Kasvukauden alku / Start of vegetation period

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)

Uomakorjaus: rumpujen kaiverrus (korkeusmalli 2m)

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).

EMODnet View Service for Seabed substrate

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 project partnership consists mainly of the marine departments of the geological surveys of Europe (through the Association of European Geological Surveys-EuroGeoSurveys), which 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), the Caspian Sea and the Caribbean Sea. EMODnet seabed substrate data products include datasets at 1:1 000 000, 1:250 000, 1:100 000 and high-resolution scales (1:1 500, 1:5 000, 1:10 000, 1:15 000, 1:20 000, 1:25 000, 1:30 000, 1:45 000, 1: 50 000, 1:60 000, 1:70 000). 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. The datasets have been compiled at different scales from background information that depends on the original producer. In cases, the data has been generalized into a target scales. Coarser scale data (1M, 250k and 100k) describes the seabed substrate at a general level only and is not suitable for a detailed analysis. High-resolution material includes multiple scales from 1:1 500 to 1:70 000 and the user should assess its suitability for the intended purpose. The smallest cartographic unit within the data is about 4 km2 at 1:1M, 0,3km2 at 1:250k and 0,05km2 at 1:100k scale. Further information about the EMODnet Geology project is available on the centralized EMODnet portal https://emodnet.ec.europa.eu/en/geology.

Energywood potentials 2026-2035

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

Kasvihuonekaasupäästöt maanpeitteen mukaan

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.

Hiekkarantojen ominaisuudet

FIN Suomen hiekkarantoja ja niiden taustatekijöitä kuvaava aineisto. Datan taustalla olevan hankkeen pääasiallisena tarkoituksena on hiekkarantojen identifioiminen parhaasta käytettävissä olevasta tiedosta, näiden rantojen ominaispiirteiden kuvaaminen, ympäristöllisen arvon arvioiminen sekä hoitotarpeessa olevien rantojen löytäminen. Aineistosta on julkaistu kaksi erillistä versiota. -HiekkarantojenOminaisuudet_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 -HiekkarantojenOminaisuudet_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/RantaPutte_Menetelmakuvaus.pdf sekä muuttujaseloste https://geoportal.ymparisto.fi/meta/julkinen/dokumentit/RantaPutte_VariableDescription.xlsx ENG This data describes Finnish sandy beaches and their background factors. The main purpose of the project underlying the data is to identify sandy beaches from the best available information, to describe the characteristics of these beaches, to assess their environmental value and to find beaches in need of conservation There are two separate versions of the data. -HiekkarantojenOminaisuudet_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. -HiekkarantojenOminaisuudet_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/RantaPutte_Menetelmakuvaus.pdf All the variables in the data are explained in this bilingual variable description https://geoportal.ymparisto.fi/meta/julkinen/dokumentit/RantaPutte_VariableDescription.xlsx

Statistics Finland's Web Service (WMS)

Statistics Finland's Web Service is a WMS interface service through which the following data required by INSPIRE and national legislation on geographic information are available: 1) Statistical units: Regional divisions (municipality, major region, region, sub-regional unit, Regional State Administrative Agency (AVI), Centre for Economic Development, Transport and the Environment (ELY), electoral district) and grid 1 km x 1 km. 2) Non-profit and public services: Educational institutions (comprehensive schools, upper secon-dary general schools) 3) Production and industrial facilities: Production and industrial facilities 4) Population distribution by the regional divisions used in statistics and by 1 km x 1 km grids. Other data published: - Open data by postal code area (Paavo) - Population distribution by 5 km x 5 km grids The data are administered by Statistics Finland. The service is free of charge and does not require authentication or identification with a user ID and password. The general Terms of Use must be observed when using the data: http://tilastokeskus.fi/org/lainsaadanto/copyright_en.html.

Ortokuvien ja korkeusmallien kyselypalvelu (WCS)

Ortokuvien ja korkeusmallien kyselypalvelun (WCS) kautta voit hakea rasterimuotoisia ortokuvia ja korkeusmalleja. Palvelussa voit poimia haluttuja paloja aineistoista omalla aluerajauksellasi. Ortokuvien osalta palvelu sisältää Maanmittauslaitoksen väri-, vääräväri- ja mustavalkoisia ortokuvia eri vuosilta. Korkeusmalli on 2 m korkeusmallia, joka on tuotettu laserkeilausaineiston pohjalta. Korkeusmallia pystyy hakemaan palvelusta myös karkeammilla kuin 2m resoluutioilla. Tarjolla ovat seuraavat resoluutiot: 2 m, 4 m, 8 m, 16 m, 32 m, 64 m, 128 m, 256 m ja 512 m. Ortokuvat ovat saatavilla palvelusta GeoTIFF-formaatissa ja korkeusmalli GeoTIFF- tai ASCII Grid -formaatissa. Palvelun käyttäminen edellyttää perehtyneisyyttä paikkatietorajapintojen ohjelmalliseen hyödyntämiseen. Yksittäisten latausten tekeminen onnistuu myös selaimella. Ladatut tiedostot saat auki ja voit jatkokäsitellä paikkatieto-ohjelmalla. Toistaiseksi palvelua ei pysty käyttämään esimerkiksi QGIS -ohjelmalla. Aineistot ovat Maanmittauslaitoksen avoimen tietoaineiston Nimeä CC 4.0 -lisenssin alaisia. Palvelu tarjotaan avoimena rajapintana, jonka käyttö on maksutonta. Käyttäjä tunnistetaan API-avaimella. Lue lisää Maanmittauslaitoksen avoimen rajapinnan käyttöehdoista ja API-avaimen luomisesta ja käyttämisestä. https://www.maanmittauslaitos.fi/rajapinnat/api-avaimen-ohje https://www.maanmittauslaitos.fi/ortokuvien-ja-korkeusmallien-kyselypalvelu

Crop sidestreams

Field biomass sidestreams GIS data describes the maximum harvestable sidestream potential based on current tillage. Sidestreams has been calculated by crop statistics, cultivation area, solid content and harvest index. Harvest index describes the part of the plant that is utilized as a crop. Rest of the plant is considered sidestream. In many cases the maximum sidestream cannot be necessarily utilized as whole, because of technical and economical constraints for harvest. Part of the sidestream is also wise to plough in to field to maintain its fertility. Field crop data is conducted from Luke's crop production statistics. The crop statistics in ELY centre level is divided into the Biomass Atlas grid weighting by the crop area of that certain plant. Crop area is from IACS-register, used to manage subsidies in agriculture. Farmers report their cultivation plans there every spring. Crop area and amount are from same year, usually previous year.

Statistics Finland's INSPIRE data Web Service (OGC API Features)

Statistics Finland's INSPIRE data Web Service is a OGC API interface service through which the following data required by INSPIRE and national legislation on geographic information are available: 1) Statistical units: Regional divisions (municipality, major region, region, sub-regional unit, Regional State Administrative Agency (AVI), Centre for Economic Development, Transport and the Environment (ELY), electoral district) and grids 1 km x 1 km and 5 km x 5 km 2) Non-profit and public services: Educational institutions (comprehensive schools, upper secondary general schools) 3) Production and industrial facilities: Production and industrial facilities 4) Population distribution by the regional divisions used in statistics and by 1 km x 1 km and 5 km x 5 km grids. The data are administered by Statistics Finland. The service is free of charge and does not require authentication or identification with a user ID and password. The general Terms of Use must be observed when using the data: http://tilastokeskus.fi/org/lainsaadanto/copyright_en.html.