Paavo - Open data by postal code area contain the following geographic data: 1) Paavo postal code areas 2) Paavo postal code areas (extended to sea areas) 3) Paavo statistical data (103 variables) combined with the postal code areas There are two different versions of the map data: extending to sea areas mainly produced for statistics production, and the version produced from this for map visualisation cut with the coastline. The map data contain the surface areas of the postal code areas and the municipality codes defined for the postal code areas. The statistical data contain data on the population structure, the degree of education, the income of the inhabitants and households, the size of house-holds and life stage, buildings and dwellings, workplaces, and the main ac-tivities of the inhabitants. The statistical data are also available in the PxWeb database (http://pxnet2.stat.fi/PXWeb/pxweb/en/Postinumeroalueittainen_avoin_tieto/). The data are protected. Protected data are indicated with -1. New data are updated annually in January. The data descriptions can be found in this link: http://tilastokeskus.fi/tup/paavo/paavon_aineistokuvaukset_en.html. The general Terms of Use must be observed when using the data: http://tilastokeskus.fi/org/lainsaadanto/copyright_en.html.

The Plain map series is a simple, plain and readable dataset product series in raster format that depicts the whole of Finland. The product is meant to be used as a background map whose character changes to a guide map in large scales. Impaired vision has been taken into account when designing the product. The key objects presented on the map are roads and railways, road names, buildings and constructions, administrative borders, waterways and other geographical names. The road network, public buildings and texts have been especially emphasised. The most usual limitations of colour vision have been taken into account in the use of colours. 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.

Municipal Division is a dataset depicting the municipal division in the whole of Finland. The Municipal Division dataset is produced in scales 1:10,000, 1:100,000, 1:250,000, 1:1,000,000 and 1:4,500,000. The data included in the dataset in scale 1:10,000 are taken from the cadastral registry. Regarding other scales, municipal boundaries have been generalised to suit the scale in question. The Municipal Division dataset is available as products both in vector and raster format. The products in vector format contain the number codes of the municipalities, the names of the municipalities in both Finnish and in Swedish as well as municipal boundaries and municipal geographical areas. In addition, the vector product includes the corresponding information about the regions, the State Administrative Agencies and the nation as well as a specification of the municipality's area into land and water area in MapInfo and Shape format. Products in raster format include municipal boundaries only. 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 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.