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

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.

Happywhale.com is a resource to help you know whales as individuals, and to benefit conservation science with rich data about individual whales. Original provider: Happywhale Dataset credits: Happywhale and contributorsSupplemental information: Sightings and images were submitted to Happywhale by contributors. A portion of the Happywhale data were transferred to OBIS-SEAMAP upon the agreement between Happywhale and OBIS-SEAMAP. There may be duplicate records among Happywhale datasets and other OBIS-SEAMAP datasets. The precision of date/time vary per record. Some records have date accuracy up to year only. This dataset includes sightings and photos from the following 1 contributors in alphabetic order: Marilia Olio

Happywhale.com is a resource to help you know whales as individuals, and to benefit conservation science with rich data about individual whales. Original provider: Happywhale Dataset credits: Happywhale and contributorsSupplemental information: Sightings and images were submitted to Happywhale by contributors. A portion of the Happywhale data were transferred to OBIS-SEAMAP upon the agreement between Happywhale and OBIS-SEAMAP. There may be duplicate records among Happywhale datasets and other OBIS-SEAMAP datasets. The precision of date/time vary per record. Some records have date accuracy up to year only. This dataset includes sightings and photos from the following 4 contributors in alphabetic order: Amanda Urena; Hondius; MS Otto Sverdrup; Theo Vickers

Happywhale.com is a resource to help you know whales as individuals, and to benefit conservation science with rich data about individual whales. Original provider: Happywhale Dataset credits: Happywhale and contributors Supplemental information: Sightings and images were submitted to Happywhale by contributors. A portion of the Happywhale data were transferred to OBIS-SEAMAP upon the agreement between Happywhale and OBIS-SEAMAP. There may be duplicate records among Happywhale datasets and other OBIS-SEAMAP datasets. The precision of date/time vary per record. Some records have date accuracy up to year only. This dataset includes sightings and photos from the following 2 contributors in alphabetic order: Marilia Olio; Sabine+Ulf

Abstract: Happywhale.com is a resource to help you know whales as individuals, and to benefit conservation science with rich data about individual whales. Original provider: Happywhale Dataset credits: Happywhale and contributors Supplemental information: Sightings and images were submitted to Happywhale by contributors. A portion of the Happywhale data were transferred to OBIS-SEAMAP upon the agreement between Happywhale and OBIS-SEAMAP. There may be duplicate records among Happywhale datasets and other OBIS-SEAMAP datasets. The precision of date/time vary per record. Some records have date accuracy up to year only. This dataset includes sightings and photos from the following 50 contributors in alphabetic order: Adelie Xiaohang Li; Adrian Boyle; Alex Cowan; Andrew Emmerson; Ann; Annette Bombosch; Barbara Messner; Bart Van Gelder; Cees Tineke; Christian Engelke; Conor Ryan; Doug Cheeseman; Doug Gould; Elke; Greta Henderson; Hadleigh Measham; Hannah Brightley; Hans Verdaat; Heidi Krajewsky; Hondius; Jamie Coleman; Jeff Higgott; Jeff Reynolds; Jérôme JACOB; Joel Moore; Joy van der Beek; Katharina Stoll; Keely Crowder; Kerstin Langenberger; Léa Zinsli; Loes de Heus; Marian Herz; Marijke Nita de Boer; Marilia Olio; Marit Pedersen; Mary Want; Menno Schaefer; Nacho Oria; Olivier Blaud; Petra Glardon; Philip Stone; Philip van Dueren; Phil Schultz; Pippa Low; Rémi Bigonneau; Sara Jenner; Sophie Ballagh; Steffo Polar; Tobias Brehm; Ulf Velander

The total productivity (TPROD), one of the Vegetation Phenology and Productivity (VPP) parameters, is a product of the pan-European High Resolution Vegetation Phenology and Productivity (MR-VPP) component of the Copernicus Land Monitoring Service (CLMS). The TPROD, or large integral, is the growing season integral computed as the sum of all daily Plant Phenology Index values between the dates of the season start (SOSD) and end (EOSD). 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 daily inputs, are first used in a function fitting to derive the PPI Seasonal Trajectories. 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 TPROD is one of the 13 parameters. The TPROD time series dataset is made available as raster files with 500x 500m resolution, in ETRS89-LAEA projection corresponding to the MCD43 tiling grid.

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.

EMODnet Physics - Arctic Sea Ice Extend [2009 - ongoing] - Annual Max and Min contours. This product uses the Copernicus Marine Service product id. SEAICE_GLO_SEAICE_L4_NRT_OBSERVATIONS_011_001

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.