IACS test

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 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): https://www.maanmittauslaitos.fi/laserkeilaus-ja-ilmakuvaus. For the time being, it is available only from certain parts of Finland. The product belongs to the open data of the National Land Survey of Finland. More information (in Finnish): https://www.maanmittauslaitos.fi/laserkeilausaineistot.

The data includes traffic volumes in Finland from 2012 to 2023. Data contains traffic volumes of all traffic and truck traffic.

KUVAUS: Karttataso sisältää sekajätteen keräysalueet, jotka tulevat voimaan kuudessa vaiheessa 31.12.2029 mennessä, sekä nykyisen voimassa olevan sekajätteen keräysalueen. PÄIVITYS: Satunnainen (vain tarvittaessa). YLLÄPITOSOVELLUS: Tampereen kaupungin tiedostopalvelin ja PostGIS-tietokanta KOORDINAATTIJÄRJESTELMÄ: Aineisto tallennetaan ETRS-GK24FIN (EPSG:3878) tasokoordinaattijärjestelmässä GEOMETRIA: vektori (alue) SAATAVUUS: Aineisto on tallennettu Postgis-tietokantaan. JULKISUUS: Aineisto on nähtävillä julkisesti kaikille käyttäjille Oskari-karttapalvelussa. TIETOSUOJA: Aineistoon ei liity tietosuojakysymyksiä. AINEISTOSTA VASTAAVA TAHO: Tampereen kaupunki, Alueellinen jätehuoltolautakunta, jatehuoltolautakunta@tampere.fi

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 project partnership consists mainly of the marine departments of the geological surveys of Europe (through the Association of European Geological Surveys-EuroGeoSurveys), which 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), the Caspian Sea and the Caribbean Sea. EMODnet seabed substrate data products include datasets at 1:1 000 000, 1:250 000, 1:100 000 and high-resolution scales (1:1 500, 1:5 000, 1:10 000, 1:15 000, 1:20 000, 1:25 000, 1:30 000, 1:45 000, 1: 50 000, 1:60 000, 1:70 000). 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. The datasets have been compiled at different scales from background information that depends on the original producer. In cases, the data has been generalized into a target scales. Coarser scale data (1M, 250k and 100k) describes the seabed substrate at a general level only and is not suitable for a detailed analysis. High-resolution material includes multiple scales from 1:1 500 to 1:70 000 and the user should assess its suitability for the intended purpose. The smallest cartographic unit within the data is about 4 km2 at 1:1M, 0,3km2 at 1:250k and 0,05km2 at 1:100k scale. Further information about the EMODnet Geology project is available on the centralized EMODnet portal https://emodnet.ec.europa.eu/en/geology.

The Finnish Food Authority - INSPIRE WMS is a WMS interface service that provides access to land cover and land use map layers. The service is based on data from the Integrated Aid Control and Management System (IACS) and the Land Parcel Information System (LPIS). The data are managed by the Food Authority. The service is free of charge and does not require authentication.

KUVAUS Herkät vesistöt, joiden rajaus on luotu Viherkertoimen käyttöä varten. Viherkerroinmenetelmä on ekologinen suunnittelutyökalu tonttien viherpinta-alan arviointiin, minkä avulla etsitään vaihtoehtoisia ratkaisutapoja kaupunkivihreän lisäämiseen sekä hulevesien hallintaan. Määritellyillä alueilla huleveden laadulliseen hallintaan on kiinnitettävä erityistä huomiota. Aineisto perustuu hulevesiohjelmassa määritettyihin osavaluma-alueisiin, joiden avulla aineisto on rajattu. Aineisto on päivitetty 12/2023 vastaamaan uuden hulevesiohjelman valuma-alueita. Hulevesiohjelmaan liittyvän aineiston lisäksi rajausta on arvioitu asiantuntijoiden toimesta. KATTAVUUS Koko kaupunki PÄIVITYS Aineisto on laadittu viherkertoimen käyttöön ja päivittyy tiedon tarkentuessa. YLLÄPITOSOVELLUS Aineisto on tallennettu PostgreSQL-tietokantaan ja ylläpidetään QGIS-ympäristössä. KOORDINAATISTOJÄRJESTELMÄ Aineisto tallennetaan ETRS-GK24 (EPSG:3878) tasokoordinaattijärjestelmässä. GEOMETRIA Aluemainen SAATAVUUS Aineisto on saatavilla WFS- ja WMS2-rajapinnoilta. JULKISUUS, TIETOSUOJA. Avoin aineisto. VASTUUTAHO Ympäristönsuojeluyksikkö (ymparistonsuojelu@tampere.fi) KENTÄT vesisto: vesistöalueen nimi

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.