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From 1 - 10 / 2013
  • NLS-FI INSPIRE View Service for Hydrography Theme is an INSPIRE compliant Web Map Service. It contains the following harmonized INSPIRE map layers: Land-water Boundary, Waterbodies, Man-made Objects, Hydro Point of Interest. The service is based on the NLS-FI INSPIRE Hydrography Physical Waters dataset. The dataset is administrated by the National Land Survey of Finland.

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    FTIA INSPIRE Transport Networks Theme Dataset is a dataset depicting the Transport Networks covering the whole of Finland. It contains the following INSPIRE feature types: Road network, Rail network, Waterway network and Air transport network. The dataset is available via the FTIA INSPIRE Download Service (WFS) for Transport Networks and it can be viewed via the FTIA INSPIRE View Service (WMS) for Transport Networks.

  • FIN Aineiston tarkoituksena on: -Identifioida tie- ja rata-alueet, joiden varrella esiintyy uhanalaisia ja silmälläpidettäviä lajeja -Identifioida tie- ja rata-alueet, joiden varrella esiintyy hyviä elinvoimaisia niittyindikaattorilajeja (hyönteisten mesi- ja ravintokasveja) -Identifioida tie- ja rata-alueet, joiden varrella esiintyy suojelualueita -Identifioida tie- ja rata-alueet, joiden varrella esiintyy komealupiinia tai kurtturuusua -Identifioida tie- ja rata-alueet, joiden varrella esiintyy komealupiinia tai kurtturuusua uhanalaisten lajien lisäksi -> Löytää herkät alueet ja paikallistaa vieraslajien uhka Tieto esitetään 1 kilometrin ruuduissa. Aineistosta on julkaistu kaksi erillistä versiota. -VaylanvarsienVieraslajitJaArvokkaatElinymparistot_avoin: Avoin versio, jonka lajitietoa on karkeistettu mahdollisista herkistä lajeista johtuen. Aineisto kuuluu SYKEn avoimiin aineistoihin (CC BY 4.0) ja sitä saa käyttää lisenssiehtojen mukaisesti -VaylanvarsienVieraslajitJaArvokkaatElinymparistot_kayttorajoitettu: Alkuperäinen karkeistamaton versio. Tämä versio on vain viranomaiskäyttöön eikä kyseistä aineistoa saa jakaa Aineistosta on tehty tarkempi menetelmäkuvaus https://geoportal.ymparisto.fi/meta/julkinen/dokumentit/VierasVayla_Menetelmakuvaus.pdf sekä muuttujaseloste https://geoportal.ymparisto.fi/meta/julkinen/dokumentit/VierasVayla_VariableDescription.xlsx ENG The purpose of the material is to: -Identify road and rail areas that have nearby observations of endangered and near threatened species -Identify road and rail areas with good meadow indicator plant species -Identify road and rail areas along which there are protected areas -Identify the road and rail areas along which there are observations of Lupinus polyphyllus or Rosa rugosa observations -Identify the road and rail areas along which there are Lupinus polyphyllus or Rosa rugosa observations in addition to sensitive species -> Finds sensitive areas and identify the overall threat of alien species The data is presented in 1-kilometer square grid cells. There are two separate versions of the data. -VaylanvarsienVieraslajitJaArvokkaatElinymparistot_avoin: Open access version, in which its species-related parts have been simplified due to data restriction issues. The material belongs to Syke's open materials (CC BY 4.0) and may be used in accordance with the license terms. -VaylanvarsienVieraslajitJaArvokkaatElinymparistot_kayttorajoitettu: Original version. This version is only for official use and the material in question may not be shared. A more precise description about the data procedures can be found from (In Finnish) https://geoportal.ymparisto.fi/meta/julkinen/dokumentit/VierasVayla_Menetelmakuvaus.pdf Furthermore, all the variables in the data are explained in this bilingual variable description https://geoportal.ymparisto.fi/meta/julkinen/dokumentit/VierasVayla_VariableDescription.xlsx This dataset was updated with the newest species observations on 10/2023 and 11/2024 Process code for this can be found from https://github.com/PossibleSolutions/VierasVayla_SpeciesUpdate

