Paikkatietohakemisto
Type of resources
Available actions
Topics
Keywords
Contact for the resource
Provided by
Years
Formats
Representation types
Update frequencies
status
Service types
Scale
Resolution
-
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
-
Maanmittauslaitoksen KM2-korkeusmallin kanssa yhteensopiva korkeusmalli, jossa alkuperäisiä korkeusarvoja on alennettu erityisesti virtavesikohteiden (viivamaiset sekä aluemaiset) ja tieverkoston risteyskohdissa. Alennetut korkeusarvot pyrkivät kuvaamaan virtausreittejä, kuten tierumpuja ja putkia, joita alkuperäisessä KM2:ssa ei ole. Aineisto on tuotettu yhdistämällä useita eri valtakunnan kattavia lähtöaineistoja, joita ovat - korkeusmalli KM2 (Maanmittauslaitos) - Siltojen kansien korkeudet (Syke) - Maastotietokanta (Maanmittauslaitos) - DIGIROAD-tieverkosto (Väylävirasto) - Rumpurekisteri (Väylävirasto) Lisäksi jotkin kunnat ja kaupungit ovat digitoineet Maastotietokannasta puuttuvia virtausreittejä. Korkeusarvot ovat ilmoitettu N2000-korkeusjärjestelmässä. Aineisto on avoin (lisenssi CC BY 4.0). Käyttötarkoitus: Korvaamalla KM2:n korkeusarvot uomakorjausaineiston arvoilla saadaan korkeusmalli, joka soveltuu mm. pintaveden virtauksen mallinnukseen alkuperäistä korkeusmallia paremmin. Tämä mahdollistaa esim. hulevesitulvariskien luotettavamman arvioinnin. Aineisto kuuluu SYKEn avoimiin aineistoihin (CC BY 4.0). Lähde: Syke, Maanmittauslaitos (perustuu Syken, MML:n ja Väyläviraston aineistoihin).
-
The data set consists of yearly maps of the start of the vegetation active period in deciduous vegetation and coniferous forest. The start of vegetation active period in deciduous vegetation (Day of Year) is defined as the day when deciduous trees unfold new leaves in spring. It is also often referred to as the green-up or greening day. The data set was derived from time series of the Normalized Difference Water Index (NDWI) calculated from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations. The start of vegetation active period in coniferous forest (Day of Year) is defined as the day when coniferous trees start to photosynthesize in spring. The data set was derived from MODIS satellite observation of Fractional Snow Cover. The day when snow cover decreases during spring melt was used as a proxy indicator for the beginning of the start of the vegetation active period. The data set can be used of phenology analysis at regional and national scale and as input data for modelling. This SYKE’s dataset can be used according to open data license (CC BY 4.0)
-
The Regional Stream Water 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.
-
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
-
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
-
LUOMUS WFS is an API to the geospatial information provided by the Finnish Museum of Natural History. The use of the service is free and doesn't require authentication.
-
This dataset contains the ship accidents in the Baltic Sea during the period 1989 to end of 2023. It is constructed from the annual data collected by HELCOM Contracting Parties on ship accidents in the Baltic Sea and starting from 2019 from EMSA EMCIP Database extraction (for those Contracting Parties that are member of the EU). The accident data has been compiled by the HELCOM Secretariat and EMSA. According to the decision of the HELCOM SEA 2/2001 shipping accident data compilation will include only so-called conventional ships according to the Regulation 5, Annex I of MARPOL 73/78 - any oil tanker of 150 GT and above and any other ships of 400 GT and above which are engaged in voyages to ports or offshore terminals under the jurisdiction of other Parties to the Convention. According to the agreed procedure all accidents (including but not limited to grounding, collision with other vessel or contact with fixed structures (offshore installations, wrecks, etc.), disabled vessel (e.g. machinery and/or structure failure), fire, explosions, etc.), which took place in territorial seas or EEZ of the Contracting Party irrespectively if there was pollution or not, are reported. The dataset contains the following information: Unique_ID = An unique identifier consisting of 4 digit running number and the year of the accident Country Year Date = Date (dd/mm/yyyy) Time = Time of the accident (hh:mm) Location = Location of the accident (open sea / port / port approach, from 2019 -> open sea / port) Acc_Type = Type of accident Colli_Type = Type of collision / contact (with vessel / object) Acc_Detail = More information on the accident CauseDetai = Details on the accident cause Assistance = Assistance after the accident Offence = Offence against Rule Damage = Damage to the ship HumanEleme = Occurrence / Reason of human error IceCondit = Ice conditions CrewIceTra = Crew trained for ice conditions Pollution = Pollution (Yes/No) Pollu_m3 = Pollution in m3 Pollu_t = Pollution in tonnes Pollu_Type = Type of pollution RespAction = Response actions after the accident Cargo_Type = Type of cargo Ship1_Name = Ship 1 identification (Not published after 2018) Sh1_Categ = Ship 1 type (according to AIS category) Sh1_Type = Ship 1 more detail ship type category Sh1_Hull = Ship 1 hull construction Sh1Size_gt = Ship 1 GT Sh1Sizedwt = Ship 1 DWT Sh1Draug_m = Ship 1 draught in meters / category Cause_Sh1 = Cause of accidents from ship 1 Pilot_Sh1 = Presence of pilot on ship 1 Ship2_Name = Ship 2 identification (Not published after 2018) Sh2_Categ = Ship 2 type (according to AIS category) Sh2_Type = Ship 2 more detail ship type category Sh2_Hull = Ship 2 hull construction Sh2Size_gt = Ship 2 GT Sh2Sizedwt = Ship 2 DWT Sh2Draug_m = Ship 2 draught in meters / category Cause_Sh2 = Cause of accidents from ship 2 Pilot_Sh2 = Presence of pilot on ship 2 Add_Info = Additional information Latitude = Latitude (decimal degrees) Longitude = Longitude (decimal degrees) For more information about shipping accidents in the Baltic Sea, see the HELCOM annual reports: https://helcom.fi/helcom-at-work/publications/ https://helcom.fi/media/publications/HELCOM-report-on-Shipping-accidents-in-the-Baltic-Sea-2019-211207-FINAL.pdf
-
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 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.