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environment

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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. Five sets of estimates have been produced for the most part of the country until now and four sets for Lapland. The number of the map form themes in the most recent version, from year 2009, is 43. 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 and 2009. MS-NFI 2011 will be ready early 2013. The first set of the products freely available are from year 2009. The new set of the products will be produced annually or biannually in the future. The map from products are in a raster format with a pixel size of 20mx20m and in 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 topographic database of the Land Survey of Finland.

  • 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 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))

  • This dataset represents the integrated assessment of hazardous substances in the Baltic Sea in 2011-2016, assessed using the CHASE tool (https://github.com/helcomsecretariat/CHASE-integration-tool). The integration is based on hazardous substances core indicators covering concentrations of hazardous substances. This dataset displays the result of the assessment in HELCOM Assessment unit Level 3 (Division of the Baltic Sea into 17 sub-basins and further division into coastal and offshore areas). Attribute information: "HELCOM_ID" = ID of the HELCOM scale 3 assessment unit "country" = Country/ opensea "level_3" = Name of the HELCOM scale 3 assessment unit "area_km2 = Area of the HELCOM scale 3 assessment unit "AULEVEL" = Scale of the assessment units "coastal" = Code of scale 3 HELCOM assessment unit "Input" = Contamination ratio of the assessment unit (Higher score indicates higher contamination) "Confidence" = Confidence of the assessment (Low/ Moderate/ High/ Not assessed) "Status" = Status value for the assessment (= 1.0: Low contamination score, > 1.0: High contaminantion score)

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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/

  • 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))

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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. Six sets of estimates have been produced for the most part of the country until now and five sets for Lapland. The number of the map form themes in the most recent version, from year 2011, 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 and 2011. The maps from 2011 is the second set of products freely available. The 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 20mx20m 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 topographic database of the Land Survey of Finland.

