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  • 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.

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    Datapaketet Skogsområden med högt biodiversitetsvärde i Finland består av 12 landsomfattande rasterkartor. Dessa 12 kartor är olika versioner av biodiversitetsvärden i Finlands skogar. Rasterkartornas upplösning är 96 x 96 meter. Enkla anvisningar för att läsa rasterkartorna: Ju större numeriskt värde, desto högre biodiversitetsvärde. National = Nationella analyser över biodiversitetsvärden i finska skogar (sex analyser) Regional = Regionala analyser över biodiversitetsvärden i finska skogar (ser ut som en karta men är i själva verket en samling av 13 separata analyser, region = Närings-, trafik- och miljöcentralen i Finland) (sex analyser) Sex olika prioriteringar av naturskydd gjordes med Zonation-programvaran (a) så att varje ny version innefattade allt som fanns med i tidigare, enklare analysversioner. National / Regional 1 Potentiell mängd död ved: Version 1 (V1) innefattade potentiell mängd död ved* på lokal nivå. Områden med många stora träd, många trädslag och ovanliga skogsmiljöer får högt lokalt värde. National / Regional 2 Potentiell mängd död ved och straff: Version 2 = V1 + straff för åtgärder som har negativ inverkan på biodiversiteten. De lokala värdena stämde bättre överens med verkligheten när man tog hänsyn till verkliga förändringar i skogar. National / Regional 3 Potentiell mängd död ved – straff + skogskonnektivitet: Version 3 = V2 + konnektivitet utifrån ekologisk likhet, avstånd och kvalitet mellan skogsområden (genomsnittlig försvagning 400 m). Ofragmenterade skogsområden av hög kvalitet framkommer. National / Regional 4 Potentiell mängd död ved – straff + skogskonnektivitet + RL-arter: Version 4 = V3 + observationer av rödlistade skogsarter. Habitat med rödlistade skogsarter framkommer. National / Regional 5 Potentiell mängd död ved – straff + skogskonnektivitet + RL-arter + skogslagen 10 §: Version 5 = V4 + konnektivitet till särskilt viktiga livsmiljöer enligt skogslagens 10 § (genomsnittlig försvagning 200 m). Värdefulla skogsområden och landskap i närheten av skyddade skogsområden med högt biodiversitetvärde framkommer. National / Regional 6 Potentiell mängd död ved – straff + skogskonnektivitet + RL-arter + skogslagen 10 § + PN-konnektivitet: Version 6 = V5 + konnektivitet till permanenta naturskyddsområden (genomsnittlig försvagning 2 km). Värdefulla skogsområden och landskap i närheten av skyddade områden med högt biodiversitetvärde framkommer. *Uträkning av potentiell mängd död ved (PMDV) PMDV beräknades i två skeden för varje skikt träslag i varje trädskikt: 1) Index för potentiell mängd död ved (PMDVi) togs fram med MOTTI-programmet (b, c, d). • 168 trädslag, fertilitetsklass och latitudkombinationer 2) PMDVi användes för att omvandla diameter och volym till potentiell mängd död ved • Genererades för hela Finland enligt bestånd med en upplösning på 16 x 16 m • Kombinerades sedan i 20 trädslag och fertilitetsklasser och förenades till 96 x 96 m upplösning. Inmatade data Den potentiella mängden död ved beräknades från beståndsdata (trädslag, medeldiameter, volym, vegetationsklass) vilket omfattade hela landet. Bästa möjliga data användes för varje område. - 24 % av Finland täcks av statligt ägda skogs- och naturskyddsområden och privata naturskyddsområden. o Forststyrelsens Naturtjänster: data om fält- och bestånd (5/2015) o Forststyrelsens Skogsbruk: data om fält- och bestånd (5/2015) o Privatägda naturskyddsområden: data om fält- och bestånd (5/2015) - 37 % av Finland täcks av privatägd skog som inte är naturskyddsområden: Skogscentralen, skogsdata (6.5.2005–6.5.2015) - 39 % av Finland täcks av o Naturresursinstitutet: