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From 1 - 10 / 2026
  • The Baltic Sea Impact Index is an assessment component that describes the potential cumulative burden on the environment in different parts of the Baltic Sea. The BSII is based on georeferenced datasets of human activities (36 datasets), pressures (18 datasets) and ecosystem components (36 datasets), and on sensitivity estimates of ecosystem components (so-called sensitivity scores) that combine the pressure and ecosystem component layers, created in <a href="http://www.helcom.fi/helcom-at-work/projects/holas-ii" target="_blank">HOLAS II</a> project. Cumulative impacts are calculated for each assessment unit (1 km2 grid cells) by summing all pressures occurring in the unit for each ecosystem component. Highest impacts are found from the cells where both are abundant, but high impacts can be caused also by a single pressure if there are diverse and sensitive habitats in the grid cell. All data sets and methodologies used in the index calculations are approved by all HELCOM Contracting Parties in review and acceptance processes. This data set covers the time period 2011-2016. Please scroll down to "Lineage" and visit <a href="http://stateofthebalticsea.helcom.fi/cumulative-impacts/" target="_blank">State of the Baltic Sea website</a> for more info.

  • The technical harvesting potential of small-diameter trees can be defined as the maximum potential procurement volume of small-diameter trees available from the Finnish forests based on the prevailing guidelines for harvesting of energy wood. The potentials of small-diameter trees from early thinnings have been calculated for fifteen NUTS3-based Finnish regions covering the whole country (Koljonen et al. 2017). To begin with the estimation of the region-level potentials, technical harvesting potentials were estimated using the sample plots of the eleventh national forest inventory (NFI11) measured in the years 2009–2013. First, a large number of sound and sustainable management schedules for five consecutive ten-year periods were simulated for each sample plot using a large-scale Finnish forest planning system known as MELA (Siitonen et al. 1996; Redsven et al. 2013). MELA simulations consisted of natural processes and human actions. The ingrowth, growth, and mortality of trees were predicted based on a set of distance-independent tree-level statistical models (e.g. Hynynen et al. 2002) included in MELA and the simulation of the stand (sample plot)-level management actions was based on the current Finnish silvicultural guidelines (Äijälä et al. 2014) and the guidelines for harvesting of energy wood (Koistinen et al. 2016). Simulated management actions for the small-tree fraction consisted of thinnings that fulfilled the following stand criteria: • mean diameter at breast height ≥ 8 cm • number of stems ≥ 1500 ha-1 • mean height < 10.5 m (in Lapland) or mean height < 12.5 m (elsewhere). Energy wood was harvested as delimbed (i.e. including the stem only) in spruce-dominated stands and peatlands and as whole trees (i.e. including stem and branches) elsewhere. When harvested as whole trees, a total of 30% of the original crown biomass was left onsite (Koistinen et al. 2016). Energy wood thinnings could be integrated with roundwood logging or carried out independently. Second, the technical energy wood potential of small trees was operationalized in MELA by maximizing the removal of thinnings in the first period. In this way, it was possible to pick out all small tree fellings simulated in the first period despite, for example, the profitability of the operation. However, a single logging event was rejected if the energy wood removal was lower than 25 m³ha-1 or the industrial roundwood removal of pine, spruce, or birch exceeded 45 m³ha-1. The potential calculated in this way contained also timber suitable for industrial roundwood. Therefore, two estimates are given: • potential of trees below 10.5 cm in breast-height diameter • potential of trees below 14.5 cm in breast-height diameter. Subsequently, the region-level potentials were spread on a raster grid at 1 km × 1 km resolution. Only grid cells on Forests Available for Wood Supply (FAWS) were considered in this operation. In this study, FAWS was defined as follows: First, forest land was extracted from the Finnish Multi-Source National Forest Inventory (MS-NFI) 2013 data (Mäkisara et al. 2016). Second, restricted areas were excluded from forest land. The restricted areas consisted of nationally protected areas (e.g. nature parks, national parks, protection programme areas) and areas protected by the State Forest Enterprise. In addition, some areas in northernmost Lapland restricted by separate agreements between the State Forest Enterprise and stakeholders were left out from the final data. Furthermore, for small trees, FAWS was further constrained by the stand criteria presented above to represent similar stand conditions for small-tree harvesting as in MELA. Finally, the region-level potentials were distributed to the grid cells by weighting with MS-NFI stem wood biomasses. References Äijälä O, Koistinen A, Sved J, Vanhatalo K, Väisänen P (2014) Metsänhoidon suositukset [Guidelines for sustainable forest management]. Metsätalouden kehittämiskeskus Tapion julkaisuja. Hynynen J, Ojansuu R, Hökkä H, Salminen H, Siipilehto J, Haapala P (2002) Models for predicting the stand development – description of biological processes in MELA system. The Finnish Forest Research Institute Research Papers 835. Koistinen A, Luiro J, Vanhatalo K (2016) Metsänhoidon suositukset energiapuun korjuuseen, työopas [Guidelines for sustainable harvesting of energy wood]. Metsäkustannus Oy, Helsinki. Koljonen T, Soimakallio S, Asikainen A, Lanki T, Anttila P, Hildén M, Honkatukia J, Karvosenoja N, Lehtilä A, Lehtonen H, Lindroos TJ, Regina K, Salminen O, Savolahti M, Siljander R (2017) Energia ja ilmastostrategian vaikutusarviot: Yhteenvetoraportti. [Impact assessments of the Energy and Climate strategy: The summary report.] Publications of the Government´s analysis, assessment and research activities 21/2017. Mäkisara K, Katila M, Peräsaari J, Tomppo E (2016) The Multi-Source National Forest Inventory of Finland – methods and results 2013. Natural resources and bioeconomy studies 10/2016. Redsven V, Hirvelä H, Härkönen K, Salminen O, Siitonen M (2013) MELA2012 Reference Manual. Finnish Forest Research Institute. Siitonen M, Härkönen K, Hirvelä H, Jämsä J, Kilpeläinen H, Salminen O, Teuri M (1996) MELA Handbook. Metsäntutkimuslaitoksen tiedonantoja 622. ISBN 951-40-1543-6.