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    This assessment was part of project Baltic ForBio funded by the Interreg Baltic Sea Region Programme (https://www.slu.se/en/departments/forest-economics/forskning/research-projects/baltic-forbio/). The project was carried out in 2017-2020. The harvesting potentials in Finland were calculated for the following assortments: • Stemwood for energy from thinnings, pine • Stemwood for energy from thinnings, spruce • Stemwood for energy from thinnings, broadleaved • Stemwood for energy from thinnings (smaller than pulpwood-sized trees), pine • Stemwood for energy from thinnings (smaller than pulpwood-sized trees), spruce • Stemwood for energy from thinnings (smaller than pulpwood-sized trees), broadleaved • Logging residues, pine • Logging residues, spruce • Logging residues, deciduos • Stumps, pine • Stumps, spruce. 1.1 Decision support system used in assessment Regional energywood potentials were calculated with MELA forest planning tool (Siitonen et al. 1996; Hirvelä et al. 2017). 1.2 References and further reading Anttila P., Muinonen E., Laitila J. 2013. Nostoalueen kannoista jää viidennes maahan. [One fifth of the stumps on a stump harvesting area stays in the ground]. BioEnergia 3: 10–11. Anttila P., Nivala V., Salminen O., Hurskainen M., Kärki J., Lindroos T.J. & Asikainen A. 2018. Re-gional balance of forest chip supply and demand in Finland in 2030. Silva Fennica vol. 52 no. 2 article id 9902. 20 p. https://doi.org/10.14214/sf.9902 Hakkila, P. 1978. Pienpuun korjuu polttoaineeksi. Summary: Harvesting small-sized wood for fuel. Folia Forestalia 342. 38 p. 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., Siipilehto, J., Salminen, H. & Haapala, P. 2002. Models for predicting stand development in MELA System. Metsäntutkimuslaitoksen tiedonantoja 835. 116 p. Koistinen A., Luiro J., Vanhatalo K. 2016. Metsänhoidon suositukset energiapuun korjuuseen, työopas. [Guidelines for sustainable harvesting of energy wood]. Metsäkustannus Oy, Helsinki. ISBN 978-952-5632-35-4. 74 p. Mäkisara, K., Katila, M., Peräsaari, J. 2019: The Multi-Source National Forest Inventory of Finland - methods and results 2015. 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. Natural Resources Institute Finland. 2019. Industrial roundwood removals by region. Available at: http://stat.luke.fi/en/industrial-roundwood-removals-by-region. Accessed 22 Nov 2019. Ruotsalainen, M. 2007. Hyvän metsänhoidon suositukset turvemaille. Metsätalouden kehittämiskeskus Tapio julkaisusarja 26. Metsäkustannus Oy, Helsinki. 51 p. ISBN 978-952-5694-16-1, ISSN 1239-6117. Siitonen M, Härkönen K, Hirvelä H, Jämsä J, Kilpeläinen H, Salminen O et al. 1996. MELA Handbook. 622. 951-40-1543-6. Äijälä, O., Kuusinen, M. & Koistinen, A. (eds.). 2010. Hyvän metsänhoidon suositukset: energiapuun korjuu ja kasvatus. Metsätalouden kehittämiskeskus Tapion julkaisusarja 30. 56 p. ISBN 978-952-5694-59-8, ISSN 1239-6117. Äijälä, O., Koistinen, A., Sved, J., Vanhatalo, K. & Väisänen, P. (eds). 2014. Metsänhoidon suositukset. Metsätalouden kehittämiskeskus Tapion julkaisuja. 180 p. ISBN 978-952-6612-32-4. 2. Output considered in assessment Valid for scenario: Maximum sustained removal Main output ☒Small-diameter trees ☒Stemwood for energy ☒Logging residues ☒Stumps ☐Bark ☐Pulpwood ☐Saw logs Additional information Stemwood for energy from thinnings. Part of this potential consists of trees smaller than pulpwood size. This part is reported as Stemwood for energy from thinnings (smaller than pulpwood-sized trees). Forecast period for the biomass supply assessment Start year: 2016 End year: 2045 Results presented for period 2026-2035 3. Description of scenarios included in the assessments Maximum sustained removal The maximum sustained removal is defined by maximizing the net present value with 4% discount rate subject to non-declining periodic total roundwood removals, energy wood removals and net incomes, further the saw log removals have to remain at least at the level of the first period. There are no sustainability constraints concerning tree species, cutting methods, age classes or the growth/drain -ratio in order to efficiently utilize the dynamics of forest structure. Energy wood removal can consist of stems, cutting residues, stumps and roots. According to the scenario the total annual harvesting potential of industrial roundwood is 79 mill. m3 (over bark) for period 2026-2035. In 2018 removals of industrial roundwood in Finland totaled 68.9 mill. m3 (Natural Resources… 2019). 4. Forest data characteristics Level of detail on forest description ☒High ☐Medium ☐Low NFI data with many and detailed variables down to tree parts. Sample plot based ☒Yes ☐No NFI sample plot data from 2014-2018. Stand based ☐Yes ☒No Grid based ☒Yes ☐No Multi-Source NFI data from 2017 (Mäkisara et al. 2019) utilized when distributing regional potentials to 1 km2 resolution. 5. Forest available for wood supply: Total forest area defined as in: FAO. 2012. FRA 2015, Terms and Definitions. Forest Resources Assessment Working Paper 180. 36 p. Available at: http://www.fao.org/3/ap862e/ap862e00.pdf. Forest and scrub land 22 812 000 ha Forest land 20 278 000 ha and scrub land 2 534 000 ha Forest area not available for wood supply Forest and scrub land 2 979 000 ha Forest land 1 849 000 ha and scrub land 1 130 000 ha Partly available for wood supply Forest and scrub land 2 553 000 ha (includes in FAWS, below) Forest land 1 149 000 ha and scrub land 1 404 000 ha. Forest Available for wood supply (FAWS) Forest and scrub land 19 833 000 ha Forest land 18 429 000 ha and scrub land 1 404 000 ha In MELA calculations all the scrub land belonging to the FAWS belongs to the category “Partly available for wood supply”, but there are no logging events on scrub land regardless or the category. 6. Temporal allocation of fellings Valid for scenario: Maximum sustained removal Allocation method ☐Optimization based without even flow constraints ☒Optimization based with even flow constraints ☐Rule based with no harvest target ☐Rule based with static harvest target ☐Rule based with dynamic harvest target See item 3 above (max NPV with 4 % discount rate). 7. Forest management Valid for scenario: Maximum sustained removal Representation of forest management ☐Rule based ☒Optimization ☐Implicit Treatments, among of the optimization makes the selections, are based on management guidelines (e.g. Äijälä etc 2014) 7.2 General assumptions on forest management Valid for scenario: Maximum sustained removal ☒Complies with current legal requirements ☐Complies with certification ☒Represents current practices ☐None of the above ☐ No information available Forest management follows science-based guidelines of sustainable forest management (Ruotsalainen 2007, Äijälä et al. 2010, Äijälä et al. 2014). 7.3 Detailed assumptions on natural processes and forest management Valid for scenario: Maximum sustainable removal Natural processes ☒Tree growth ☒Tree decay ☒Tree death ☐Other? Tree-level models (e.g. Hynynen et al., 2002). Silvicultural system ☒Even-aged ☐Uneven-aged Click here to enter text. Regeneration method ☒Artificial ☒Natural Regeneration species ☐Current distribution ☒Changed distribution Optimal distribution may differ from the current one. Genetically improved plant material ☐Yes ☒No Cleaning ☒Yes ☐No Thinning ☒Yes ☐No Fertilization ☐Yes ☒No 7.4 Detailed constraints on biomass supply Volume or area left on site at final felling ☒Yes ☐No 5 m3/ha retained trees are left in final fellings. Final fellings can be carried out only on FAWS with no restrictions for wood supply. Constraints for residues extraction ☒Yes ☐No ☐N/A Retention of 30% of logging residues onsite (Koistinen et al. 2016). Dry-matter loss 20% for logging residues, 5% for stemwood. Constraints for stump extraction ☒Yes ☐No ☐N/A Retention of 16–18% of stump biomass (Muinonen et al. 2013; Anttila et al. 2013) Dry-matter loss 5%. 8. External factors Valid for scenario: Maximum sustained removal External factors besides forest management having effect on outcomes Economy ☐Yes ☒No Climate change ☐Yes ☒No Calamities ☐Yes ☒No Other external ☐Yes ☒No

