Description:

Snow, glaciers and permafrost in cold mountain areas such as the Swiss Alps are especially sensitive to changes in environmental conditions due to their proximity to melting conditions. In addition, mass wasting is most intensive in those mountain areas with high relief energy. Environmental changes in high mountain regions substantially influence the potential for glacial and periglacial hazards. Ice- and moraine-dammed lakes represent a widespread hazard potential closely related to glacier fluctuations. Magnitude and frequency of ice avalanches from steep glaciers - in principle a normal expression of mass exchange under such topographic conditions - are coupled with stability conditions affected by glacier advance/retreat and, hence, with long-term atmospheric impacts. Steep and unstable reservoirs of loose debris, a potential source of debris flows, are often the result of glacier shrinkage. In a similar way, changes in the stress regime due to vanishing glaciers lead to potential destabilization of adjacent valley flanks. Since the Alps are among the most densely populated high mountain areas in the world, Switzerland is particularly impacted by glacial and periglacial hazards but, on the other hand, also has an extensive and well-recognized tradition in investigating such processes. A number of specific monitoring and modeling studies related to single hazardous situations have been performed, mainly based on recent catastrophes or imminent hazard situations. An urgent need exists for area-wide modeling of glacier hazard potentials with a view to establishing an integrated and adequate information base for planning and detailed monitoring, but a corresponding systematic approach is, for the present, still lacking. The proposed project aims at closing this gap in several ways: Work Package (WP) (1): By developing techniques for detection of glacier hazard potentials based on optical spaceborne remote sensing data which rarely has been used to date in Swiss glacier monitoring; multispectral analyses and multitemporal and multiscale fusion will play a major role in this, with a special focus on recent or upcoming high resolution sensors. WP (2): By integrating empirical models for glacier hazard assessment into geographical information systems (GIS) which have proven to be successful for hazard simulation but have not been used yet for determining glacier hazard potentials; GIS modeling especially allows for the fusion of remote sensing and elevation data for spatial (3D) analyses. To ensure high synergy, WPs (1) and (2) will be closely related to the ongoing SNF project "The Swiss Glacier Inventory 2000" (SWI 2000) (no. 21-54073.98) and the international project "Global Land Ice Monitoring from Space" (GLIMS). WP (3): By applying the methods from WPs (1) and (2), an initial attempt will be undertaken to implement an area-wide model for integrating glacier hazard potentials of extensive regions in the Swiss Alps following a downscaling strategy with varying resolution and accuracy levels, both with respect to data and to models. As hazard management in Switzerland is the domain of local and regional authorities, the proposed project does not aim at preparing detailed local hazard maps (Gefahrenkarten), but rather will provide new remote sensing and modeling techniques for decision support. It should demonstrate the usefulness of these techniques for overview mapping (Gefahrenhinweiskarten) as a basis for decision-making and for scenario simulations in connection with climate change effects. The efforts made in this project will contribute to handle economically complex mathematical and physical models and represent a decision basis for the specific need of further detailed case studies. A further outcome will be a documentation of historical glacier catastrophes in the Swiss Alps, which will - among others - be used for model calibration and verification. [Summary provided by Christian Huggel, University of Zurich.]

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• UNIZH_AGREG

Temporal Extent:

Start: 1970-01-01T00:00:00.000Z

Spatial Extent:

Minimum Bounding Rectangle: -90 -180 90 180

SCIOPS Short Name: UNIZH_AGREG Version ID: Not provided Unique ID: C1214614963-SCIOPS

Description:

This data set contains shapefiles of termini traces from 294 Greenland glaciers, derived using a deep learning algorithm (AutoTerm) applied to satellite imagery. The model functions as a pipeline, imputing publicly availably satellite imagery from Google Earth Engine (GEE) and outputting shapefiles of glacial termini positions for each image. Also available are supplementary data, including temporal coverage of termini traces, time series data of termini variations, and updated land, ocean, and ice masks derived from the <a href="https://nsidc.org/data/nsidc-0714/versions/1">Greenland Ice Sheet Mapping Project (GrIMP) ice masks</a>.

