The SIOS Data Management Service (SDMS) integrates information from SIOS partner data repositories into a unified virtual data centre, the SIOS Data Access Portal, allowing users to search for and access data regardless of where they are archived. Providers and users have to commit to the SIOS data policy.
The current focus is on dataset discovery through standardised metadata, and retrieval, visualisation & transformation of data. Ultimately, the Data Management Service works towards integration of datasets which requires a high level of interoperability at the data level.
SDMS currently harvests information on SIOS relevant datasets from a number of data centres (see below), some hosted by SIOS partners and some not. Data centres hosted by SIOS partners work to harmonise access to the data allowing integrated visualisation etc for the relevant datasets.
Data centres SDMS is harvesting information from.
SIOS partner data centres
Other
AWI (DE)
British Antarctic Survey
CNR (IT) - temporarily disabled due to server issues
National Snow and Ice Data Center
IGPAS (PL)
IMR (NO)
IOPAN (PL)
MET (NO) - weather stations have not been updated for a while, update in progress
NERSC (NO)
NILU (NO)
NIPR (JP)
NPI (NO)
UiS (PL)
Citation of data and service
If you use data retrieved through this portal, please acknowledge our funding source: Research Council of Norway, project number 291644, Svalbard Integrated Arctic Earth Observing System – Knowledge Centre, operational phase.
Always remember to cite data when used!
Citation information for individual datasets is often provided in the metadata. However, not all datasets have this information embedded in the discovery metadata. On a general basis a citation of a dataset include the same components as any other citation:
author,
title,
year of publication,
publisher (for data this is often the archive where it is housed),
edition or version,
access information (a URL or persistent identifier, e.g. DOI if provided)
SIOS recommends all partner data repositories to mint Digital Object Identifiers (DOI) on all datasets. The information required to properly cite a dataset is normally provided in the discovery metadata the datasets.
SIOS Core Data
In order to find SIOS Core Data please use the searchable item marked "Collection" on the right hand side of the map and select "SIOSCD". Quick access to SIOS Core Data is provided here.
Nansen Legacy Data
The Nansen Legacy project is using the SIOS Data Management system as the data portal. Quick access to all Nansen Legacy related datasets is available here.
Brief user guide
The Data Access Portal has information in 3 columns. An outline of the content in these columns is provided above. When first entering the search interface, all potential datasets are listed. Datasets are indicated in the map and results tabulation elements which are located in the middle column. The order of results can be modified using the "Sort by" option in the left column. On top of this column is normally relevant guidance information to user presented as collapsible elements.
If the user want to refine the search, this can be done by constraining the bounding box search. This is done in the map - the listing of datasets is automatically updated. Date constraints can be added in the left column. For these to take effect, the user has to push the button marked search. In the left column it is also possible to specific text elements to search for in the datasets. Again pushing the button marked "Search" is necessary for these to take action. Complex search patterns can be constructed using logical operators from the drop down above the text field and prefixing words with '+' to require their presence and '-' to require their non presence.
Other elements indicated in the left and right columns are facet searches, i.e. these are keywords that are found in the datasets and all datasets that contain these specific keywords in the appropriate metadata elements are listed together. Further refinement can be done using full text, date or bounding box constraints. Individuals, organisations and data centres involved in generating or curating the datasets are listed in the facets in the right column.
Institutions: Norwegian Water Resources and Energy Directorate (NVE)
Last metadata update: 2024-03-13T11:33:04Z
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Abstract:
Glacier Periodic photos (GPP) from Norwegian glaciers. The photo series illustrate how the extent of a selection of Norwegian glaciers have changed. The pictures are not taken from the same position each year. The earliest photos are from the 1860s. The majority of the pictures are from the last 20 years. The number of photos per glacier varies. The source of the data is NVEs photo archive, with contributions from NVE collaborators. https://glacier.nve.no/Glacier/viewer/gpp/en/cc/
Institutions: Norwegian Water Resources and Energy Directorate (NVE)
Last metadata update: 2024-03-13T11:33:04Z
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Abstract:
The climate change indicator products of glaciers in mainland Norway include surface mass balance and length change (from NVE’s field observations) and area changes (from satellite imagery and topographical maps) for a selection of glaciers. Glacier surface mass balance and glacier length change are obtained directly from NVE’s databases. https://glacier.nve.no/Glacier/viewer/CI/en/cc
On many glaciers in Svalbard, three surface types are visible on SAR images, the dark glacier ice at the glacier's lower end, the brighter superimposed ice in the middle, and the white firn at the higher elevations. Surface classification of these types is valuable especially since the retreat or advance of the firn area provides information on the status of the glacier. While the snowline reacts immediately to annual changes, the firn area smoothes out these short-term changes and shows, similar to the glacier front, longer-term changes of the glaciers.
