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  • The map compiles seabed samples since 1985 onwards. The data includes geographic data and metadata related to each sample, mainly based on the data produced by the Geological Survey of Finland

  • Harvester Seasons is a service designed to help with estimating evolving trafficability conditions in forested terrain based on weather and model forecast information. The full service is currently provided for the geographical area of Finland.

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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. Nine sets of estimates have been produced for the most part of the country until now and eight sets for Lapland. The number of the map form themes in the most recent version, from year 2019, 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, 2015, 2017 and 2019. The maps from 2019 is the fifth set of products freely available. It is also the fourth 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.

  • A maritime spatial plan is a strategic development document illustrated by a map. Map markings are used to show the values of marine areas and existing activities and potential future sites for new activities and their alternative placement in all of Finland’s marine areas. The plan covers the territorial waters and the Exclusive Economic Zone. The plan is not legally binding, but an assessment of its indirect and direct impacts and effectiveness forms part of the planning process. The administrative authorities of coastal regional councils approved the plan, prepared according to the Land Use and Building Act, between November and December 2020. The councils of coastal regions have prepared the maritime spatial plan in three different parts: Gulf of Finland (Helsinki-Uusimaa Regional Council and Regional Council of Kymenlaakso), Archipelago Sea and Southern Bothnian Sea (Regional Council of Southwest Finland and Regional Council of Satakunta), and Northern Bothnian Sea, Quark and Bothnian Bay (Regional Council of Ostrobothnia, Regional Council of Central Ostrobothnia, Council of Oulu Region and Regional Council of Lapland). The data is suitable for a general-level examination of Finnish marine areas. More information on maritime spatial plan:

  • 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.

  • Seabed substrate maps of the European marine areas including (e.g. the Baltic Sea, the Greater North Sea, the Celtic Sea, the Iberian Coast, and the Mediterranean Sea within EU waters). The maps are collated and harmonized from seabed substrate information within the EMODnet-Geology III project. Where necessary, the existing seabed substrate classifications (of individual maps) have been translated to a scheme that is supported by EUNIS. This EMODnet reclassification scheme includes at least five seabed substrate classes. Four substrate classes are defined on the basis of the modified Folk triangle (mud to sandy mud; sand; coarse sediment; and mixed sediment) and one additional substrate class (rock and boulders) was included by the project team. If the original seabed substrate dataset has enabled more detailed substrate classification, classifications with 7 and 16 substrate classes might be available. The EMODnet-Geology III project started in 2017 with 39 marine departments of the geological surveys of Europe (from 30 countries), with an objective to assemble marine geological information from all European sea areas.

  • 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.

  • Laser scanning data refers to three-dimensional point-like data depicting the ground and objects on the ground. Each point is provided with x, y and z coordinate information. Laser scanning data is collected i.a. for updating elevation models, creating 3D geometries of buildings, mapping flood risks, and collecting information about forest resources. Laser scanning data 0.5 p has been spaced out from Laser scanning data 5 p's density of 5 p/m² to a density of 0.5 p/m². Laser scanning data 0.5 p is open data, and from 2020 onwards, it will be collected according to the national laser scanning programme (in Finnish): For the time being, it is available only from certain parts of Finland. Laser scanning data 0.5 p is available mainly automatically classified from the NLS Open data file download service: More information (in Finnish):

  • WFS download service for EMODnet Seabed substrate dataset: EMODnet Seabed substrate multiscale 1:1 000 000 –Europe (Seabed_substrate:multiscale_1m), EMODnet Seabed substrate multiscale 1:250 000 –Europe (Seabed_substrate:multiscale_250k), EMODnet Seabed substrate multiscale 1:100 000 –Europe (Seabed_substrate:multiscale_100k), EMODnet Seabed substrate multiscale 1:50 000 –Europe (Seabed_substrate:multiscale_50k), EMODnet Seabed substrate 1:100 000 –Europe (Seabed_substrate:seabed_substrate_100k), EMODnet Seabed substrate 1:250 000 –Europe (Seabed_substrate:seabed_substrate_250k), EMODnet Seabed substrate 1:1 000 000 –Europe (Seabed_substrate:seabed_substrate_1m), EMODnet Sedimention rates –Europe (Seabed_substrate:sedimentation_rates). The service is based on the EMODnet Geology dataset. The dataset is administrated by the Geological Survey of Finland. The service contains all features from the dataset that are modelled as polygons.

  • The database consists of three components: "Published age determination”, ”Published Sm-Nd isotope data" and "Pb isotope data on galena". The "Published age determination" database is based on age determinations, which comprise predominantly U-Pb zircon data produced at the Geological Survey of Finland since 1960’s. For igneous rocks the age register contains radiometric ages mostly interpreted as primary ages. The information given consists of location data, rock type, method, mineral analyzed, age results, comments and references. "Published Sm-Nd isotope data" comprise Sm-Nd data procuded at GTK since 1981, which mostly are used to constrain the origin of crust. "Pb isotope data on galena" gives results produced at GTK since 1970's, and include also previously unpublished data.