Nationella skogsinventariedata som är tillverkat med skogsinventeringsmetod som utnyttjar information om riksskogstaxeringens provytor och satellitbilder 2013 (volym, trädslag, vegetationsklass och medeldiameter) Spatiella data om skogsbruk med negativ effekt på biodiversitet (till exempel fällning, gallring och dikning) (uppdaterades 10/2017) - Lantmäterivärket och Finlands miljöcentral SYKE: dikning i finsk torvmark (SOJT_09b1) - Forststyrelsens Skogsbruk: utförda anmälningar om användning av skog och dikningsfigurer - Skogscentralen: anmälningar om användning av skog och dikningsfigurer - University of Maryland/Dept. of Geographica Sciences: Global Forest Change/Forest Cover Loss 2000-2014 Observationer av skogsarter som har rödlistats av IUCN (sedan 1990): Finländska miljödatabasen HERTTA Spatiella data om särskilt viktiga livsmiljöer enligt skogslagens 10 § (uppdaterades 10/2017) - Forststyrelsens Skogsbruk och Skogscentralen Spatiella data om permanenta naturskyddsområden (uppdaterades 2/2018) - Forststyrelsens Naturtjänster: databas över naturskyddsområden SATJ Bakgrund Områden som är viktiga för skogens biodiversitet identifierades runt om i Finland för att främja hållbar markanvändning genom planering och naturskydd på lokal, regional och nationell nivå genom att informera markägare, ministerier och skogtjästemän. Vikten av sådana analyser beror på ökad användning av naturresurser och skadliga effekter på biodiversiteten tillsammans med begränsade naturskyddsresurser. Dessa betonar vikten av att utveckla kostnadseffektiv, ekologiskt hållbar markanvändning som dessa spatiella prioriteringar av naturskydd för skogar som görs för första gången för hela Finland. Prioriteringsmetoden Zonation användes för att hitta nya skogsområden med potentiellt högt skyddsvärde. Det övergripande målet var att tillämpa rikstäckande prioriteringsanalyser utifrån skogsdata relaterade till biodiversitet och markanvändningsdata som hade samlats in på beståndsnivå. De data som primärt tillämpades på skogsstruktur och -kvalitet (vegetationsklass, trädslag, volym och diameter) gav ekologiskt användbara ersättningar för skyddsvärde i barrskog. Resultaten visar att en betydande andel skog med högt biodiversitetsvärde finns utanför det aktuella nätverket för finska naturskyddsområden. Eftersom största delen av det finska skogsområdet är kommersiellt kan nätverket för naturskyddsområden inte stoppa den pågående nedgången av biodiversitet i skogarna. Nyckelord: biodiversitet, död ved, GIS, Handlingsplanen för den biologiska mångfalden i skogarna i södra Finland METSO, markanvändning, värdering, prioritering, skogar, skogarnas biodiversitet, skogsbruk, skogsskydd, spatiell prioritering av naturskydd,Zonation-programvara Datapaketet innefattar 12 rasterkartor och en .lyr-fil. .lyr-filen innehåller färgade symboler och beskrivningar av olika analysversioner. .lyr-filen är troligen endast genomförbar med GIS-programmet som tillhandahålls av ESRI Inc. Datapaketet kan hämtas från: http://www.syke.fi/en-US/Open_information/Spatial_datasets High Biodiversity Value Forests 2018 (Zonation) nationwide High Biodiversity Value Forests 2018 (Zonation) regional Detailjerad poster på engelska: http://www.syke.fi/en-US/Research__Development/Ecosystem_services/Specialist_work/Zonation_in_Finland/Zonation_materials/Posters eller http://www.syke.fi/download/noname/%7B771FF5A4-DAB6-45EE-8246-F38FC0090CAD%7D/138289 Detailjerad rapport på finska: 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. Andra källor: 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. Användar lisens: Creative Commons 4.0. © SYKE Datasources: Finnish Forest Centre, Metsähallitus, Natural Resources Institute Finland, National Land Survey of Finland, Hansen/UMD/Google/USGS/NASA

