Dataset
ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Machine Learning Generated Greenland Calving Front Locations v1.0
Abstract
Calving Front locations for Upernavik A,E,F, Humboldt and Hagen glaciers in Greenland, generated by a deep learning based model using Sentinel-2 imagery.
The calving front location is generated by a deep learning based model using Sentinel-2 imagery acquired from 2019-2020. The digitized calving fronts are stored in geoJSON vector file format and include metadata information on the sensor and processing steps in the corresponding attribute table.
The CCI Calving Front Locations (CFL) v1.0 release contains one primary dataset, the calving front locations, and auxiliary files to describe the file product: locations.png and glaciers.geojson for visualizing the glaciers, README and DESCRIPTION text files about the product structure, and a visual example of what a calving front looks like. The Greenland CCI Calving Front Locations (CFL) v1.0 product is an experimental product using deep learning to automatically derive calving front locations for selected glaciers based on Sentinel-2 imagery at the end of the summer season.
The product was generated by S[&]T Norway and ENVEO.
Details
| Previous Info: |
No news update for this record
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| Previously used record identifiers: |
No related previous identifiers.
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| Access rules: |
Public data: access to these data is available to both registered and non-registered users.
Use of these data is covered by the following licence(s): https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_icesheets_greenland_terms_and_conditions.pdf When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record. |
| Data lineage: |
Data were produced by ENVEO (Environmental Earth Observation Information Technology GmbH) as part of the ESA CCI Greenland Ice Sheet project and were supplied to CEDA in the context of the ESA CCI Open Data Portal Project. Data are produced within ESA Greenland CCI, stored at http://products.esa-icesheets-cci.org/ |
| Data Quality: |
As provided by the CCI Greenland Ice Sheets team
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| File Format: |
txt, geojson, png
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Process overview
| Title | Machine Learning Calving Front locations derived by the ESA Greenland Ice Sheets Climate Change Initiative project. |
| Abstract | The CFL product is generated by a deep learning-based model using optical satellite imagery (Sentinel-2). The digitized calving front is stored as vector lines in standard GeoJSON files. Additionally, metadata information on the sensor and processing steps are stored in corresponding attributes in the GeoJSON files. GeoJSON is an open standard format designed for representing simple geographical features (points, line strings, polygons, and collections), along with their non-spatial attributes. |
| Input Description | None |
| Output Description | None |
| Software Reference | None |
No variables found.
Temporal Range
2019-08-02T15:58:29
2020-08-15T18:09:19
Geographic Extent
90.0000° |
||
-80.0000° |
-10.0000° |
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60.0000° |