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  • Road traffic accidents involving personal injury known to the police in Finland and reported to Statistics Finland, which have co-ordinate data. The data cover the following information: vvonn = year of the accident kkonn = month of the accident kello = time of the accident vakav = seriousness of the accident: 1 = accident resulting in death, 2 = accident resulting in injury, 3 = accident resulting in serious injury onntyyppi = type of accident: 0 = Same direction of travel (going straight), 1 = Same direction of travel (turning), 2 = Opposite direction of travel (going straight), 3 = Opposite direction of travel (turning), 4 = Intersecting direction of travel (going straight), 5 = Intersecting direction of travel (turning), 6 = Pedestrian accident (on pedestrian crossing), 7 = Pedestrian accident (elsewhere), 8 = Running off the road, 9 = Other accident lkmhapa = number of passenger cars and vans in the accident lkmlaka = number of buses and lorries in the accident lkmjk = number of pedestrians in the accident lkmpp = number of cyclists in the accident lkmmo = number of mopeds in the accident lkmmp = number of motor cycles in the accident lkmmuukulk = number of other vehicles in the accident x = x co-ordinate of the accident y = y co-ordinate of the accident The general Terms of Use must be observed when using the data (http://tilastokeskus.fi/org/lainsaadanto/copyright_en.html).

  • NLS-FI INSPIRE Cadastral Parcels Theme Dataset is a dataset depicting the Cadastral Parcels and Basic Property Units covering the whole of Finland. It contains the following INSPIRE feature types: BasicPropertyUnit, CadastralParcel, CadastralBoundary. The elements are updated weekly. The dataset is based on the NLS Cadastral Index Map database. The dataset is available via the NLS-FI INSPIRE Download Service (WFS) for Cadastral Parcels Theme and it can be viewed via the NLS-FI INSPIRE View Service (WMS) for Cadastral Parcels.

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    Lorry parking areas at E18 road in Finland. Data is in Esri shapefiles, in ETRS-TM35FIN coordinates. Data is maintained and provided by FTA (Finnish Transport Agency).

  • 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.

  • The themes of the Topographic database and Topographic map raster series (scale 1:10,000) have been compiled into seven theme entities, theme rasters, required by the Inspire directive: hydrography, elevation, traffic network, land use, land cover, place names and buildings. In addition to the above, the theme rasters also include the municipal division, road names and map sheet division as separate themes. The theme rasters have not been implemented according to the imaging technology defined in the Inspire directive. They will be produced later. The product belongs to the open data of the National Land Survey of Finland. More information: Topographic data and how to acquire it http://www.maanmittauslaitos.fi/en/maps-and-spatial-data/expert-users/topographic-data-and-how-acquire-it.

  • NLS-FI INSPIRE Geographical Names Theme Dataset is a dataset depicting the Named Places and Geographical Names covering the whole of Finland. It contains the following INSPIRE feature types: NamedPlace The elements are updated weekly. The dataset is based on the Geographic Names Register of the National Land Survey of Finland: http://www.paikkatietohakemisto.fi/geonetwork/srv/fin/catalog.search#/metadata/eec8a276-a406-4b0a-8896-741cd716ade6 The dataset is available via the NLS-FI INSPIRE Download Service (WFS) for Geographical Names Theme and it can be viewed via the NLS-FI INSPIRE View Service (WMS) for Geographical Names.

  • Control points and their coordinates and elevations define in practice the reference system for coordinates and elevations used in Finland. The NLS benchmark register contains information about nationwide control points and benchmarks. The marks are mainly horizontal and elevation control points in classes 1–3 measured by the National Land Survey of Finland. The product belongs to the open data of the National Land Survey of Finland. More information: Topographic data and how to acquire it http://www.maanmittauslaitos.fi/en/maps-and-spatial-data/expert-users/topographic-data-and-how-acquire-it.

  • Grid net for statistics 1 km x 1 km covers whole of Finland. The grid net includes all grid squares in Finland. The location reference of a grid square is the coordinates of the bottom left corner of each grid cell. An identifier in accordance with national conventions (consecutive numbering) and INSPIRE definitions (format: 1kmNxxxxExxxx, where 1 km expresses the square grid size, N the y coordinate of the bottom left corner of the square divided by 1,000 and E the x coordinate of the bottom left corner of the square divided by 1,000) has been produced for each grid cell. The Grid net for statistics 1 km x 1 km is the area division used in the production of statistics by 1 km x 1 km squares. The general Terms of Use must be observed when using the data (http://tilastokeskus.fi/org/lainsaadanto/copyright_en.html).

  • 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.