  • The marine habitat type data concerns the modelling work carried out within the Finnish Inventory Programme for the Underwater Marine Environment (VELMU) in spring 2015. The task was done in cooperation between the Geological Survey of Finland (GTK) and Åbo Academi University (ÅA). The work included the modelling of the marine habitats included in the Annex 1 of the Habitats Directive: reefs (1170) and sandbanks, which are slightly covered by sea water all the time (1110). The aforementioned marine habitat types are specified on the basis of seabed substrate type and topographic form and they can overlap one another. The objective was to produce comprehensive maps of the occurrences of reefs and sandbanks throughout the entire marine area of Finland based on the best data available. The criteria to determine the marine habitats were discussed with the responsible bodies and the instructions (version 5.1), which include more precise criteria for determining marine habitat types than the Natura 2000 Habitats Manual (Airaksinen & Karttunen 2001), for a Natura 2000 inventory were utilised. On the basis of different criteria and test analyses, a decision was made to model the following entireties: - Potential rocky reefs - detail-scale sites that are likely to have reef occurrences. - Potential rocky reef environments - larger sites that are likely to have reef occurrences. - Potential sandbanks - detail-scale sites that are likely to have sandbank occurrences. - Potential sandbank environments - larger sites that are likely to have sandbank occurrences. The data concerning the marine habitats of restricted areas has been removed.

  • 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. https://doi.org/10.14214/sf.9902 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. https://doi.org/10.14214/sf.1022. Siitonen M, Härkönen K, Hirvelä H, Jämsä J, Kilpeläinen H, Salminen O et al. 1996. MELA Handbook. 622. 951-40-1543-6.

  • The Plain map series is a simple, plain and readable dataset product series in raster format that depicts the whole of Finland. The product is meant to be used as a background map whose character changes to a guide map in large scales. Impaired vision has been taken into account when designing the product. The key objects presented on the map are roads and railways, road names, buildings and constructions, administrative borders, waterways and other geographical names. The road network, public buildings and texts have been especially emphasised. The most usual limitations of colour vision have been taken into account in the use of colours. The product belongs to the open data of the National Land Survey of Finland. More information: Topographic data and how to acquire it http://www.maanmittauslaitos.fi/en/maps-and-spatial-data/expert-users/topographic-data-and-how-acquire-it.

