Paikkatietohakemisto
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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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The data compiles seabed remote sensing situation since the 1960s. The data includes spatial data and metadata related to each survey line, mainly based on the data produced by the Geological Survey of Finland
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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
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The map compiles seabed samples since 1985 onwards. The data includes geographic data and metadata related to each sample, mainly based on the data produced by the Geological Survey of Finland
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The database consists of three components: "Published age determination”, ”Published Sm-Nd isotope data" and "Pb isotope data on galena". The "Published age determination" database is based on age determinations, which comprise predominantly U-Pb zircon data produced at the Geological Survey of Finland since 1960’s. For igneous rocks the age register contains radiometric ages mostly interpreted as primary ages. The information given consists of location data, rock type, method, mineral analyzed, age results, comments and references. "Published Sm-Nd isotope data" comprise Sm-Nd data procuded at GTK since 1981, which mostly are used to constrain the origin of crust. "Pb isotope data on galena" gives results produced at GTK since 1970's, and include also previously unpublished data.
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FIN Järvien vesikasvillisuusvyöhykettä kuvaava aineisto 1971 suomalaisesta järvivesimuodostumasta. Aineisto on polygonivektorimuodossa, jossa yksittäisen järven vesikasvivyöhyke esitetään moniosaisena polygonina. Vesikasvillisuusvyöhyke koostuu ilmakuvilta erottuvasta vedenpinnan yläpuolisesta (ilmaversoinen ja kelluslehtinen) ja aivan vedenpinnan tasolle yltävästä uposlehtisestä kasvillisuudesta. Vesikasvillisuusvyöhykkeen ja järven 0–3 metrin syvyysvyöhykkeen perusteella järville on laskettu kasvittumisaste-niminen tunnusluku, jota käytetään järvien ekologisen tilan arvioinnissa kuvaamaan rehevöitymisen aiheuttamaa kasvillisuuden runsastumista. Vesikasvillisuusvyöhyke on analysoitu Picterra-yrityksen koneoppimismalleilla Maanmittauslaitoksen hallinnoimista väri-infra- eli vääräväriortokuvista vuosilta 2012-2023. Vyöhykkeen analysointi on rajattu 1.7.–10.9. otettuihin ortokuviin. Lisäksi analysointi on rajattu seuraaviin vesienhoidon suunnittelun 3. suunnittelukaudella määritettyihin järvityyppeihin: • Pienet humusjärvet • Keskikokoiset humusjärvet • Runsashumuksiset järvet • Matalat humusjärvet • Matalat runsashumuksiset järvet Aineisto sisältää 698 järvivesimuodostumalta ilmakuvatulkinnan useammalta vuodelta. Havaittu kasvittumisaste on laskettu niille 977 järvivesimuodostumalle, joilta oli saatavissa tieto 0–3 metrin syvyysvyöhykkeestä. Aineistoon on jätetty järviä ilman syvyysaineistoa ja siten kasvittumisasteen laskentaa siinä tarkoituksessa, jotta aineistoa voidaan tarvittaessa hyödyntää muuhunkin kuin kasvittumisaste-muuttujaan perustuvaan tila-arviointiin. Aineistolle on tehty silmämääräinen tarkastus virheellisten havaintojen poistamiseksi. Aineisto voi silti sisältää väärintulkintoja. Kasvittumisasteen luontaisen vaihtelun mallintamisesta saadut tunnusluvut, kuten odotetut kasvittumisasteet ja kasvittumisasteeseen perustuva ekologinen tilaluokka, ovat ympäristöhallinnon asiantuntijoiden katseltavissa Pisara-järjestelmässä. Käyttötarkoitus: Ympäristöhallinnon tehtävien tueksi vesien tilan arviointiin. Järvien ekologisen tilan arviointia tekevät asiantuntijat käyttävät paikkatietoaineistoa ilmakuvatulkinnan laadun arvioimiseen yksittäisellä järvellä. Asiasanat: kaukokartoitus, ilmakuvat, vesikasvillisuus, seuranta, ekologinen tila Lisätietoja: https://geoportal.ymparisto.fi/meta/julkinen/dokumentit/Jarvien_vesikasvillisuusvyohykkeet.pdf https://vesi.fi/aineistopankki/koneoppimispohjaiseen-ilmakuvatulkintaan-perustuva-jarvien-vesikasvillisuuden-tilanarviointi/ ENG This data describes lake macrophyte zone on 1971 Finnish lake waterbodies. The spatial features are represented as multi-part polygons. The attributes are in Finnish. The zone represents emergent and floating-leaved vegetation plus submerged vegetation just above the surface of water. Together with lake bathymetric data, the