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Maatalousmaa vuonna 2021 aineisto kuvaa mahdollisimman kattavasti maankäytöltään maatalouteen kuuluvia alueita vuonna 2021, sisältäen sekä maataloustukia saavat alueet, että tukien ulkopuoliset alueet. Aineisto on koostettu käyttäen Ruokaviraston tuottamia perus- ja kasvulohkoaineistoja sekä Maanmittauslaitoksen tuottamaa maastotietokantaa. Peruslohkoaineisto on komission asetuksen 796/2004 ja neuvoston asetuksen (EY) N:o 1782/2003 20 artiklassa tarkoitettu viljelylohkojen tunnistusjärjestelmä. Järjestelmää käytetään EU:n pinta-alaperusteisen maataloustuen hallinnoinnissa. Aineisto käsittää vuoden 2021 peruslohkojen tilanteen 31.12.2021. Kasvulohkolla tarkoitetaan yhteen peruslohkoon kuuluvaa yhtenäistä aluetta, jossa kasvatat yhtä kasvilajia, useamman kasvilajin seosta tai jota kesannoidaan tai joka on erityiskäytössä. Yhdellä peruslohkolla voi olla yksi tai useampia kasvulohkoja. Kasvulohko voi kuulua vain yhteen peruslohkoon. Kasvulohkojen rajat ja samalla niiden pinta-alat voivat vaihdella peruslohkon sisällä vuosittain. Peltolohkorekisteristä on aineistoon otettu mukaan ne lohkot joihin yhdistyy kasvulohkoista tieto viljellystä kasvista. Aineistosta on tiputettu pois ei-maatalousaluetta olevat lohkot, esimerkiksi metsäiset alueet. Maanmittauslaitoksen Maastotietokanta on koko Suomen kattava maastoa kuvaava aineisto ja se koostuu erilaisista kohderyhmistä. Maastotietokannan Maatalousmaa -aineisto sisältää Maastotietokannan pellot, ja puutarhat. Niityt ovat erillinen kohdeluokka. Mammuttiprojektia varten MTK kohdeluokat Maatalousmaa (pellot ja puutarhat) ja Niitty yhdistettiin yhdeksi aineistoksi. Kohdeluokat on poimittu vuoden 2021 Maastotietokannasta. Kohdeluokat ja niiden kuvaukset löytyvät: https://www.maanmittauslaitos.fi/sites/maanmittauslaitos.fi/files/attachments/2018/03/Maastotietokohteet_0.pdf Peruslohkoaineistosta ja maastotietokannasta poimitut kohteet on yhdistetty siten, että maatalousmaa muodostetaan ensisijaisesti käyttämällä peruslohkoaineistosta poimittuja peruslohkoja. Tämän joukon ulkopuolelle jäävä maatalousmaa tulee maastotietokannasta. Aineistojen yhdistäminen on kuvattu tarkemmin tuotantokuvauksessa. https://geoportal.ymparisto.fi/meta/julkinen/dokumentit/maatalousmaa2021.pdf https://geoportal.ymparisto.fi/meta/julkinen/dokumentit/Metatietokuvaus_peltolohkorekisteri.pdf Aineisto kuuluu SYKEn avoimiin aineistoihin (CC BY 4.0).