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Temporal Extent:

Start: 1972-01-01T00:00:00.000Z

End: 2022-01-01T23:59:59.999Z

Spatial Extent:

Minimum Bounding Rectangle: 57 -75 85 -8

NSIDCV0 Short Name: NSIDC-0788 Version ID: 1 Unique ID: C2849438379-NSIDCV0

Description:

The BigFoot project gathered data for nine EOS Land Validation Sites located from Alaska to Brazil from 2000 to 2003. Each site is representative of one or two distinct biomes, including the Arctic tundra; boreal evergreen needleleaf forest; temperate cropland, grassland, evergreen needleleaf forest, and deciduous broadleaf forest; desert grassland and shrubland; and tropical evergreen broadleaf forest. These surfaces were produced from Landsat ETM+ imagery to explicitly characterize the land cover at the BigFoot Sites to provide validation of the MODIS land cover product. BigFoot was funded by NASA's Terrestrial Ecology Program.

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Temporal Extent:

Start: 2000-01-01T00:00:00.000Z

End: 2003-12-31T23:59:59.000Z

Spatial Extent:

Minimum Bounding Rectangle: -2.86 -156.61 71.27 -54.96

ORNL_CLOUD Short Name: Land_Cover_surfaces_748 Version ID: 1 Unique ID: C2751481308-ORNL_CLOUD

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Description:

This data set contains shapefiles of Greenland’s glacial termini and basins for the years 1972 to 2019. These vector data were created from Landsat 1-8 satellite imagery using the Calving Front Machine (CALFIN) an automated processing workflow utilizing neural networks for extracting calving fronts from satellite images of marine-terminating glaciers.

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Temporal Extent:

Start: 1972-09-06T00:00:00.000Z

End: 2019-06-25T23:59:59.999Z

Spatial Extent:

Minimum Bounding Rectangle: 60 -75 80 -15

NSIDC_ECS Short Name: NSIDC-0764 Version ID: 1 Unique ID: C2116307977-NSIDC_ECS

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Description:

On the background of these requirements for sensor calibration, intercalibration and product validation, the subgroup on Calibration and Validation of the Committee on Earth Observing System (CEOS) formulated the following recommendation during the plenary session held in China at the end of 2004, with the goal of setting-up and operating an internet based system to provide sensor data, protocols and guidelines for these purposes: Background: Reference Datasets are required to support the understanding of climate change and quality assure operational services by Earth Observing satellites. The data from different sensors and the resulting synergistic data products require a high level of accuracy that can only be obtained through continuous traceable calibration and validation activities. Requirement: Initiate an activity to document a reference methodology to predict Top of Atmosphere (TOA) radiance for which currently flying and planned wide swath sensors can be intercompared, i.e. define a standard for traceability. Also create and maintain a fully accessible web page containing, on an instrument basis, links to all instrument characteristics needed for intercomparisons as specified above, ideally in a common format. In addition, create and maintain a database (e.g. SADE) of instrument data for specific vicarious calibration sites, including site characteristics, in a common format. Each agency is responsible for providing data for their instruments in this common format. Recommendation : The required activities described above should be supported for an implementation period of two years and a maintenance period over two subsequent years. The CEOS should encourage a member agency to accept the lead role in supporting this activity. CEOS should request all member agencies to support this activity by providing appropriate information and data in a timely manner. Pseudo-Invariant Calibration Sites (PICS): Algeria 5 is one of six CEOS reference Pseudo-Invariant Calibration Sites (PICS) that are CEOS Reference Test Sites. Besides the nominally good site characteristics (temporal stability, uniformity, homogeneity, etc.), these six PICS were selected by also taking into account their heritage and the large number of datasets from multiple instruments that already existed in the EO archives and the long history of characterization performed over these sites. The PICS have high reflectance and are usually made up of sand dunes with climatologically low aerosol loading and practically no vegetation. Consequently, these PICS can be used to evaluate the long-term stability of instrument and facilitate inter-comparison of multiple instruments.

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Temporal Extent:

Start: 1972-08-15T00:00:00.000Z

Spatial Extent:

Minimum Bounding Rectangle: 29.24 -1.32 32.79 4.24

USGS_LTA Short Name: CEOS_CalVal_Test_Sites-Algeria5 Version ID: Not provided Unique ID: C1220567104-USGS_LTA