  • The Regional Till Geochemical Mapping data set gives information on the concentrations of 37 elements in unaltered basal till. The samples have been taken, in 1983, from an unaltered basal till (C horizon) below the groundwater table at a depth of ca. 70 cm (variation 50-200 cm) with a density of one sample per 300 km2. The data set covers the whole of Finland with a total sample amount of 1056. The samples are composite field samples. The calculated sample point coordinates entered in the data set have been obtained from the centroid coordinates of five subsamples. The subsamples have been collected from a 300 m x 1000 m rectangular-shaped area. In Northern Finland, samples have been obtained by including samples taken previously in the Nordkallot Project. The samples have been sieved for analysis at a grain size grade less than 0.06 mm. The samples have been analysed for total elemental concentrations and aqua regia concentrations. Total concentrations have been determined either by neutron activation analysis (method code 900N) or by total dissolution with strong concentrated mineral acids (method code 312P). The analysis code for aqua regia dissolution is 511P. Gold and palladium have been determined with a analysis method based on flameless atomic absorption (519U). The sulfur concentration has been determined with a LECO analyser (810L). Further, total concentrations (312P) and aqua regia soluble concentrations (511P) were determined from Southern Finland and Mid-Finland samples with a grain size grade less than two millimetres. The original purpose of the Regional Till Geochemical Mapping data set was national geochemical general mapping and ore exploration. Other uses are, for example, estimating the baseline concentration of the soil, the nutrient levels of forest soil, assessing the buffering capacity of base cations in the soil and evaluating the weathering rate.

  • 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 1:15 000 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/).

  • 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 (http://www.emodnet-geology.eu/) 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 (http://www.emodnet-geology.eu/). Permission (AK15246) to publish the material was obtained from the Finnish Defence Office 28.07.2014

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    Elevation model 10 m depicts the elevation of the ground surface of the whole of Finland in relation to sea level. Its grid size is 10 m x 10 m and the accuracy of elevation data 1.4 metres. The product belongs to the open data of 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.