Notagildi: Reitakerfi eru nauðsynlegt til að birta upplýsingar sem af einhverjum ástæðum er ekki hægt að birta stakar s.s. vegna persónuverndar, umfangs verkefnis eða nákvæmni þeirra upplýsinga sem fyrir liggja. Reitakerfi Íslands er með mismunandi reitastærðum til að mæta mismunandi þörfum notenda við upplýsingamiðlun. Mælt er með notkun reitakerfisins m.a. þegar verið er að bera gögn saman milli stofnana. Reitakerfið er byggt á Lambert Azimuthal Equal Area vörpun sem tryggir að allir reitir sé jafn stórir. En það er helsta skilyrði þess að reitakerfið sé Inspire tækt. Viðmiðun er ISN 2004 Ef reitakerfið er notað í einhverjum af ISN Lambert vörpunum er það ferhyrnt. Orðskýringar: Heildarkerfið er nefnt reitakerfi. Hvert lag í því er nefnt net. Einingar í netinu eru nefndar reitir. Heiti reitana: Hver reitur hefur nafn sem er einkvæmt og er m.a. byggt upp á stærðareiningunni. 1km 10km og 100m skrárnar ná yfir strandlínu og eyjar landsins en 100km skráin nær yfir alla efnahagslögsöguna. grid_100k grid_50k grid_25k grid_10k grid_5k grid_2_5k grid_1k grid_500m grid_250m grid_100m Frekari tækniupplýsingar er að finna hér https://inspire.ec.europa.eu/id/document/tg/gg

Vegagerðin rekur umferðarteljara víða um land sem telja ökutæki samfellt alla daga ársins og upplýsingar frá meira en helmingi þeirra berast sjálfvirkt til Vegagerðarinnar og eru þær upplýsingar aðgengilegar í þessari þjónustu. Umferðargreinar mæla fjölda ökutækja en auk þess mæla þeir t.d. hraða ökutækja. Aðrir umferðarteljarar skrá eingöngu fjölda ökutækja. Slíkir teljarar eru tengdir flestum veðurstöðvum auk nokkurra sem standa sér. Upplýsingar úr umferðargreinum og umferðarteljurum sem eru tengdir veðurstöðvum eru sóttar að jafnaði nokkrum sinnum á klukkustund, en upplýsingar frá teljurum sem ekki eru tengdir veðurstöðvum, berast Vegagerðinni sjaldnar.

Skoðunarþjónustur Veðurstofu Íslands.

The Start-of-Season Date (SOSD), one of the Vegetation Phenology and Productivity (VPP) parameters, is a product of the pan-European High Resolution Vegetation Phenology and Productivity (HR-VPP) component of the Copernicus Land Monitoring Service (CLMS). The Start-of-Season Date (SOSD) marks the date when the vegetation growing season starts in the time profile of the Plant Phenology Index (PPI). The start-of-season occurs, by definition, when the PPI value reaches 25% of the season amplitude during the green-up period. The Plant Phenology Index (PPI) is a physically based vegetation index, developed for improving the monitoring of the vegetation growth cycle. The PPI index values, with 5-day satellite revisit cycle, are first used in a function fitting to derive the PPI Seasonal Trajectories, which is a filtered time series with regular 10-day time step. From these Seasonal Trajectories, a suite of 13 Vegetation Phenology and Productivity (VPP) parameters are then computed and provided, for up to two seasons each year. The Start-of-Season Date is one of the 13 parameters. The full list is available in the table 3 of the Product User Manual in the below link section. A complementary quality indicator (QFLAG) provides a confidence level, that is described in table 4 of the same manual. The SOSD dataset is made available as raster files with 10 x 10m and 100 x 100m resolutions, in ETRS89-LAEA projection corresponding to the HRL grid, for those tiles that cover the EEA38 countries and the United Kingdom and for two seasons in each year from 2017 onwards. It is updated in the first quarter of each year.

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This metadata refers to the Plant Phenology Index (PPI) Seasonal Trajectories, is one of the products of the pan-European High Resolution Vegetation Phenology and Productivity (HR-VPP) component of the Copernicus Land Monitoring Service (CLMS). The Plant Phenology Index (PPI) is a physically based vegetation index for improved monitoring of plant phenology, that is developed from a simplified solution to the radiative transfer equation by Jin and Eklundh (2014) and that has a linear relationship with green leaf area index. The PPI Seasonal Trajectories (ST) product is derived from a TIMESAT-based function fitting of the time series of the PPI vegetation index and thus provides a filtered time series of Plant Phenology Index (PPI), with regular 10-day time step. The PPI dataset is made available as raster files with 10 x 10m resolution and 100 x 100m resolutions, in ETRS89-LAEA projection corresponding to the HRL grid, for those tiles that cover the EEA38 countries and the United Kingdom and for two seasons in each year from 2017 onwards. It is updated in the first quarter of each year. Each file has an associated quality indicator (QFLAG) that provides a confidence level.

This metadata refers to the Copernicus Building Height 2012 third version. The dataset is a 10m high resolution raster layer containing height information generated for selected cities and urban areas in the EEA38 member countries and United Kingdom as part of the Urban atlas suite of products. Height information is based on satellite data and derived datasets like the digital surface model (DSM), the digital terrain model (DTM) and the normalized DSM. The satellite data sources are IRS-P5 stereo images for the capital cities and VHR false stereo pairs extracted from the MAXAR catalogue (WV-01, WV-02, GE-01 and IK) for the remaining areas supplemented by LiDAR data as additional option.

The GEBCO_2022 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. In regions outside of the Arctic Ocean area, the grid uses as a base Version 2.4 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2022 Grid represents all data within the 2022 compilation. The compilation of the GEBCO_2022 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base using a remove-restore blending procedure. This is a two-stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2022 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA.

This metadata refer to the 'Corine Land Cover plus Backbone' (CLCplus Backbone) which is a spatially detailed, large scale, Earth Observation-based land cover inventory. The CLCplus Backbone Raster Product is a 10m pixel-based land cover map based on Sentinel satellite time series from July 2017 to June 2019. For each pixel it shows the dominant land cover among the 11 basic land cover classes. The product has a three years update cycle and is available for the 2018 reference year.