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 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

This dataset represents the Integrated biodiversity status assessment for benthic habitats using the BEAT tool. Status is shown in five categories based on the integrated assessment scores obtained in the tool. Biological Quality Ratios (BQR) above 0.6 correspond to good status. The assessment in open sea areas was based on the core indicators ‘State of the soft-bottom macrofauna community’ and ‘Oxygen debt’. Coastal areas were assessed by national indicators, and may hence not be directly comparable with each other. This dataset displays the result of the integrated biodiverity status in HELCOM Assessment unit Scale 4 (Division of the Baltic Sea into 17 sub-basins and further division into coastal and off-shore areas and division of the coastal areas by WFD water types or water bodies). Attribute information: "BQR" = Biological Quality Ratio "Confidence" = Confidence of the assessment "HELCOM_ID" = id of the HELCOM assessment unit "country" = name of the country / opensea "level_2" = HELCOM sub-basins (name of the scale 2 assessment unit) "Name" = Name of the coastal assessment unit on scale 4 "AULEVEL" = scale of the assessment units "type_descr" = Name of the HELCOM scale 4 assessment unit "SAUID" = ID number for the spatial assessment unit "EcosystemC" = Ecosystem component assessed "Confiden_1" = Confidence of the assessment (0-1, higher values mean higher confidence) "Total_numb" = Number of indicators used in assessment "Area_km2" = Area of assessment unit (km2) "Confiden_1" = Confidence level of the assessment (scores < 0.5 = low, 0.5 - 0.75 = intermediate, > 0.75 = high) "STATUS" = Integrated status category (0-0.2 = not good (lowest score), 0.2-0.4 = not good (lower score), 0.4-0.6 = not good (low score), 0.6-0.8 = good (high score), 0.8-1.0 = good (highest score))

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 partnership includes 39 marine organizations from 30 countries. The partners, mainly from the marine departments of the geological surveys of Europe (through the Association of European Geological Surveys-EuroGeoSurveys), 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). This dataset includes EMODnet seabed substrate maps at a scale of 1:60 000 from the European marine areas. 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. Further information about the EMODnet Geology project is available on the portal (http://www.emodnet-geology.eu/).

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.

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 raw materials of forest chips in Biomass Atlas are small-diameter trees from first thinning fellings and logging residues and stumps from final fellings. The harvesting potential consists of biomass that would be available after technical and economic constraints. Such constraints include, e.g., minimum removal of energywood per hectare, site fertility and recovery rate. Note that the techno-economic potential is usually higher than the actual availability, which depends on forest owners’ willingness to sell and competitive situation. The harvesting potentials were estimated using the sample plots of the 11th and 12th national forest inventory (NFI11 and NFI12) measured in the years 2013–2017. 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; Hirvelä et al. 2017). 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). Future potentials were assumed to materialize when the industrial roundwood fellings followed the level of maximum sustainable removals (80.7 mill. m3 in this calculation). 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 potential for energywood from first thinnings was calculated separately for all the wood from first thinnings (Small-diameter trees from first thinnings) and for material that does not fulfill the size-requirements for pulpwood (Small-diameter trees from first thinnings, smaller than pulpwood). The minimum top diameter of pulpwood in the calculation was 6.3 cm for pine (Pinus sylvestris) and 6.5 cm for spruce (Picea abies) and broadleaved species (mainly Betula pendula, B. pubescens, Populus tremula, Alnus incana, A. glutinosa and Salix spp.). The minimum length of a pulpwood log was assumed at 2.0 m. The potentials do not include branches. The potentials for logging residues and stumps were calculated as follows: The biomass removals of clear fellings were obtained from MELA. According to harvesting guidelines for energywood (Koistinen et al. 2016) mineral soils classified as sub-xeric (or weaker) and peatlands with corresponding low nutrient levels were left out from the potentials. Finally, technical recovery rates were applied (70% for logging residues and 82-84% for stumps) (Koistinen et al. 2016; Muinonen et al. 2013) The techno-economical harvesting potentials were first calculated for nineteen Finnish regions and then distributed on a raster grid at 1 km × 1 km resolution by weighting with Multi-Source NFI biomasses as described by Anttila et al. (2018). The potentials represent time period 2025-2034 and are presented as average annual potentials in solid cubic metres over bark. References Äijälä O, Koistinen A, Sved J, Vanhatalo K, Väisänen P. 2014. Metsänhoidon suositukset. [Guidelines for sustainable forest management]. Metsätalouden kehittämiskeskus Tapion julkaisuja. Anttila P., Nivala V., Salminen O., Hurskainen M., Kärki J., Lindroos T.J. & Asikainen A. 2018. Regional balance of forest chip supply and demand in Finland in 2030. Silva Fennica vol. 52 no. 2 article id 9902. 20 s. https://doi.org/10.14214/sf.9902 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, 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]. Tapion julkaisuja. 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. Siitonen M, Härkönen K, Hirvelä H, Jämsä J, Kilpeläinen H, Salminen O et al. 1996. MELA Handbook. 622. 951-40-1543-6.

NLS-FI INSPIRE View Service for Geographical Names Theme is an INSPIRE compliant Web Map Service. It contains the following harmonized INSPIRE map layers: NamedPlace. The service is based on the Geographic Names Register of the National Land Survey of Finland. The dataset is administrated by the National Land Survey of Finland.