percentage of vegetated littoral (PVL) was calculated. The PVL is applied in ecological status assessment. Lake macrophyte zone was detected from color-infrared aerial orthophotos administered by the National Land Survey of Finland. The detections were performed with the help of a custom machine learning model trained using Picterra. The detections were applied to orthophotos in 2012-2013 which were filmed between 1st of July and 10th of September. The detections were limited to humic and humic-rich lake waterbodies. There are detections from multiple years for 698 lake waterbodies. Observed PVL were calculated on 977 lake waterbodies which have bathymetric data to identify the 0 to 3 meters deep littoral zone. To potentially utilize the data for more than just the PVL-based approach, the data also have detections on waterbodies without bathymetric data and therefore observed PVL. A visual inspection of the data has been performed to remove erroneous detections. The data may still contain misinterpretations. Purpose of use: Support of environmental administration in ecological status assessment. More information: https://geoportal.ymparisto.fi/meta/julkinen/dokumentit/Jarvien_vesikasvillisuusvyohykkeet.pdf https://vesi.fi/aineistopankki/koneoppimispohjaiseen-ilmakuvatulkintaan-perustuva-jarvien-vesikasvillisuuden-tilanarviointi/
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The Finnish Uniform Coordinate System (in Finnish Yhtenäiskoordinaatisto, YKJ) has been used in biological observation mapping since the 1970s. Based on YKJ, Finland is divided in square-shaped areas, the size of which are determined according to the needs of the study. The area division used in national biomonitoring is 10 km x 10 km squares, but in some cases 1 km x 1 km and 100 m x 100 m YKJ squares are also used. This data set includes XY-lines that form square grid in four scales according to Unified Coordinate System (100 m - 100 km), with identifiers describing each square.
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Elevation zones is a raster dataset that visualises elevation of the terrain. The product covers the whole of Finland. There are four product versions available in which the pixel sizes are 32, 64, 128 and 512 metres. The dataset does not contain elevation values; it is a colour image that visualises the height of the terrain above sea level as zones. The sea is shown in light blue in the elevation zone. The product Elevation zones is available as a version that covers the whole country and as versions that cover a certain area. The product belongs to the open data of the National Land Survey of Finland.
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Production and Industrial Facilities contain the data set on establishments based on Statistics Finland's Business Register as follows: Data: location coordinates of the establishment, industry according to the Standard Industrial Classification TOL 2008 at the 2-digit level Industries according to D2.8.III.8 INSPIRE in TOL 2008 industries: B Mining and quarrying C Manufacturing D Electricity, gas steam and air conditioning supply E Water supply, sewerage, waste management and remediation activities F Construction H Transport and storage (excl. 53 Postal and courier activities) Coverage of the data set: establishments with over ten employees Statistical reference year: 2019 The data set is also suitable for viewing the location of industrial establishments. The coverage of the spatial data is about 90 % of the statistical data. The general Terms of Use must be observed when using the data: http://tilastokeskus.fi/org/lainsaadanto/copyright_en.html. In addition to the national version, an INSPIRE information product is also available from the data.
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KUVAUS: Aineisto sisältää raitiotien katusuunnitelmien reitit Tampereen alueelta sekä linkkejä suunnitelmapiirustuksiin. KATTAVUUS: Kaikille käyttäjille Oskari-karttapalvelussa. PÄIVITYS: Aineistoa päivitetään tarpeen mukaan (ylläpito jatkuvaa). YLLÄPITOSOVELLUS: PostgreSQL-tietokanta ja QGIS-ohjelmisto. KOORDINAATTIJÄRJESTELMÄ: Aineisto tallennetaan ETRS-GK24FIN (EPSG:3878) tasokoordinaattijärjestelmässä. GEOMETRIA: vektori (viiva) SAATAVUUS: Aineisto on saatavilla WFS-rajapinnalta Tampereen kaupungin sisäiseen käyttöön. JULKISUUS: Kaikille käyttäjille Oskari-karttapalvelussa. AINEISTOSTA VASTAAVA TAHO: Tampereen kaupunki, Kuntatekniikan suunnittelu