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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.

  • Air traffic network-product is a link-knot routing dataset compliant with INSPIRE requirements. It includes f.ex. flight routes and aerodromes. Data shall not be used for operational flight activities or flight planning.

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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: High Biodiversity Value Forests 2018 (Zonation) nationwide High Biodiversity Value Forests 2018 (Zonation) regional Detailed poster available: OR Detailed report (only in Finnish): 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 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

  • The Arctic SDI Gazetteer Service is a service that contains authoritative place names data from the arctic area. The service can be used for searching place names and performing reverse geocoding. The service contains about 2.87 million place name locations with about 3.15 million place names. It contains data from following sources: * Canada (Natural Resources Canada, updated: 02/2018) * Denmark (including Greenland) (SDFE, updated: 05/2017) * Finland (National Land Survey of Finland, updated: 04/2017) * GEBCO Undersea feature names gazetteer (updated: 04/2019) * Iceland (National Land Survey of Iceland, updated: 08/2017) * Norway (Norwegian Mapping Authority, updated: 08/2017) * Russia (Russian Mapping Agency, updated: 04/2019) * Sweden (Swedish National Mapping Agency, updated: 05/2017) * USA (US Geological Survey, updated: 05/2017)

  • The raw materials of forest chips in Biomass Atlas are small-diameter trees from first thinning fellings and logging residues and stumps from final fellings. The harvesting potential consists of biomass that would be available after technical and economic constraints. Such constraints include, e.g., minimum removal of energywood per hectare, site fertility and recovery rate. Note that the techno-economic potential is usually higher than the actual availability, which depends on forest owners’ willingness to sell and competitive situation. The harvesting potentials were estimated using the sample plots of the 11th and 12th national forest inventory (NFI11 and NFI12) measured in the years 2013–2017. First, a large number of sound and sustainable management schedules for five consecutive ten-year periods were simulated for each sample plot using a large-scale Finnish forest planning system known as MELA (Siitonen et al. 1996; Hirvelä et al. 2017). MELA simulations consisted of natural processes and human actions. The ingrowth, growth, and mortality of trees were predicted based on a set of distance-independent tree-level statistical models (e.g. Hynynen et al. 2002) included in MELA and the simulation of the stand (sample plot)-level management actions was based on the current Finnish silvicultural guidelines (Äijälä et al. 2014) and the guidelines for harvesting of energy wood (Koistinen et al. 2016). Future potentials were assumed to materialize when the industrial roundwood fellings followed the level of maximum sustainable removals (80.7 mill. m3 in this calculation). The maximum sustainable removals were defined such that the net present value calculated with a 4% discount rate was maximized subject to non-declining periodic industrial roundwood and energy wood removals and net incomes, and subject to the saw log removal remaining at least at the level of the first period. There were no constraints concerning tree species selection, cutting methods, age classes, or the growth/drain ratio in order to efficiently utilize the dynamics of forest structure. The potential for energywood from first thinnings was calculated separately for all the wood from first thinnings (Small-diameter trees from first thinnings) and for material that does not fulfill the size-requirements for pulpwood (Small-diameter trees from first thinnings, smaller than pulpwood). The minimum top diameter of pulpwood in the calculation was 6.3 cm for pine (Pinus sylvestris) and 6.5 cm for spruce (Picea abies) and broadleaved species (mainly Betula pendula, B. pubescens, Populus tremula, Alnus incana, A. glutinosa and Salix spp.). The minimum length of a pulpwood log was assumed at 2.0 m. The potentials do not include branches. The potentials for logging residues and stumps were calculated as follows: The biomass removals of clear fellings were obtained from MELA. According to harvesting guidelines for energywood (Koistinen et al. 2016) mineral soils classified as sub-xeric (or weaker) and peatlands with corresponding low nutrient levels were left out from the potentials. Finally, technical recovery rates were applied (70% for logging residues and 82-84% for stumps) (Koistinen et al. 2016; Muinonen et al. 2013) The techno-economical harvesting potentials were first calculated for nineteen Finnish regions and then distributed on a raster grid at 1 km × 1 km resolution by weighting with Multi-Source NFI biomasses as described by Anttila et al. (2018). The potentials represent time period 2025-2034 and are presented as average annual potentials in solid cubic metres over bark. References Äijälä O, Koistinen A, Sved J, Vanhatalo K, Väisänen P. 2014. Metsänhoidon suositukset. [Guidelines for sustainable forest management]. Metsätalouden kehittämiskeskus Tapion julkaisuja. Anttila P., Nivala V., Salminen O., Hurskainen M., Kärki J., Lindroos T.J. & Asikainen A. 2018. Regional balance of forest chip supply and demand in Finland in 2030. Silva Fennica vol. 52 no. 2 article id 9902. 20 s. Hirvelä, H., Härkönen, K., Lempinen, R., Salminen, O. 2017. MELA2016 Reference Manual. Natural Resources Institute Finland (Luke). 547 p. Hynynen J, Ojansuu R, Hökkä H, Salminen H, Siipilehto J, Haapala P. 2002. Models for predicting the stand development – description of biological processes in MELA system. The Finnish Forest Research Institute Research Papers. 835. Koistinen A, Luiro J, Vanhatalo K. 2016. Metsänhoidon suositukset energiapuun korjuuseen, työopas. [Guidelines for sustainable harvesting of energy wood]. Tapion julkaisuja. Muinonen E., Anttila P., Heinonen J., Mustonen J. 2013. Estimating the bioenergy potential of forest chips from final fellings in Central Finland based on biomass maps and spatially explicit constraints. Silva Fennica 47(4) article 1022. Siitonen M, Härkönen K, Hirvelä H, Jämsä J, Kilpeläinen H, Salminen O et al. 1996. MELA Handbook. 622. 951-40-1543-6.

