Abstract:
This dataset contains floe-scale fragmentation data derived from high-resolution satellite imagery from the USGS Global Fiducials Library. Individual sea ice floes were identified and tracked before and after fragmentation to study the fragmentation processes. The dataset includes floe-scale images, segmentation masks, and floe parameters. It can be used to investigate the fragmentation of Arctic sea ice during the spring breakup and summer melt seasons. The dataset was produced by the University of Huddersfield team.
NERC standard grant NE/V011693/1.
Keywords:
Arctic, cracks, floe-scale, fragmentation, leads, melt, melt ponds, sea ice, spring breakup
Hwang, B., & Basu, R. (2025). Floe-scale Fragmentation of Arctic Sea Ice 2013-2014 (Version 1.0) [Data set]. NERC EDS UK Polar Data Centre. https://doi.org/10.5285/17eeb01b-179e-4285-8619-734f390452ac
| Access Constraints: | Under embargo until publication of associated article. |
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| Use Constraints: | Data supplied under Open Government Licence v3.0 http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/. |
| Creation Date: | 2025-04-15 |
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| Dataset Progress: | Complete |
| Dataset Language: | English |
| ISO Topic Categories: |
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| Parameters: |
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| Personnel: | |
| Name | UK Polar Data Centre |
| Role(s) | Metadata Author |
| Organisation | British Antarctic Survey |
| Name | Byongjun Hwang |
| Role(s) | Investigator, Technical Contact |
| Organisation | University of Huddersfield |
| Name | Rajlaxmi Basu |
| Role(s) | Investigator |
| Organisation | University of Huddersfield |
| Parent Dataset: | N/A |
| Quality: | The data quality was checked by manually inspecting each image. It should be noted that some of the fragments in the post-fragmentation images could not be identified. Some were too small, while others were difficult to distinguish based on floe and melt pond patterns. The delineation of the floe boundaries was performed using the OpenCV tool (CVAT AI). The delineation was relatively accurate for large floes, but the accuracy decreased for smaller floes. | |
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| Lineage/Methodology: | The floe-scale fragmentation data were derived from high-resolution satellite imagery provided by the USGS Global Fiducials Library (GFL). The original images were cropped to the individual floe scale so that each floe could be clearly identified. These GFL images were acquired by tracking drifting buoys, allowing us to identify the same floe across a sequence of images. In this way, we could observe the floe before and after the fragmentation event. Identifying the same floe was done manually by searching through the images based on floe and melt pond patterns. Once the floe-scale images were created, we used OpenCV drawing tool in CVAT AI (www.cvat.ai) to delineate the boundaries of the floes. The results were exported as segmentation masks, which were analysed by a MATLAB code to calculate floe parameters including the size, area, perimeter, shape factor and circularity of the floes. The data are organised according to the buoys that the images were tracking - IABP123530, MIZ Cluster 3, MIZ Cluster 4, and MIZ Cluster 2. IABP123530 is the buoy ID used in the USGS GFL data portal. This corresponds to IABP Buoy ID 300025010123530 on the IABP website. This buoy is co-located with CRREL IMB ID 2012L. MIZ Cluster 3 is the second northernmost cluster of drifting buoys deployed during the ONR MIZ program. The co-located buoys are WHOI ITP (ID: ITP78), AWS 3, and IMB 4 (see ONR MIZ website). MIZ Cluster 4 is the northernmost cluster of drifting buoys deployed during the ONR MIZ program. The co-located buoys are WHOI ITP (ID: ITP79), AWS 4, and IMB 9 (see ONR MIZ website). MIZ Cluster 2 is the second southernmost cluster of drifting buoys deployed during the ONR MIZ program. The co-located buoys are WHOI ITP (ID: ITP77), AWS 2, and IMB 17 (see ONR MIZ website). The spatial coverage of the dataset covers the Beaufort Sea. Latitude and longitude coordinates for each floe are provided in CSV files in the floe_parameter folder. |
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| Temporal Coverage: | |
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| Start Date | 2013-06-01 |
| End Date | 2014-08-14 |
| Spatial Coverage: | |
| Latitude | |
| Southernmost | 73.88772 |
| Northernmost | 75.0952 |
| Longitude | |
| Westernmost | -153.4876 |
| Easternmost | -136.3707 |
| Altitude | |
| Min Altitude | N/A |
| Max Altitude | N/A |
| Depth | |
| Min Depth | N/A |
| Max Depth | N/A |
| Data Resolution: | |
| Latitude Resolution | N/A |
| Longitude Resolution | N/A |
| Horizontal Resolution Range | 1 meter - < 30 meters |
| Vertical Resolution | N/A |
| Vertical Resolution Range | N/A |
| Temporal Resolution | N/A |
| Temporal Resolution Range | N/A |
| Location: | |
| Location | Arctic |
| Detailed Location | Beaufort Sea, Arctic Ocean |
| Data Collection: | Characteristics of satellite imagery data used to derive the FSD data are described below. USGS GGFL: 1-m resolution visible (panchromatic) satellite imagery from the USGS Global Fiducials Library (GFL) (www.glf.usgs.gov), declassified by the MEDEA group. |
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| Distribution: | |
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| Distribution Media | Online Internet (HTTP) |
| Distribution Size | 81 MB |
| Distribution Format | N/A |
| Fees | N/A |
| Data Storage: | The dataset is organised in four folders - IA1, MC3, MC4, and MC2. Each folder represents the tracking buoys. Within each folder the subfolders contains image files in Tiff and PNG format, and floe parameters and locations in Comma Separated Value (CSV) format. Folder structure The dataset contains four main folders, each representing a tracking buoy. The data in the IA1 and MC3 folders represent the spring fragmentation process, covering the period from late May to early June. In contrast, the data in the MC4 and MC2 folders represent cases of summer melt-related fragmentation, covering early to mid-August. In each folder, the data are organised into three subfolders: floe_image, floe_parameter, and segmentation_mask. The floe_image folder contains image files cropped to the individual floe scale. The segmentation_mask folder contains mask images generated using the OpenCV drawing tool in CVAT AI. These files include mask images for all fragments as well as for each individual fragment (see Naming convention for more information). The floe_parameter folder contains the parameters calculated for each floe and fragment, both before and after fragmentation (see Naming convention for more information). Naming convention The naming convention for the floe_image files uses the first letters to represent the tracking buoy, such as IA1, MC3, MC4, or MC2, followed by two letters representing the floe number, such as F1, F2, or F3. The letter a or b at the end indicates whether the image was taken before (a) or after (b) fragmentation. See an example below. The naming convention for the segmentation_mask files follows the same pattern for pre-fragmentation floe masks but adds a few notations for post-fragmentation floe masks. There are two types of post-fragmentation floe masks. The first type is the floe mask that contains all fragments in one image. For that file, the letter b0 represents all fragments with a background value of 0. See the example below. The second type is the floe masks that contain individual fragments. For those files, the number after b at the end represent fragment id. See an example below. The data within the folder floe_parameter contains the parameters that were calculated for each floe or fragment using the MATLAB code. The parameters are shown below. Date yyyy.mm.dd The day that the image was taken Floe size Metres Mean calliper diameter of the floes Floe area Square metres Area of the floes Floe perimeter Metres Perimeter of the floes Shape factor Unitless Ratio of the major axis to the minor axis of the floes (major axis / minor axis) Circularity Unitless The maximum circularity is 1. (4*Floe area/Perimeter2)*(1 - 0.5/r)2, where r = Perimeter/(2pi) + 0.5 Floe size, area, perimeter, major/minor axes and circularity were calculated using regionprops function within Blob analysis in MATLAB. |