  • The technical harvesting potential of small-diameter trees can be defined as the maximum potential procurement volume of small-diameter trees available from the Finnish forests based on the prevailing guidelines for harvesting of energy wood. The potentials of small-diameter trees from early thinnings have been calculated for fifteen NUTS3-based Finnish regions covering the whole country (Koljonen et al. 2017). To begin with the estimation of the region-level potentials, technical harvesting potentials were estimated using the sample plots of the eleventh national forest inventory (NFI11) measured in the years 2009–2013. 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; Redsven et al. 2013). 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). Simulated management actions for the small-tree fraction consisted of thinnings that fulfilled the following stand criteria: • mean diameter at breast height ≥ 8 cm • number of stems ≥ 1500 ha-1 • mean height < 10.5 m (in Lapland) or mean height < 12.5 m (elsewhere). Energy wood was harvested as delimbed (i.e. including the stem only) in spruce-dominated stands and peatlands and as whole trees (i.e. including stem and branches) elsewhere. When harvested as whole trees, a total of 30% of the original crown biomass was left onsite (Koistinen et al. 2016). Energy wood thinnings could be integrated with roundwood logging or carried out independently. Second, the technical energy wood potential of small trees was operationalized in MELA by maximizing the removal of thinnings in the first period. In this way, it was possible to pick out all small tree fellings simulated in the first period despite, for example, the profitability of the operation. However, a single logging event was rejected if the energy wood removal was lower than 25 m³ha-1 or the industrial roundwood removal of pine, spruce, or birch exceeded 45 m³ha-1. The potential calculated in this way contained also timber suitable for industrial roundwood. Therefore, two estimates are given: • potential of trees below 10.5 cm in breast-height diameter • potential of trees below 14.5 cm in breast-height diameter. Subsequently, the region-level potentials were spread on a raster grid at 1 km × 1 km resolution. Only grid cells on Forests Available for Wood Supply (FAWS) were considered in this operation. In this study, FAWS was defined as follows: First, forest land was extracted from the Finnish Multi-Source National Forest Inventory (MS-NFI) 2013 data (Mäkisara et al. 2016). Second, restricted areas were excluded from forest land. The restricted areas consisted of nationally protected areas (e.g. nature parks, national parks, protection programme areas) and areas protected by the State Forest Enterprise. In addition, some areas in northernmost Lapland restricted by separate agreements between the State Forest Enterprise and stakeholders were left out from the final data. Furthermore, for small trees, FAWS was further constrained by the stand criteria presented above to represent similar stand conditions for small-tree harvesting as in MELA. Finally, the region-level potentials were distributed to the grid cells by weighting with MS-NFI stem wood biomasses. References Äijälä O, Koistinen A, Sved J, Vanhatalo K, Väisänen P (2014) Metsänhoidon suositukset [Guidelines for sustainable forest management]. Metsätalouden kehittämiskeskus Tapion julkaisuja. 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]. Metsäkustannus Oy, Helsinki. Koljonen T, Soimakallio S, Asikainen A, Lanki T, Anttila P, Hildén M, Honkatukia J, Karvosenoja N, Lehtilä A, Lehtonen H, Lindroos TJ, Regina K, Salminen O, Savolahti M, Siljander R (2017) Energia ja ilmastostrategian vaikutusarviot: Yhteenvetoraportti. [Impact assessments of the Energy and Climate strategy: The summary report.] Publications of the Government´s analysis, assessment and research activities 21/2017. Mäkisara K, Katila M, Peräsaari J, Tomppo E (2016) The Multi-Source National Forest Inventory of Finland – methods and results 2013. Natural resources and bioeconomy studies 10/2016. Redsven V, Hirvelä H, Härkönen K, Salminen O, Siitonen M (2013) MELA2012 Reference Manual. Finnish Forest Research Institute. Siitonen M, Härkönen K, Hirvelä H, Jämsä J, Kilpeläinen H, Salminen O, Teuri M (1996) MELA Handbook. Metsäntutkimuslaitoksen tiedonantoja 622. ISBN 951-40-1543-6.

  • FTA INSPIRE Download Service (WFS) for Transport Networks is an INSPIRE compliant direct access Web Feature Service. It contains the following INSPIRE feature types: Road network, Rail network, Waterway network and Air transport network. The service is based on the FTA INSPIRE Transport Networks Theme Dataset. The dataset is administrated by the Finnish Transport Agency. The service is still under development and as such accessibility and full operationality or conformity with Inspire spesifications is not guaranteed.

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    The Bio-geographical regions are internally homogeneous biogeographical regions of Finland. The number of regions is 21. The regions were spatially defined by an expert committee in 1930 as collections of municipalities. Consequently, the province boundaries follow the delineation of of municipalities in the 1930's including some enclaves, exclaves, and narrow stripes as the province boundaries have not been changed or updated since then excluding the cession of territory after the Second World War. In the "Extended" data set regions have names and abbreviations in Finnish, Swedish, and Latin. No other attribute data is available.

  • FTA INSPIRE View Service (WMS) for Transport Networks is an INSPIRE compliant . It contains the following INSPIRE feature types: Road network, Rail network, Waterway network and Air transport network. The service is based on the FTA INSPIRE Transport Networks Theme Dataset. The dataset is administrated by the Finnish Transport Agency. The service is still under development and as such accessibility and full operationality or conformity with Inspire spesifications is not guaranteed.

  • NLS-FI INSPIRE Download Service (WFS) for Buildings/Point is an INSPIRE compliant direct access Web Feature Service. It contains the following INSPIRE feature types: Building The service is based on the NLS-FI INSPIRE Buildings Theme Dataset. The dataset is administrated by the National Land Survey of Finland. The service contains all features from the dataset that are modelled as points.