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    The GTK’s Mineral Deposit database contains all mineral deposits, occurrences and prospects in Finland. Structure of the new database was created in 2012 and it is based on global geostan-dards (GeoSciML and EarthResourceML) and classifications related to them. The database is in Oracle, data products are extracted from the primary database. During 2013 GTK’s separate mineral deposit databases (Au, Zn, Ni, PGE, U, Cu, Industrial minerals, FODD, old ore deposit database) were combined into a single entity. New database contains extensive amount of information about mineral occurrence feature along with its associated commodities, exploration activities, holding history, mineral resource and re-serve estimates, mining activity, production and geology (genetic type, host and wall rocks, min-erals, metamorphism, alteration, age, texture, structure etc.) Database will be updated whenever new data (e.g. resource estimate) is available or new deposit is found. Entries contain references to all published literature and other primary sources of data. Also figures (maps, cross sections, photographs etc.) can be linked to mineral deposit data. Data is based on all public information on the deposits available including published literature, archive reports, press releases, companies’ web pages, and interviews of exploration geologists. Database contains 33 linked tables with 216 data fields. Detailed description of the tables and fields can be found in separate document. (http://tupa/metaviite/MDD_FieldDescription.pdf) The data products extracted from the database are available on Mineral Deposits and Exploration map service (http://gtkdata.gtk.fi/MDaE/index.html) and from Hakku -service (http://hakku.gtk.fi).

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    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.

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    Sedimentation rates are part of EMODnet (European Marine Observation and Data network) Geology, Work Package 3 (WP3) Seabed substrate. The objective of WP3 is to compile all available seabed substrate information on a scale of 1:100 000 or finer from all European marine areas, and to update sedimentation rate data collected in the previous phases. WP3 has compiled and harmonized available information on the rate of sedimentation on the seafloor. The information on sedimentation rates for recent sediments is presented as point-source information. Estimations of modern sedimentation rates (centimetres/year) can be based e.g. on established historical records of anthropogenic radionuclides (e.g. 137Cs and 241Am), polychlorinated biphenyls (PCBs), lead (Pb) and stable lead isotope (206/207Pb ratios). Sedimentation rate estimations can be based also on varve/laminae counting, radionuclide 210Pb and 14C decay dating methods. In addition stratigraphic marker horizons, like in the Baltic Sea, horizons formed by documented Major Baltic Inflow (MBIs) events (Moros et al. 2017), can be used in the estimations. Project partners have delivered information on sedimentation rates available in their national waters including their EEZ. The focus is on the present-day sedimentation rates. That means sediment accumulation to the seabed over the past decades, since AD 1900 or so. Further information about the EMODnet-Geology project is available on the portal (http://www.emodnet-geology.eu/).

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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.

  • 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