2016 all ship types AIS shipping density

This dataset represents the density of all IMO registered ships operating in the Baltic Sea. Density is defined as the number of ships crossing a 1 x 1km grid cell. It is based on HELCOM AIS (Automatic Identification System) data. The HELCOM AIS network hosts all the AIS signals received by the Baltic Sea States since 2005. The AIS Explorer allows to compare density maps of different ship types per month: http://maps.helcom.fi/website/AISexplorer/ The data was processed to produce density maps and traffic statistics. All scripts are available in GitHub: https://github.com/helcomsecretariat. The production of these maps have been carried out 2016-2017 through the HELCOM project on the assessment of maritime activities in the Baltic Sea. The underlying AIS data processing work has been co-financed by EU projects Baltic Scope (2015-2017 EASME/EMFF/2014/1.2.1.5) and Baltic Lines (2016-2019, Interreg Baltic Sea Region). In addition, the Ministry of the Environment of Finland supported the work with a special contribution in view of the use of the results in the HOLAS II process.

Landscape feature on agricultural land 2021

Plain map series (raster)

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.

Integrated biodiversity status assessment - seals 2018

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))

Väylänvarsien vieraslajit ja arvokkaat elinympäristöt

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

Energywood potentials

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 1st thinnings, pine • Stemwood for energy from 1st thinnings, spruce • Stemwood for energy from 1st thinnings, broadleaved • Stemwood for energy from 1st thinnings (smaller than pulpwood-sized trees), pine • Stemwood for energy from 1st thinnings (smaller than pulpwood-sized trees), spruce • Stemwood for energy from 1st 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 sustainable removal Main output ☒Small-diameter trees ☒Stemwood for energy ☒Logging residues ☒Stumps ☐Bark ☐Pulpwood ☐Saw logs Additional information Stemwood for energy from 1st thinnings. Part of this potential consists of trees smaller than pulpwood size. This part is reported as Small-diameter trees. Forecast period for the biomass supply assessment Start year: 2015 End year: 2044 Results presented for period 2025-2034 3. Description of scenarios included in the assessments Maximum sustainable removal The maximum sustainable 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 80.7 mill. m3 (over bark) for period 2025-2034. 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 2013-2017. Stand based ☐Yes ☒No Grid based ☒Yes ☐No Multi-Source NFI data from 2015 (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 sustainable 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 sustainable 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 sustainable 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) Constraints for stump extraction ☒Yes ☐No ☐N/A Retention of 16–18% of stump biomass (Muinonen et al. 2013; Anttila et al. 2013) 8. External factors Valid for scenario: Maximum sustainable removal External factors besides forest management having effect on outcomes Economy ☐Yes ☒No Climate change ☐Yes ☒No Calamities ☐Yes ☒No Other external ☐Yes ☒No

Rakennukset alueina

KUVAUS: Tampereen rakennusten 2D-seinälinjat aluemuotoisena geometriana korkeudeltaan nollattuna. Rakennusten ominaisuustiedot tulevat masterdatasta i_pyraknron perusteella. Jos tunnusvastaavuutta ei löydy, geometria ei tule mukaan näkymään. Virkistys aamuisin klo 6.15. KATTAVUUS: Tampereen kaupunkiseutu PÄIVITYS: Aineistoa päivitetään jatkuvasti uusien rakennusten valmistuessa. YLLÄPITOSOVELLUS: StellaMap (DGN-tiedostot) ja FME KOORDINAATTIJÄRJESTELMÄ: Aineisto tallennetaan ETRS-GK24FIN (EPSG:3878) tasokoordinaattijärjestelmässä. GEOMETRIA: vektori (alue) SAATAVUUS: Aineisto on saatavilla WFS-rajapinnalta. Aineiston primäärilähde on Oracle-tietokanta. JULKISUUS: Aineisto on katsottavissa Oskari-karttapalvelussa. KENTÄT: -PYSYVA_RAKENNUSTUNNUS: Tulee rakennuksen i_pyraknro perusteella Factasta. -SIJAINTIKIINTEISTO: Rakennuksen kiinteistötunnus -VALMISTUMISPVM -KERROSALA: Kerrosalaan luetaan kerrosten pinta-alat ja se ullakon tai kellarikerrosten ala, jossa on asuin- tai työhuoneita tai muita rakennuksen pääasiallisen käyttötarkoituksen mukaisia tiloja. Kerrosala on vaakasuora pinta-ala, jota rajoittavat kerrosten seinien ulkopinnat tai niiden ajateltu jatke ulkoseinien pinnassa olevien aukkojen ja koristeosien osalta (Tilastokeskus 2024). -KERROSTEN_LKM -HISSI -RAKENNUSTILAVUUS -POLTTOAINE -LAMMITYSTAPA: Vesikeskuslämmitys, Ilmakeskuslämmitys, Suora sähkölämmitys, Uunilämmitys, Ei kiinteää lämmityslaitetta, tuntematon. -PYSYVA_RAK_NRO_FACTA: Rakennelman pysyvä rakennusnumero Factasta. AINEISTOSTA VASTAAVA TAHO: Tampereen kaupunki, Paikkatietoyksikkö, paikkatieto_tuki@tampere.fi

