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  • 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 orthophotos are an aerial photo data set covering the whole of Finland. The geometry of the orthophotos corresponds to a map. NLS orthophotos are updated every 3 to 10 years. The product is a part of the open data of the National Land Survey of Finland. More information: Acquisition of open data http://www.maanmittauslaitos.fi/en/maps-and-spatial-data/expert-users/topographic-data-and-how-acquire-it

  • The Topographic map series is a dataset depicting the terrain of all of Finland. The key elements in it are the road network, buildings and constructions, geographic names, waterways, land use and elevation. The more precise levels of the Topographic map series consist of the same map objects and map symbols depicted in the same way as in the familiar Basic map. Basic map raster is applicable to be used, for instance, as a base map for planning land use or for excursion and outdoor recreational purposes in mobile devices and in various Internet services associated with nature. When going over to the more general datasets in the Topographic map series, the number and visualisation of objects and map symbols changes. The generalised small-scale Topographic maps raster are applicable to be used as approach maps in e.g. mobile devices and Internet services. 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

  • 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.

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    Forests of high biodiversity value 2018 (Zonation) datapackage consists of 12 nationwide raster maps from Finland. These 12 maps are all different versions of biodiversity values of Finnish forests. Resolution of these raster maps is 96 meters x 96 meters. Simple instructions for reading the raster maps: The bigger the numeric value the higher the biodiversity value. NAT = National scale analyses of biodiversity values of Finnish forests (6 analysis) REG = Regional scale analyses of biodiversity values of Finnish forests (map looks like one but is in reality a collection of 13 separately done analysis, region = Centre for Economic Development, Transport and the Environment in Finland) (6 analysis) Six different spatial conservation prioritizations were made with Zonation Software (a) so that each new version included everything that had been included in previous, simpler, analysis versions. NAT / REG 1 Decaying wood potential: Version 1 (V1) included the local decaying wood potentials*. Areas with lot of large trees, many tree species and rare forest environments get high local value. NAT / REG 2 Decaying wood potential – penalties: Version 2 = V1 + penalties for forestry operations with negative impact on biodiversity. More realistic local values when taking into account real life changes in forests. NAT / REG 3 Decaying wood potential – penalties + forest connectivity: Version 3 = V2 + connectivity based on ecological similarity, distance and quality between forest patches (attenuation avg. 400m). Unfragmented high value forests areas emerge. NAT / REG 4 Decaying wood potential – penalties + forest connectivity + RL species: Version 4 = V3 + observations of Red List forest species. Red List forest species habitats emerge. NAT / REG 5 Decaying wood potential – penalties + forest connectivity + RL species + FFA 10§: Version 5 = V4 + connectivity to woodland key habitats protected by Finnish Forest Act 10 § (attenuation avg. 200m). Valuable forest areas and landscapes close to protected high biodiversity forest patches emerge. NAT / REG 6 Decaying wood potential – penalties + forest connectivity + RL species + FFA 10§ + PA connectivity: Version 6 = V5 + connectivity to permanent conservation areas (attenuation avg. 2km). Valuable forest areas and landscapes close to protected high biodiversity areas emerge. *Calculation of Decaying wood potential (DWP) DWP was calculated for every strata of tree species in every crown storey class in 2 stages: 1) Decaying wood potential indexes (DWPi) were modelled with MOTTI-program (b, c, d). • 168 tree species, fertility class and latitude combinations 2) DWPis were used for converting diameter and volume into decaying wood potential • Generated for the whole Finland at tree stand level at the resolution of 16 m x 16 m • Eventually combined into 20 tree species & fertility classes and aggregated to 96 m x 96 m resolution. Input data Decaying wood potential was calculated from forest stand level datasets (tree species, diameter, volume, fertility) covering whole Finland. Best possible data was used for every area. - 24 % of Finland covered by state-owned forestry and conservation areas and private conservation areas o Metsähallitus Parks & Wildlife: field and forest stand data (5/2015) o Metsähallitus Forestry Inc.: field and forest stand data (5/2015) o Private owned conservation areas: field and forest stand data (5/2015) - 37 % of Finland covered by privately owned other than protected forest areas: Finnish Forest Centre, forest information (6.5.2005 – 6.5.2015) - 39 % of Finland covered by o Natural Resources Institute Finland: Multi-source national forest inventory data of Finland 2013(volume, tree species, fertility class, diameter) Spatial data on forestry operations with negative impact on biodiversity (e. g. fellings, thinning and ditching) (updated 10/2017) - National Land Survey of Finland & Finnish Environment Institute SYKE: Ditching state of Finnish peatlands (SOJT_09b1) - Metsähallitus Forestry Inc.: Executed forest operations of forest operations from field and forest stand data and ditching status - Finnish Forest Centre: Forest declariations and ditching status - University of Maryland / Dept. of Geographica Sciences: Global Forest Change / Forest Cover Loss 2000-2014 Observations of IUCN Red List forest species (since 1990): Finnish Environmental database HERTTA Spatial data on woodland key habitats protected by The Finnish Forest Act 10§ (updated 10/2017) - Finnish Forest Centre: woodland key habitats protected by Finnish Forest act 10§ Spatial data on permanent conservation areas (updated 2/2018) - Metsähallitus Parks & Wildlife: Conservation area database SATJ Background Areas important to forest biodiversity were identified throughout Finland to support sustainable land using planning and nature conservation at local, regional and national level by informing land owners, ministries and forestry stakeholders. Importance of analyzes like this rise from increased usage of natural resources and consequent harmful impacts on biodiversity together with limited resources for conservation. These highlight the importance of developing cost-effective, ecologically sustainable land use planning approaches such as these spatial conservation prioritizations of forests made for a first time for the whole Finland. Prioritization approach, Zonation, was used to find new forest areas of potential high conservation value. The overall aim was to implement nationwide prioritization analyses based on biodiversity-related forest data and land use data recorded at the level of forest stand. Primarily employed data on forest structure and quality (vegetation class, tree species, volume and diameter) provided ecologically useful surrogates for conservation value in boreal forest. Results show that a significant portion of high biodiversity value forests lay outside the current Finnish protected area (PA) network. As most of the Finnish forest area is under commercial management, PA network cannot halt the on-going decline of forest biodiversity. Keywords: biodiversity value, decaying wood, forest biodiversity, Forest Biodiversity Programme for Southern Finland (METSO), forest conservation, forestry, geographical information system (GIS), land use, spatial conservation prioritization, Zonation software Datapackage includes all 12 raster maps and a .lyr -file. .lyr -file contains coloured symbology and descriptions of different analysis versions. .lyr -file is probably operable only with GIS-software prvided by ESRI Inc. Datapackage can be loaded from: http://www.syke.fi/en-US/Open_information/Spatial_datasets High Biodiversity Value Forests 2018 (Zonation) nationwide High Biodiversity Value Forests 2018 (Zonation) regional Detailed poster available: http://www.syke.fi/en-US/Research__Development/Ecosystem_services/Specialist_work/Zonation_in_Finland/Zonation_materials/Posters OR http://www.syke.fi/download/noname/%7B771FF5A4-DAB6-45EE-8246-F38FC0090CAD%7D/138289 Detailed report (only in Finnish): http://hdl.handle.net/10138/234359 Mikkonen et al. 2018. Suomen ympäristökeskuksen raportteja 9/2018. Monimuotoisuudelle tärkeät metsäalueet Suomessa - Puustoisten elinympäristöjen monimuotoisuusarvojen Zonation-analyysien loppuraportti. Other references: a) Moilanen et al. 2014. Zonation–Spatial Conservation Planning Methods and Software. Version 4. User Manual. See also www.syke.fi/Zonation/en b) Hynynen et al. 2015. Eur. J. For. Res. 134/3. Long-term impacts of forest management on biomass supply and forest resource development: a scenario analysis for Finland. c) Hynynen et al. 2014. Metlan työraportteja 302. Scenario analysis for the biomass supply potential and the future development of Finnish forest resources. d) Salminen et al. 2005. Comput. electron. agr. 49/1. Reusing legacy FORTRAN in the MOTTI growth and yield simulator. Availability: Aineisto kuuluu SYKEn avoimiin aineistoihin (CC BY 4.0) Creative Commons 4.0. © SYKE Datasources: Finnish Forest Centre, Metsähallitus, Natural Resources Institute Finland 2015, National Land Survey of Finland, Hansen/UMD/Google/USGS/NASA