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    Forests of high biodiversity value 2018 (Zonation) datapackage consists of 12 nationwide raster maps from Finland. These 12 maps are all different versions of biodiversity values of Finnish forests. Resolution of these raster maps is 96 meters x 96 meters. Simple instructions for reading the raster maps: The bigger the numeric value the higher the biodiversity value. NAT = National scale analyses of biodiversity values of Finnish forests (6 analysis) REG = Regional scale analyses of biodiversity values of Finnish forests (map looks like one but is in reality a collection of 13 separately done analysis, region = Centre for Economic Development, Transport and the Environment in Finland) (6 analysis) Six different spatial conservation prioritizations were made with Zonation Software (a) so that each new version included everything that had been included in previous, simpler, analysis versions. NAT / REG 1 Decaying wood potential: Version 1 (V1) included the local decaying wood potentials*. Areas with lot of large trees, many tree species and rare forest environments get high local value. NAT / REG 2 Decaying wood potential – penalties: Version 2 = V1 + penalties for forestry operations with negative impact on biodiversity. More realistic local values when taking into account real life changes in forests. NAT / REG 3 Decaying wood potential – penalties + forest connectivity: Version 3 = V2 + connectivity based on ecological similarity, distance and quality between forest patches (attenuation avg. 400m). Unfragmented high value forests areas emerge. NAT / REG 4 Decaying wood potential – penalties + forest connectivity + RL species: Version 4 = V3 + observations of Red List forest species. Red List forest species habitats emerge. NAT / REG 5 Decaying wood potential – penalties + forest connectivity + RL species + FFA 10§: Version 5 = V4 + connectivity to woodland key habitats protected by Finnish Forest Act 10 § (attenuation avg. 200m). Valuable forest areas and landscapes close to protected high biodiversity forest patches emerge. NAT / REG 6 Decaying wood potential – penalties + forest connectivity + RL species + FFA 10§ + PA connectivity: Version 6 = V5 + connectivity to permanent conservation areas (attenuation avg. 2km). Valuable forest areas and landscapes close to protected high biodiversity areas emerge. *Calculation of Decaying wood potential (DWP) DWP was calculated for every strata of tree species in every crown storey class in 2 stages: 1) Decaying wood potential indexes (DWPi) were modelled with MOTTI-program (b, c, d). • 168 tree species, fertility class and latitude combinations 2) DWPis were used for converting diameter and volume into decaying wood potential • Generated for the whole Finland at tree stand level at the resolution of 16 m x 16 m • Eventually combined into 20 tree species & fertility classes and aggregated to 96 m x 96 m resolution. Input data Decaying wood potential was calculated from forest stand level datasets (tree species, diameter, volume, fertility) covering whole Finland. Best possible data was used for every area. - 24 % of Finland covered by state-owned forestry and conservation areas and private conservation areas o Metsähallitus Parks & Wildlife: field and forest stand data (5/2015) o Metsähallitus Forestry Inc.: field and forest stand data (5/2015) o Private owned conservation areas: field and forest stand data (5/2015) - 37 % of Finland covered by privately owned other than protected forest areas: Finnish Forest Centre, forest information (6.5.2005 – 6.5.2015) - 39 % of Finland covered by o Natural Resources Institute Finland: Multi-source national forest inventory data of Finland 2013(volume, tree species, fertility class, diameter) Spatial data on forestry operations with negative impact on biodiversity (e. g. fellings, thinning and ditching) (updated 10/2017) - National Land Survey of Finland & Finnish Environment Institute SYKE: Ditching state of Finnish peatlands (SOJT_09b1) - Metsähallitus Forestry Inc.: Executed forest operations of forest operations from field and forest stand data and ditching status - Finnish Forest Centre: Forest declariations and ditching status - University of Maryland / Dept. of Geographica Sciences: Global Forest Change / Forest Cover Loss 2000-2014 Observations of IUCN Red List forest species (since 1990): Finnish Environmental database HERTTA Spatial data on woodland key habitats protected by The Finnish Forest Act 10§ (updated 10/2017) - Finnish Forest Centre: woodland key habitats protected by Finnish Forest act 10§ Spatial data on permanent conservation areas (updated 2/2018) - Metsähallitus Parks & Wildlife: Conservation area database SATJ Background Areas important to forest biodiversity were identified throughout Finland to support sustainable land using planning and nature conservation at local, regional and national level by informing land owners, ministries and forestry stakeholders. Importance of analyzes like this rise from increased usage of natural resources and consequent harmful impacts on biodiversity together with limited resources for conservation. These highlight the importance of developing cost-effective, ecologically sustainable land use planning approaches such as these spatial conservation prioritizations of forests made for a first time for the whole Finland. Prioritization approach, Zonation, was used to find new forest areas of potential high conservation value. The overall aim was to implement nationwide prioritization analyses based on biodiversity-related forest data and land use data recorded at the level of forest stand. Primarily employed data on forest structure and quality (vegetation class, tree species, volume and diameter) provided ecologically useful surrogates for conservation value in boreal forest. Results show that a significant portion of high biodiversity value forests lay outside the current Finnish protected area (PA) network. As most of the Finnish forest area is under commercial management, PA network cannot halt the on-going decline of forest biodiversity. Keywords: biodiversity value, decaying wood, forest biodiversity, Forest Biodiversity Programme for Southern Finland (METSO), forest conservation, forestry, geographical information system (GIS), land use, spatial conservation prioritization, Zonation software Datapackage includes all 12 raster maps and a .lyr -file. .lyr -file contains coloured symbology and descriptions of different analysis versions. .lyr -file is probably operable only with GIS-software prvided by ESRI Inc. Datapackage can be loaded from: http://www.syke.fi/en-US/Open_information/Spatial_datasets High Biodiversity Value Forests 2018 (Zonation) nationwide High Biodiversity Value Forests 2018 (Zonation) regional Detailed poster available: http://www.syke.fi/en-US/Research__Development/Ecosystem_services/Specialist_work/Zonation_in_Finland/Zonation_materials/Posters OR http://www.syke.fi/download/noname/%7B771FF5A4-DAB6-45EE-8246-F38FC0090CAD%7D/138289 Detailed report (only in Finnish): http://hdl.handle.net/10138/234359 Mikkonen et al. 2018. Suomen ympäristökeskuksen raportteja 9/2018. Monimuotoisuudelle tärkeät metsäalueet Suomessa - Puustoisten elinympäristöjen monimuotoisuusarvojen Zonation-analyysien loppuraportti. Other references: a) Moilanen et al. 2014. Zonation–Spatial Conservation Planning Methods and Software. Version 4. User Manual. See also www.syke.fi/Zonation/en b) Hynynen et al. 2015. Eur. J. For. Res. 134/3. Long-term impacts of forest management on biomass supply and forest resource development: a scenario analysis for Finland. c) Hynynen et al. 2014. Metlan työraportteja 302. Scenario analysis for the biomass supply potential and the future development of Finnish forest resources. d) Salminen et al. 2005. Comput. electron. agr. 49/1. Reusing legacy FORTRAN in the MOTTI growth and yield simulator. Availability: Aineisto kuuluu SYKEn avoimiin aineistoihin (CC BY 4.0) Creative Commons 4.0. © SYKE Datasources: Finnish Forest Centre, Metsähallitus, Natural Resources Institute Finland 2015, National Land Survey of Finland, Hansen/UMD/Google/USGS/NASA

  • This dataset contains points of information describing the location and size of illegal oil discharges observed during aerial surveillance flights by HELCOM Contracting Parties during 1998-2017. 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, 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 = The category of the detection: OIL 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

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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. Seven sets of estimates have been produced for the most part of the country until now and six sets for Lapland. The number of the map form themes in the most recent version, from year 2015, 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 and 2015. The maps from 2015 is the fourth set of products freely available. It is also the second 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.