NLS-FI INSPIRE Administrative Units Theme Dataset

NLS-FI INSPIRE Administrative Units Theme Dataset is a dataset depicting Administrative Units covering the land area and Maritime Units covering the sea area of Finland. Administrative Units contain the following INSPIRE feature types: AdministrativeUnit, AdministrativeBoundary. Maritime Units contain the following INSPIRE feature types: Baseline, MaritimeZone, MaritimeBoundary. Administrative Units are updated once a year from the NLS Cadastral Index Map database. Maritime Units are quite stable and have no regular update cycle. The dataset is available via the NLS-FI INSPIRE Download Service (WFS) for Administrative Units Theme and it can be viewed via the NLS-FI INSPIRE View Service (WMS) for Administrative Units.

NLS-FI INSPIRE Download Service (WFS) for Cadastral Parcels

NLS-FI INSPIRE Download Service (WFS) for Cadastral Parcels Theme is an INSPIRE compliant direct access Web Feature Service. It contains the following INSPIRE feature types: BasicPropertyUnit, 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.

Geochemical atlas of Finland: stream sediment

The Regional Stream Sediment Geochemical Mapping data set gives information on the elemental concentrations in organic sediments of small headwater streams. The samples have been taken from small headwater streams (catchment area under 30 km2) in the late summer of 1990. Sampling has been repeated for about every fourth point during the years 1995, 2000 and 2006. The number of samples was 1162 in 1990 (at a density of one sample / 300 km2), 286 in 1995, 286 in 2000 and 249 in 2006. The data set covers the whole of Finland. Stream water samples have also been taken at the same time. Sampling, processing and analysis methods have been described in the Geochemical Atlas of Finland, Part 3, p. 27 - 30 (Lahermo et. al 1996). Field observations, coordinates and element concentrations determined from samples have been made into a database, in which each record represents one sample point. The data for each sampling year have been recorded on different tables. The method of analysis is referred to with a four-character method code. The codes are as follows: 503H = mercury determination using the cold vapour method 503P = nitric acid extraction in a microwave oven, measurement with ICP-AES 503M = nitric acid extraction in a microwave oven, measurement with ICP-MS 820L = carbon, hydrogen and nitrogen determination with a LECO analyser. The element concentration data include a numerical concentration value (as mg kg-1 or ppm) and possibly a check mark. The concentration is recorded as a variable, which has a name that comprises the chemical symbol for the element and the code for the method of analysis. For example AS_503M is arsenic (As) concentration, which is determined with the ICP-MS method (503M). The next variable has a check mark, for example AS_503MT. If the numerical value following the check mark is ‘>’ or '‘<’ then the number recorded in the concentration field is the determination limit of the chemical analytical method used and the actual concentration is less than this value. If the check mark is an exclamation mark (!), the analytical result is smaller than the determination limit of the analytical method use but the (unreliable) value obtained with the measuring instrument has been entered in the database. There is no data are if the check mark is a 'x'. The original purpose of the Regional Stream Water Geochemical Mapping data set was national general geochemical mapping and the basic assessment of environmental state. Other uses are, for example, the assessment of changes in environmental state and determination of the baseline concentrations of surface water as part of the evaluation of the chemical state of catchment areas in accordance with the Water Framework Directive of the EU. The original purpose of the Regional Stream Water Geochemical Mapping data set was national general geochemical mapping and the basic assessment of environmental state. Other uses are, for example, the assessment of changes in environmental state and determination of the baseline concentrations of surface water as part of the evaluation of the chemical state of catchment areas in accordance with the Water Framework Directive of the EU.