Glacier Firn Area Change is based on the "Glacier Surface Type - Svalbard" dataset, presenting the actual area value sper glacier and year as tabular data to be plotted graphically
On many glaciers in Svalbard, three surface types are visible on SAR images, the dark glacier ice at the glacier’s lower end, the brighter superimposed ice in the middle, and the white firn at the higher elevations. Surface classification of these types is valuable especially since the retreat or advance of the firn area provides information on the status of the glacier. While the snowline reacts immediately to annual changes, the firn area smoothes out these short-term changes and shows, similar to the glacier front, longer-term changes of the glaciers.
GST uses a Otsu three-category algorithm to separate the image into these three surface types for selected Svalbard glaciers. The method works very well on glacier with distinct surface types, the main weakness is crevasses and rough areas being classifed as superimposed ice. A quality number indicates if an individual classification is ideal (1), good (2) or of medium quality (3). The quality number mainly indicates how much crevasses are classified as superimposed ice. The firn area should be displayed correctly for all selected glaciers.
Satellite albedo data from MODIS is used to track snow-line on glaciers in Svalbard, with snow-line serving as a proxy for the Equilibrium Line Altitude (ELA). Eventually the results will be available as shapefiles.
A table with snow lines derived with this method is available and snow line can be plotted against time
Method: albedo data and snow line tracking. Sensors: MODIS.
The data set consists of digital elevation models (DEM) of subglacial topography, ice thickness, bathymetry and ice surface elevation of Kongsfjorden, northwestern Svalbard, near Ny-Ålesund (78.9 deg N, 12.4 deg E). The DEMs cover five tide-water glaciers with a grid size of 150 m. The data have a total area of ~1100 km^2 and cover the glaciers Blomstrandbreen, Conwaybreen, Kongsbreen, Kronebreen, and Kongsvegen, including the ice fields Holtedahlfonna and Isachsenfonna. A 50 m resolution DEM is also available for Kronebreen. The compiled data set covers one of the most studied regions in Svalbard and can be valuable for studies of glacier dynamics, geology, hydrology and fjord circulation. For further details see Lindbäck et al. (2018, https://doi.org/10.5194/essd-2018-37).
If you use the data set in presentations and publications please also refer to the peer-reviewed paper (Lindbäck et al., 2018, https://doi.org/10.5194/essd-2018-37). The data set will be updated when the quality of the data is improved or if new data sets become available.
File format: GeoTIFF and ASCII Spatial reference: WGS-1984 UTM Zone 33W
Contact person: Jack Kohler (jack.kohler@npolar.no)
This work was part of the TIGRIF (Tidewater Glacier Retreat Impact on Fjord circulation and ecosystems) project, funded by the Research Council of Norway.
The archipelago of Svalbard presently contains approximately 33,200 km2 of glaciers, with a large number of small valley glaciers as well as large areas of contiguous ice fields and ice caps. While a first glacier inventory was compiled in 1993, there has not been a readily available digital version. Here we present a new digital glacier database, which will be available through the GLIMS project. Glacier outlines have been created for the years 1936, 1966-71, 1990, and 2001-2010. For most glaciers, outlines are available from more than one of these years. A complete coverage of Svalbard is available for the 2001-2010 dataset. Glacier outlines were created using cartographic data from the original Norwegian Polar Institute topographic map series of Svalbard as basis by delineating individual glaciers and ice streams, assigning unique identification codes relating to the hydrological watersheds, digitizing center-lines, and providing a number of attributes for each glacier mask. The 2001-2010 glacier outlines are derived from orthorectified satellite images acquired from the SPOT-5 and ASTER satellite sensors. In areas where coverage for all time periods is available, the overwhelming majority of glaciers are observed to be in sustained retreat over the period from 1936-2010.