  • 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. Six sets of estimates have been produced for the most part of the country until now and five sets for Lapland. The number of the map form themes in the most recent version, from year 2011, 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 and 2011. The maps from 2011 is the second set of products freely available. The 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 20mx20m 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 topographic database of the Land Survey of Finland.

  • 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.

  • 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 2017, 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 and 2017. The maps from 2017 is the fifth set of products freely available. It is also the third 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.

  • 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. in order to produce elevation models and collect information about forest resources. Currently laser scanning data is available only from certain parts of Finland. Laser scanning data belongs to the open data of the National Land Survey of Finland. All laser scanning data is available as a version where the points that represent the ground surface are automatically classified. Part of the laser scanning data is available as a version where the points that represent the ground surface are classified with the help of stereo models. Both versions are available from the NLS File service of open data. 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.

  • The Arctic SDI Geoportal provides access to geospatial data and services available via the Arctic SDI to support and facilitate monitoring, management and decision making, and support sustainable development in the Arctic. Specifically, the Arctic SDI Geoportal facilitates the discovery, visualization, evaluation, download and integration of geographic data from a variety of sources for the Arctic. The Arctic SDI Geoportal is the result of cooperative efforts between the National Mapping Agencies (NMAs) of the eight Arctic Council Member countries - Canada, Denmark, Finland, Iceland, Norway, Russia, Sweden and the United States. The Arctic SDI Geoportal includes reference data (such as the Arctic SDI topographic basemap or Pan-Arctic Digital Elevation Model) and thematic data from various sources. Thematic data section includes themes such as oceans, climatology and geoscientific information. Most of the data covers the Arctic or the involved Arctic countries, but new data sources with a smaller or larger geographical extent may be accepted. The Geoportal allows searching placenames via a circumpolar gazetteer, and embedding interactive maps to any website. Some of the features require registration.