DOI: 10.7280/d1fh5d
title: CALFIN: Calving front dataset for East/West Greenland, 1972-2019

description: We present Calving Front Machine (CALFIN), an automated method for
 extracting calving fronts from satellite images of marine-terminating
 glaciers. The results use Landsat imagery from 1972 to 2019 to generate
 22,678 calving front lines across 66 Greenlandic glaciers. The method uses
 deep learning, and builds on existing work by Mohajerani et al., Zhang et
 al., and Baumhoer et al. Additional post-processing techniques allow for
 accurate segmentation of imagery into Shapefile outputs. This method is
 uniquely robust to the impact of clouds, illumination differences, ice
 mélange, and Landsat-7 Scan Line Corrector errors. CALFIN provides
 improvements on the current state of the art. A model inter-comparison is
 performed to evaluate performance against existing methodologies.
 CALFIN's ability to generalize to SAR imagery is also evaluated.
 CALFIN's fronts are often indistinguishable from manually-curated
 fronts, deviating by 2.25 pixels (86.76 meters) from the true front on a
 diverse set of 162 testing images. The current implementation offers a new
 opportunity to explore sub-seasonal trends on the extent of
 Greenland's margins, and supplies new constraints for simulations of
 the evolution of the mass balance of the Greenland Ice Sheet and its
 contributions to future sea level rise.
description: We collect our source data from Landsat NIR band images spanning
 from 1972 to 2019. We provide 1997 manually-masked calving fronts, which
 we use for training, validating, and testing our automated algorithm. We
 also provide over 17912 automatically generated fronts, along with
 estimated mean errors calculated for each basin. This dataset contains a
 total of 19909 calving fronts for Helheim, Kangerlussuaq, Kong Oscar,
 Hayes, Rink Isbrae, Upernavik, Jakobshavn, Petermann, Kangiata Nunaata,
 and 62 other nearby glaciers along East/West Greenland.
 We process our source data by utilizing deep learning, in the
 form of the Google DeeplabV3+ Xception derived CALFIN Neural Network.
 Additional post-processing techniques allow our method to achieve accurate
 and useful segmentation of raw Landsat subsets into Shapefile
 outputs. 
description: We provide two levels of data products.  
 Level 0 products consist of fjord boundary GeoTiff
 masks, the domain Shapefiles used for subsetting, a glacier names
 reference Shapefile, and the Landsat scene name ID
 lists. Level 1 product consists of a
 LineString Shapefile with 22678 features, and a Polygon Shapefile with
 17771 features, grouped by glacial basin. Polygons are ocean masks that
 are constructed from merged calving front Line Strings, fjord boundaries,
 and domain boundaries. Both Shapefiles share a
 feature schema derived from the MEaSUREs glacial
 terminus positions dataset (NSIDC-0642), as detailed in Table
 S2: Properties Spatial extent:
 66 Greenlandic glacial basins, including Petermann, Upernavik, Rink
 Isbrae, Jakobshavn, Helheim, Kangerlussuaq, Kangiata Nunaata, Kong Oscar,
 Hayes, and other nearby basins (See External Spatial Figure) Time Series: Sept. 1972 - June 2019 (See External Temporal Figure) Temporal resolution: sub-seasonal Spatial resolution: 30 meters Spatial accuracy: &lt;90 meters Projection: EPSG:3413 (WGS 84 / NSIDC Sea Ice Polar Stereographic North) Usage Example: (See External Usage Figure) Shapefile Feature Schema Attribute Table Data Field Description Format (Values) GlacierID Numerical ID assigned to each glacier (as derived from MEaSUREs NSIDC-0642) # ([1, 246]) Center_X Mean X coordinate in EPSG:3413. # ([-463626, 682313]) Center_Y Mean Y coordinate in EPSG:3413. # ([-2821269, -906747]) Latitude Latitude of center. # ([64.29, 81.24]) Longitude Longitude of center. # ([-63.17, -28.21]) QualFlag Quality flag to indicate digitization conditions # (0 - Manually digitized, 3 - Manually digitized, w/ L7 SCE, 10 - Automatically digitized, 13 - Automatically digitized, w/ L7 SCE. See MEaSUREs NSIDC-0642) Satellite Satellite/sensor of the digitized source image LXSS ([LM01, LC08]) See usgs.gov/faqs/what-naming-convention-landsat-<br> collections-level-1-scenes Date Date of the digitized source image YYYY-MM-DD ([1972-09-06, 2019-06-25]) ImageID Source image file name. LXSS_LLLL_PPPRRR_YYYYMMDD_yyyymmdd_CC_TX<br> (LC08_L1TP_026006_20170702_20170715_01_T1, etc.) GrnlndcN Greenlandic glacier name NAME (New_Greenl names from Bjørk et al., 2015 database of Greenland glacier names) OfficialN Officially recognized glacier name NAME (Official_n names from Bjørk et al., 2015 database of Greenland glacier names) AltName Alternative, Foreign, Old Greenlandic, or<br> other glacier names NAME (Foreign_na, Old_Greenl, Alternative names (Bjørk et al., 2015), or other names) RefName Reference glacier name, non-authoritative<br> names used in CALFIN to denote<br> grouped/unnamed glaciers NAME (New_Greenl, Official_n, Foreign_na, Old_Greenl, Alternative names (Bjørk et al.,<br> 2015), or other names) Author Digitization author’s name LastName_FirstInitial (Cheng_D) level-1_shapefiles-greenland-termini.zip LineString Shapefiles from 1972-2019, containing all features in one file level-1_shapefiles-greenland-termini-closed.zip Polygon Shapefiles from 1972-2019, containing all features in one file level-1_shapefiles-domain-termini.zip LineString Shapefiles from 1972-2019, separated by glacial domain level-1_shapefiles-domain-termini-closed.zip Polygon Shapefiles from 1972-2019, separated by glacial domain. Reference for MEaSUREs glacial terminus positions dataset: Joughin, I., T. Moon, J. Joughin, and T. Black. 2015, 2017. MEaSUREs Annual Greenland Outlet Glacier Terminus Positions from SAR Mosaics, Version 1. [NSIDC-0642]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: https://doi.org/10.5067/DC0MLBOCL3EL.