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

Hillshade (elevation model) is a raster dataset visualising the elevation of the terrain. There are five product versions available in which the pixel sizes are 2, 8, 32, 64, 128 and 512 metres. Pixel size 2 m has been produced of the dataset Elevation model 2 m. The other sizes have been produced of the dataset Elevation model 10 m. The material does not contain elevation values; it is a greyscale image that visualises the direction and steepness of hills. The product belongs to the open data of the National Land Survey of Finland.

This dataset represents the density of all IMO registered ships operating in the Baltic Sea. Density is defined as the number of ships crossing a 1 x 1km grid cell. It is based on HELCOM AIS (Automatic Identification System) data. The HELCOM AIS network hosts all the AIS signals received by the Baltic Sea States since 2005. The AIS Explorer allows to compare density maps of different ship types per month: http://maps.helcom.fi/website/AISexplorer/ The data was processed to produce density maps and traffic statistics. All scripts are available in GitHub: https://github.com/helcomsecretariat. The production of these maps have been carried out 2016-2017 through the HELCOM project on the assessment of maritime activities in the Baltic Sea. The underlying AIS data processing work has been co-financed by EU projects Baltic Scope (2015-2017 EASME/EMFF/2014/1.2.1.5) and Baltic Lines (2016-2019, Interreg Baltic Sea Region). In addition, the Ministry of the Environment of Finland supported the work with a special contribution in view of the use of the results in the HOLAS II process.

The Regional Till Geochemical Mapping data set gives information on the concentrations of 37 elements in unaltered basal till. The samples have been taken, in 1983, from an unaltered basal till (C horizon) below the groundwater table at a depth of ca. 70 cm (variation 50-200 cm) with a density of one sample per 300 km2. The data set covers the whole of Finland with a total sample amount of 1056. The samples are composite field samples. The calculated sample point coordinates entered in the data set have been obtained from the centroid coordinates of five subsamples. The subsamples have been collected from a 300 m x 1000 m rectangular-shaped area. In Northern Finland, samples have been obtained by including samples taken previously in the Nordkallot Project. The samples have been sieved for analysis at a grain size grade less than 0.06 mm. The samples have been analysed for total elemental concentrations and aqua regia concentrations. Total concentrations have been determined either by neutron activation analysis (method code 900N) or by total dissolution with strong concentrated mineral acids (method code 312P). The analysis code for aqua regia dissolution is 511P. Gold and palladium have been determined with a analysis method based on flameless atomic absorption (519U). The sulfur concentration has been determined with a LECO analyser (810L). Further, total concentrations (312P) and aqua regia soluble concentrations (511P) were determined from Southern Finland and Mid-Finland samples with a grain size grade less than two millimetres. The original purpose of the Regional Till Geochemical Mapping data set was national geochemical general mapping and ore exploration. Other uses are, for example, estimating the baseline concentration of the soil, the nutrient levels of forest soil, assessing the buffering capacity of base cations in the soil and evaluating the weathering rate.

NLS-FI INSPIRE Download Service (WFS) for Buildings/Polygon is an INSPIRE compliant direct access Web Feature Service. It contains the following INSPIRE feature types: Building The service is based on the NLS-FI INSPIRE Buildings Theme Dataset. The dataset is administrated by the National Land Survey of Finland. The service contains all features from the dataset that are modelled as polygons.

The Multi-Source National Forest Inventory of Finland (MS-NFI) view service is a WMS service that provides access to raster themes for viewing. The datasets have been computed for target years 2006 (three themes), 2009 (43 themes), 2011 (45 themes), 2013 (45 themes), 2015 (45 themes), 2017 (45 themes), 2019 (45 themes), 2021 (45 themes) and 2023 (45 themes).. The quantitative themes consist of estimates of stem volumes, total and by tree species and timber assortments (13 themes), biomasses by tree species groups and tree compartments (21 themes), basal area, age, mean height, mean diameter, canopy cover and canopy cover for broad-leaved trees. The categorical classifications include land cover type (Finnish definition and from 2011 also FRA definition), main site class, site fertility class and data source index (from 2011). The 2006 themes include only mean height, canopy cover and canopy cover for broad-leaved trees. The themes have been computed by the Natural Resource Institute of Finland (Luke) using National Forest Inventory (NFI) field data, satellite images and digital map data (provided by NLS). Use of service is free and no authentication is required.

The technical harvesting potential of logging residues and stumps from final fellings can be defined as the maximum potential procurement volume of these available from the Finnish forests based on the prevailing guidelines for harvesting of energy wood. The potentials of logging residues and stumps have been calculated for fifteen NUTS3-based Finnish regions covering the whole country (Koljonen et al. 2017). The 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). Final fellings consisted of clear cutting, seed tree cutting, and shelter-wood cutting, but only the clear-cutting areas were utilized for energy wood harvesting. As both logging residues and stumps are byproducts of roundwood removals, the technical potentials of chips have to be linked with removals of industrial roundwood. Future potentials were assumed to materialize when the industrial roundwood fellings followed the level of maximum sustainable removals. The maximum sustainable removals were defined such that the net present value calculated with a 4% discount rate was maximized subject to non-declining periodic industrial roundwood and energy wood removals and net incomes, and subject to the saw log removal remaining at least at the level of the first period. There were no constraints concerning tree species selection, cutting methods, age classes, or the growth/drain ratio in order to efficiently utilize the dynamics of forest structure. The felling behaviour of the forest owners was not taken into account either. For the present situation in 2015, the removal of industrial roundwood was assumed to be the same as the average level in 2008–2012. Fourth, the technical harvesting potentials were derived by retention of 30% of the logging residues onsite (Koistinen et al. 2016) and respectively by retention of 16–18% of stump biomass (Muinonen et al. 2013). Next, the regional potentials were allocated to municipalities proportionally to their share of mature forests (MetINFO 2014). Subsequently, the municipality-level potentials were spread evenly 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. Here, 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). 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. 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 Fenn 47. 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.