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Tämän aineiston tarkemmat metodikuvaukset löytyvät artikkeleista (Holmberg et al. 2023, Junttila et al. 2023). Tässä on kuvattu aineistoa ja sen valmistelua. Tarkoituksena on ollut tuottaa alueellista tietoa maanpeitteen merkityksestä kasvihuonekaasupäästöihin Suomessa. Lähtöaineisto ja metodit rajoittavat tarkkuutta, mutta aineisto soveltuu paikallisten, esimerkiksi maakuntatason ilmiöiden tarkasteluun. Aineisto edustaa lyhyttä ajanjaksoa. Maanpeiteaineisto perustuu rekisteritietoihin ja kaukokartoitusaineistoon vuosilta 2015-2020, lukuun ottamatta maaperäaineistoa, jokia ja järviä. Aineisto on rasterimuotoista ja tallennettu GeoTiff-formaatissa, joka on yhteensopiva useimpien paikkatieto-ohjelmistojen kanssa. Greenhouse gas net emission intensities by land cover category in Finland The methods related to the data published herein are described in detail in the associated publications (Holmberg et al. 2023, Junttila et al. 2023). This file describes the datasets and the data preparation steps. The aim of this data publication is to provide regional assessments of the role of land cover in greenhouse gas emissions in Finland. The results in the publications are reported for the large administrative divisions, the NUTS 3 regions of mainland Finland (Statistics Finland 2023a). While limited by the accuracy of the methods and source data involved, these data can also be used for more local assessments, e.g., at the scale of municipalities. The data represent a temporal snapshot of land cover. Except for the soil maps, rivers and lakes, all land cover data are from the period 2015-2020 and are based on registry data or remote sensing. Data format. The data are distributed as GeoTiff raster files, which can be read using most GIS-software.
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The data on acid sulfate soils in 1:250 000 scale contains material generated since 2009 on the existence and properties of sulfate soils on the Finnish coastal areas and their drainage basins roughly up to the highest shoreline of the ancient Litorina Sea. The data contains the following levels: - Acid sulfate soils, 1:250 000 maps o Probability of the existence of acid sulfate soils o Probability of the existence of coarse-grained acid sulfate soils - Acid sulfate soils, profile points on 1:250 000 maps - Acid sulfate soils, survey points on 1:250 000 maps - Acid sulfate soils, profile point fact sheets on 1:250 000 maps The data gives a general outlook on the properties and occurrence of acid sulfate soils. The regional existence of sulfate soils is presented as a regional map plane using a four-tiered probability classification: high, moderate, low and very low. These classifications are complemented with regional planar data on whether the acid sulfate soil is coarse-grained, since its properties are significantly different from typical fine-grained sulfate soils. The drilling point (profile points and survey points) observations and analysis data are presented as point-like data on the map and as profile point fact sheets linked to points The survey data can be utilised, for example, in the planning and execution of land use and water management as required by environmental protection and land use. The survey scale is 1:20 000 – 1:50 000. The observation point density is 1–2 / 2 km² on average, and the minimum area of the region-like pattern is usually 6 hectares. The surveys collected data on the lithostratigraphy, existence of sulfide and the depth where found, and the soil pH values. The survey depth is three metres. The laboratory analyses included the determination of elements with the ICP-OES method and pH incubation. The data is published in GTK’s Acid Sulfate Soils map service.
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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).
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The Finnish Forest Research Institute (Metla) developed a method called multi-source national forest inventory (MS-NFI). The first operative results were calculated in 1990. Small area forest resource estimates, in here municipality level estimates, and estimates of variables in map form are calculated using field data from the Finnish national forest inventory, satellite images and other digital georeferenced data, such as topographic database of the National Land Survey of Finland. Seven sets of estimates have been produced for the most part of the country until now and six sets for Lapland. The number of the map form themes in the most recent version, from year 2015, is 45. In addition to the volumes by tree species and timber assortments, the biomass by tree species groups and tree compartments have been estimated. The first country level estimates correspond to years 1990-1994. The most recent versions are from years 2005, 2007, 2009, 2011, 2013 and 2015. The maps from 2015 is the fourth set of products freely available. It is also the second set produced by the Natural Resources Institute Finland. A new set of the products will be produced annually or biannually in the future. The maps are in a raster format with a pixel size of 16m x 16m (from 2013) and in the ETRS-TM35FIN coordinate system. The products cover the combined land categories forest land, poorly productive forest land and unproductive land. The other land categories as well as water bodies have been delineated out using the elements of the topographic database of the Land Survey of Finland.
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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)
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The OGC API service of Luomus is a geospatial data interface through which openly available species observation data from the Finnish Museum of Natural History (Luomus) is available as geospatial information. The service provides data that is selected based on its usefulness for authorities. Observations come from several different sources, all managed collectively by Luomus. The use of the service is free of charge and does not require authentication with a username or password.
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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
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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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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
Paikkatietohakemisto