Date (Creation)

2022-06-01T00:00:00

Citation identifier

https://geoservice.dlr.de/catalogue/srv/metadata/7ffa8888-fe28-4f12-b3a1-d08eae6f265e

Presentation form

Digital map

Purpose

The main objective of IceLines is to provide dense time series of calving front change to improve our knowledge on Antarctic glacier and ice shelf front dynamics.

Status

ongoing

Point of contact

Organisation name	Individual name	Electronic mail address	Role
German Aerospace Center (DLR)	Celia Baumhoer	celia.baumhoer@dlr.de	Author

Maintenance and update frequency

As needed

Keywords

• opendata

• IceLines

• Antarctica

• Landcover

• Sentinel-1

• time-series

• yearly

• monthly

• quarterly

• daily

• inspireidentifiziert

GEMET - INSPIRE themes, version 1.0

• Land cover

Place

• regional

Use limitation

Nutzungseinschränkungen: Das DLR ist nicht haftbar für Schäden, die sich aus der Nutzung ergeben. / Use Limitations: DLR not liable for damage resulting from use.

Access constraints

Other restrictions

Other constraints

There are no limitations on public access to spatial data sets and services.

Use constraints

Other restrictions

Other constraints

Nutzungsbedingungen: Lizenz, https://creativecommons.org/licenses/by/4.0 / terms of use: https://creativecommons.org/licenses/by/4.0/

Other constraints

{"id": "cc-by/4.0",

"name": "Creative Commons Namensnennung – 4.0 International (CC BY 4.0)",

"url": " http://dcat-ap.de/def/licenses/cc-by/4.0",

"quelle": "Copyright DLR (year of production)"}

Spatial representation type

Vector

Denominator

80000

Language

English

Character set

UTF8

Topic category

• Environment

Begin date

2014-12-01

Unique resource identifier

EPSG:3031

Topology level

Topology 1D

Geometric object type

Curve

Distribution format

Name	Version
GeoPackage

OnLine resource

Protocol	Linkage	Name
OGC:WMS	https://geoservice.dlr.de/eoc/land/wms?	ICELINES_S1_P1Y
OGC:WMS	https://geoservice.dlr.de/eoc/land/wms?	ICELINES_S1_P1M
OGC:WMS	https://geoservice.dlr.de/eoc/land/wms?	ICELINES_SHELFNAMES
OGC:WMS	https://geoservice.dlr.de/eoc/land/wms?	TDM_POLARDEM_ANT_COASTLINE
OGC:WMS	https://geoservice.dlr.de/eoc/land/wms?	TDM_POLARDEM90_ANT_HSC
OGC:WMS-http-get-capabilities	https://geoservice.dlr.de/eoc/land/wms?SERVICE=WMS%26REQUEST=GetCapabilities
WWW:LINK-1.0-http--link	https://geoservice.dlr.de/web/maps/eoc:icelines	EOC Geoservice map context
WWW:LINK-1.0-http--link	https://download.geoservice.dlr.de/icelines/files/	EOC Download Service
WWW:LINK-1.0-http--link	https://www.dlr.de/eoc/en/desktopdefault.aspx/tabid-18220/29005_read-80071	IceLines - EOC News
WWW:LINK-1.0-http--link	https://play.quickchannel.com/play/kjjjzyu	Video: IceLines – Monitoring von Schelfeisdynamiken in der Antarktis

Hierarchy level

Series

Statement

Created from Sentinel-1 Copernicus data provided by the Alaska Satellite Facility (ASF) https://vertex.daac.asf.alaska.edu/ and the European Space Agency (ESA) https://scihub.copernicus.eu/.

Processing steps include the pre-processing of Sentinel-1 dual and single polarized GRD scenes with the ESA SNAP toolbox. The fronts are extracted with a deep learning approach described in:

Heidler, K., Mou, L., Baumhoer, C., Dietz, A., and Zhu, X. X.: HED-UNet: Combined Segmentation and Edge Detection for Monitoring the Antarctic Coastline, IEEE Trans. Geosci. Remote Sensing, 1–14, https://doi.org/10.1109/TGRS.2021.3064606, 2021.

Baumhoer, C. A., Dietz, A. J., Kneisel, C., and Kuenzer, C.: Automated Extraction of Antarctic Glacier and Ice Shelf Fronts from Sentinel-1 Imagery Using Deep Learning, Remote Sensing, 11, 2529, https://doi.org/10.3390/rs11212529, 2019.

Description

IceLines Processing:

Processing:

Calving front locations are derived from single- and dual-polarized Sentinel-1 EW data which were pre-processed with the ESA SNAP Toolbox 8.0. Front extraction is performed with the deep learning architecture “HED-UNet” and several post-processing steps including elevation thresholding, morphological filtering and vectorization. On average, the true mean distance error for fronts extracted from dual-pol imagery is 210±11 m (5.2 pixel) with 95% confidence and 354±17 m (8.8 pixel) for single-polarized imagery depending on ice shelf front morphology, occurrence of surface melt and calving pattern.

Quality Assurance:

The daily product of IceLines has been validated against 94 manually delineated fronts. For each ice shelf, two manually delineated front positions were created for random dates outside the training data period. On average, the true mean distance error for fronts extracted from dual-pol imagery is 210±11 m (5.2 pixel) with 95% confidence and 354±17 m (8.8 pixel) for single-polarized imagery. Frontal movement along centerlines can be accessed with an accuracy of 85±75 m (2.1 pixel) with 95% confidence.

Metadata

File identifier

7ffa8888-fe28-4f12-b3a1-d08eae6f265e XML

Metadata language

English

Character set

UTF8

Hierarchy level

Series

Hierarchy level name

Dataseries

Date stamp

2023-10-04T14:29:06

Metadata standard name

ISO 19115-1:2014/19139

Metadata author

Organisation name	Individual name	Electronic mail address	Role
German Aerospace Center (DLR)		geoservice@dlr.de	Point of contact