  • KUVAUS Herkät vesistöt, joiden rajaus on luotu Viherkertoimen käyttöä varten. Aineisto perustuu hulevesiohjelmassa määritettyihin osavaluma-alueisiin, joiden avulla aineisto on rajattu. Näillä alueilla huleveden laadulliseen hallintaan on kiinnitettävä erityistä huomiota. Hulevesiohjelmaan liittyvän aineiston lisäksi rajausta on arvioitu asiantuntijoiden toimesta. Viherkerroinmenetelmä on ekologinen suunnittelutyökalu tonttien viherpinta-alan arviointiin. Viherkerroinmenetelmän avulla etsitään vaihtoehtoisia ratkaisutapoja kaupunkivihreän lisäämiseen sekä hulevesien hallintaan. KATTAVUUS; PÄIVITYS; LUOTETTAVUUS Aineisto on laadittu viherkertoimen käyttöön ja päivittyy tiedon tarkentuessa. YLLÄPITOSOVELLUS; KOORDINAATISTOJÄRJESTELMÄ; GEOMETRIA; SAATAVUUS; JULKISUUS Laadittu MapInfossa. Aineisto tallennetaan ETRS-GK24 (EPSG:3878) tasokoordinaattijärjestelmässä. Aluemuotoista tietoa. Aineisto on saatavilla WFS rajapinnalta, aineisto on tallennettu Oracle-tietokantaan. YHTEYSHLÖ Sanna Markkanen JULKISUUS Sisäisesti julkinen

  • The Topographic map series is a dataset depicting the terrain of all of Finland. The key elements in it are the road network, buildings and constructions, geographic names, waterways, land use and elevation. The more precise levels of the Topographic map series consist of the same map objects and map symbols depicted in the same way as in the familiar Basic map. Basic map raster is applicable to be used, for instance, as a base map for planning land use or for excursion and outdoor recreational purposes in mobile devices and in various Internet services associated with nature. When going over to the more general datasets in the Topographic map series, the number and visualisation of objects and map symbols changes. The generalised small-scale Topographic maps raster are applicable to be used as approach maps in e.g. mobile devices and Internet services. The product belongs to the open data of the National Land Survey of Finland. More information: Topographic data and how to acquire it

  • Seabed substrate 1:250 000 is one of the products produced in the EMODnet (European Marine Observation and Data network) Geology EU project. Project provided seabed geological material from the European maritime areas. The EMODnet Geology project ( collects and harmonizes geological data from the European sea areas to support decision-making and sustainable marine spatial planning. The EMODnet Geology partnership has included 36 marine organizations from 30 countries. This data includes the EMODnet seabed substrate map at a scale of 1:250 000 from the Finnish marine areas. It is based on the data produced on a scale of 1:20 000 by the Geological Survey of Finland (GTK), which does not cover the whole Finnish marine area yet. The seabed substrate data will be updated with a new interpreted data on a yearly basis.The data has been harmonized and reclassified into five Folk substrate classes (mud, sandy clays, clayey sands, coarse sediments, mixed sediments) and bedrock. The data describes the seabed substrate from the uppermost 30 cm of the sediment column. The data have been generalized into a target scale (1:250 000). The smallest smallest cartographic unit within the data is 0.3 km2 (30 hectares). Further information about the EMODnet-Geology project is available on the portal ( Permission (AK15246) to publish the material was obtained from the Finnish Defence Office 28.07.2014

  • National Land Survey's Topographic map series in vector format is a dataset depicting the terrain of all of Finland. The most important elements are the road network, administrative borders, preservation areas, population centres, geographic names, waterways, land use and elevation. The largest scale level (1:100,000) of the Topographic map series in vector format is produced by generalising from the Topographic database. Topographic map series 1:250,000 is produced by generalising the dataset 1:100,000. Topographic map series 1:1,000,000 is produced by generalising the dataset 1:250,000. Topographic map series 1:4,500,000 is produced by generalising the dataset 1:1,000,000. The geographic names have been generalised from the geographic names in the Geographic Names Register to map names suited to the scale in question. The administrative borders in the Municipal Division of each scale are used as administrative borders. The Topographic map series in vector format can be used for the production of other map products, e.g. approach maps or maps on a regional or national level The product belongs to the open data of the National Land Survey of Finland. More information: Topographic data and how to acquire it

  • Field biomass sidestreams GIS data describes the maximum harvestable sidestream potential based on current tillage. Sidestreams has been calculated by crop statistics, cultivation area, solid content and harvest index. Harvest index describes the part of the plant that is utilized as a crop. Rest of the plant is considered sidestream. In many cases the maximum sidestream cannot be necessarily utilized as whole, because of technical and economical constraints for harvest. Part of the sidestream is also wise to plough in to field to maintain its fertility. Field crop data is conducted from Luke's crop production statistics. The crop statistics in ELY centre level is divided into the Biomass Atlas grid weighting by the crop area of that certain plant. Crop area is from IACS-register, used to manage subsidies in agriculture. Farmers report their cultivation plans there every spring. Crop area and amount are from same year, usually previous year.