This study was conducted in a collaboration between the Department of Geoscience, University of Oslo, and the Norwegian Polar Institute, it was supported by the European Space Agency (ESA) through the projects Glaciers_CCI (4000101778/10/I-AM) and Cryoclim, which is also supported by the Norwegian Space Centre.
Institutions: De Nationale Geologiske Undersøgelser for Danmark og Grønland (GEUS)
Last metadata update: 2022-11-15T12:01:24Z
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Abstract:
The Greenland Surface Type is estimated using satellite remote
sensing techniques on the MODIS insturment. This dataset contains
monthly products covering april to september for the period
2000-2014.
The data files contain 5 layers with the following content: GST,
Nobs, StDev, MaxGST, MinGST.
The monthly products were generated on a machine which uses the
little-endian data format (Intel convention). GST is coded with 2 -
Ocean, 5 - Land, 3 - Cloud, 4 - No data, 11 - Ice, 13 - Melting
snow, 14 - Dry snow.
Further information can be found in
Fausto, R.S., Mayer, C. and Ahlstrøm, A.P. 2007: Satellite-derived
surface type and melt area of the Greenland ice sheet using MODIS
data from 2000 to 2005. Annals of Glaciology 46, 35-42.
Fausto, R.S., Van As, D., Antoft, J.A., Box, J.E., Colgan, W., and
the PROMICE project team. Greenland ice sheet melt area from MODIS
(2000-2014). Geological Survey of Denmark and Greenland Bulletin 33.
Institutions: Norwegian Water Resources and Energy Directorate (NVE)
Last metadata update: 2022-11-15T12:01:24Z
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Abstract:
Glacier Area Outline (GAO) for mainland Norway from the period 1947-1985. Source: First edition N50 maps in the main map series of Norway (denoted M711 or N50) constructed from air photos taken the period 1952-1985. The original paper maps printed at a scale of 1:50 000 were scanned by Statens kartverk and then the maps were georeferenced and digitised by NVE. RMS values of less than 10 meters were obtained using the 1st order polynomial (affine) transformation.
Institutions: Norwegian Water Resources and Energy Directorate (NVE)
Last metadata update: 2022-11-15T12:01:24Z
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Abstract:
Glacier Area Outline (GAO) for western Finnmark from the period 1895-1907. Source:
"Gradteigskart" constructed from land surveys between 1895-1907, three paper maps printed at a scale of 1:100 000 include the five largest ice caps - Normannsjøkelen, Seilandsjøkelen, Øksfjordjøkelen, Svartfjelljøkelen and Langfjordjøkelen. The maps were georeferenced and digitised by NVE. The maps have poorer accuracy compared to N50-maps, and rubber sheeting was needed to do a transformation. The glacier outlines are uncertain and must be taken as a rough estimate due to the poorer quality of these old maps.
Institutions: Norwegian Water Resources and Energy Directorate (NVE)
Last metadata update: 2022-11-15T12:01:24Z
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Abstract:
Glacier Lake Outline (GLO) for Norway from the period 1988-1997. Glacier lakes can cause hazardous outburst floods. GLO is defined as water bodies that either intersected or were within a distance of 50 m of the glacier boundary (GAO). Only locations where glacier lakes were detected in the GLO 1999-2006 were mapped.
Institutions: Norwegian Water Resources and Energy Directorate (NVE)
Last metadata update: 2022-11-15T12:01:24Z
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Abstract:
Glacier Lake Outline (GLO) for Norway from the period 1999-2006. Glacier lakes can cause hazardous outburst floods.
GLO is defined as water bodies that either intersected or were within a distance of 50 m of the glacier boundary (GAO).
Institutions: Norwegian Water Resources and Energy Directorate (NVE)
Last metadata update: 2022-11-15T12:01:24Z
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Abstract:
Glacier Area Outline (GAO) for mainland Norway from the period 1988-1997, using 9 Landsat TM/ETM+ satellite images. For all scenes the horizontal positional accuracy (rmse) was less than one pixel (better than 30 m).