection was made during: National = "N", CEPCO = "C", Super CEPCO = "S" Date= The date of the detection (dd.mm.yyyy) Time_UTC= The time of the detection (hh:mm) Wind_speed= The wind speed at the time of the detection (m/s) Wind_direc= The wind direction at the time of the detection (degrees) Latitude= The latitude of the detection (decimal degrees) Longitude= The longitude of the detection (decimal degrees) 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= The category of the detection: other substance = "OS", unknown substance = "UNKNOWN" EstimVol_m= Estimated volume of the detection (m3) Polluter= Polluter (rig, ship, other, unknown) Category= Category of the detection: 100m3 = "5" Casefile= The name of the casefile the detection refers to Remarks= Any additional information

  • This dataset represents the Integrated biodiversity status assessment for benthic habitats using the BEAT tool. Status is shown in five categories based on the integrated assessment scores obtained in the tool. Biological Quality Ratios (BQR) above 0.6 correspond to good status. The assessment in open sea areas was based on the core indicators ‘State of the soft-bottom macrofauna community’ and ‘Oxygen debt’. Coastal areas were assessed by national indicators, and may hence not be directly comparable with each other. This dataset displays the result of the integrated biodiverity status in HELCOM Assessment unit Scale 4 (Division of the Baltic Sea into 17 sub-basins and further division into coastal and off-shore areas and division of the coastal areas by WFD water types or water bodies). Attribute information: "BQR" = Biological Quality Ratio "Confidence" = Confidence of the assessment "HELCOM_ID" = id of the HELCOM assessment unit "country" = name of the country / opensea "level_2" = HELCOM sub-basins (name of the scale 2 assessment unit) "Name" = Name of the coastal assessment unit on scale 4 "AULEVEL" = scale of the assessment units "type_descr" = Name of the HELCOM scale 4 assessment unit "SAUID" = ID number for the spatial assessment unit "EcosystemC" = Ecosystem component assessed "Confiden_1" = Confidence of the assessment (0-1, higher values mean higher confidence) "Total_numb" = Number of indicators used in assessment "Area_km2" = Area of assessment unit (km2) "Confiden_1" = Confidence level of the assessment (scores < 0.5 = low, 0.5 - 0.75 = intermediate, > 0.75 = high) "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))

  • 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 <a href="http://mpas.helcom.fi" target="_blank">HELCOM Marine Protected Areas database</a>. 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 State until in November 2018 (latest data update). The latest related HELCOM publication based on MPA related data is <a href="http://www.helcom.fi/Lists/Publications/BSEP148.pdf" target="_blank"> Ecological coherence assessment of the Marine Protected Area network in the Baltic. Balt. Sea Environ. Proc. No. 148 (HELCOM 2016)</a> 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 <a href="http://mpas.helcom.fi" target="_blank">HELCOM Marine Protected Areas database</a> 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

  • This dataset represents the Integrated biodiversity status assessment for pelagic habitats using the BEAT tool. Status is shown in five categories based on the integrated assessment scores obtained in the tool. Biological Quality Ratios (BQR) above 0.6 correspond to good status. Open sea areas were assessed based on the core indicators ‘Zooplankton mean size and total stock’ and ‘Chlorophyll-a’, as well as the pre-core indicator ‘Cyanobacterial bloom index’ . Coastal areas were assessed by national indicators. This dataset displays the result of the integrated biodiversity status in HELCOM Assessment unit Scale 4 (Division of the Baltic Sea into 17 sub-basins and further division into coastal and off-shore areas and division of the coastal areas by WFD water types or water bodies). Attribute information: "BQR" = Biological Quality Ratio "Confidence" = Confidence of the assessment "HELCOM_ID" = Code of the HELCOM assessment unit "Country" = Country of coastal assessment unit/ open sea "Level2" = HELCOM sub-basins (name of the scale 2 assessment unit) "Name" = Name of the HELCOM scale 4 assessment unit "Area_km2" = Area of assessment unit "AULEVEL" = scale of the assessment unit "HID" = assessment unit ID by country "SAUID" = ID number for the spatial assessment unit "EcosystemC" = Ecosystem component assessed "Confiden_1" = Confidence of the assessment (0-1, higher values mean higher confidence) "Total_numb" = Number of indicators used in assessment "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))

  • This dataset contains integrated eutrophication status assessment 2011-2016. The assessment is done using the HEAT 3.0 by combining assessment unit-specific results from various indicators by three MSFD criteria groups (C1: Nutrient levels, C2: Direct effect, C3: Indirect effect). The assessment is done on HELCOM Assessment Unit level 4: HELCOM Subbasins with coastal WFD water type or water bodies. The HEAT 3.0 has been applied for open sea assessment units using HELCOM core indicators and for coastal areas using national WFD indicators. In case of Denmark, the WFD results were used directly, displaying different classification as obtained from HEAT. For more information about the methodology, see the State of the Baltic Sea report and HELCOM Eutrophication assessment manual. Attribute information: "HELCOM_ID": ID of the HELCOM Level 4 Assessment unit "Country": Country/ Opensea "level_2": Name of the HELCOM Level 2 Assessment unit "Name": Name of the HELCOM Level 4 Assessment unit "Area_km2": Area of assessment unit "C1_N": MSFD criteria 1, number of indicators used for calculating Eutrophication Ratio (ER) "C1_ER": MSFD Criteria 1, ER "C1_SCORE": MSFD Criteria 1, Confidence of ER "C2_N": MSFD Criteria 2, number of indicators used for calculating ER "C2_ER": MSFD Criteria 2, ER "C2_SCORE": MSFD Criteria 2, Confidence of ER "C3_N": MSFD Criteria 3, number of indicators used for calculating ER "C3_ER": MSFD Criteria 3, ER "C3_SCORE": Criteria 3, Confidence of ER "N": Number of criteria used for calculating overall ER "ER": Overall ER "SCORE": Status confidence "STATUS": Status classification (Good (classes 0-0.5 & 0.5-1.0), Not Good (classes 1.0-1.5, 1.5-2.0 & >2.0), Not assessed) "CONFIDENCE": Final confidence class (< 50% = low, 50-74 % = Moderate, = 75 % = High) "AULEVEL": Level of assessment units

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    The Finnish Forest Research Institute (Metla) developed a method called multi-source national forest inventory (MS-NFI). The first operative results were calculated in 1990. The first country level estimates correspond to years 1990-1994. Small area forest resource estimates, in here municipality level estimates, and estimates of variables in map form are calculated using field data from the Finnish national forest inventory, satellite images and other digital georeferenced data, such as topographic database of the National Land Survey of Finland. Nine sets of estimates have been produced for the most part of the country until now and eight sets for Lapland. These three themes have been produced for production of the CORINE2006. The products cover the combined land categories forest land, poorly productive forest land and unproductive land. The other land categories as well as water bodies have been delineated out using the elements of the topographic database of the Land Survey of Finland. The original map data can be downloaded from http://kartta.luke.fi/