Chen, Dong; Farrell, Sinead L; Duncan, Kyle; Eun, Jaemin (2024): University of Maryland classified LVIS georeferenced imagery of Arctic summer sea ice, version 1 [dataset]. PANGAEA, https://doi.pangaea.de/10.1594/PANGAEA.972753 (DOI registration in progress)
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Abstract:
This data collection encompasses 1,387 classified LVIS georeferenced images, which include four classes: Ice, Melt Pond, Open Water, and Shadow. The original LVIS images were acquired in July 2022 using a PhaseOne medium-format camera during the ICESat-2 2022 Arctic Summer calibration campaign, with spatial resolution ranging between 0.39 m and 0.5 m. An image screening was conducted prior to the image classification to remove cloudy images from the collection. The image classification was based on the Random Forest algorithm. An accuracy assessment using 20 randomly selected classified images indicated that the classified imagery has an overall accuracy of more than 85%. The classified images can be used for tracking sea ice dynamics over time and for providing reference for the interpretation of altimetry data.
References:
Blair, Bryan; Hofton, Michelle A; Kurtz, N; Harbeck, J (2023): ICESat-2 Calibration/Validation LVIS L1B Georeferenced Imagery, Version 1 [dataset]. NASA National Snow and Ice Data Center Distributed Active Archive Center, https://doi.org/10.5067/K1EYYP0SL2PF
Breiman, Leo (2001): Random Forests. Machine Learning, 45(1), 5-32, https://doi.org/10.1023/A:1010933404324
Buckley, Ellen M; Farrell, Sinead L; Herzfeld, Ute C; Webster, Melinda A; Trantow, Thomas; Baney, Oliwia N; Duncan, Kyle; Han, Huilin; Lawson, Matthew (2023): Observing the evolution of summer melt on multiyear sea ice with ICESat-2 and Sentinel-2. The Cryosphere, 17(9), 3695-3719, https://doi.org/10.5194/tc-17-3695-2023
Chen, Dong; Farrell, Sinead L; Duncan, Kyle; Eun, Jaemin; Buckley, Ellen M; Hofton, Michelle A; Blair, Bryan; Saylam, Kutalmis (preprint): AGU2023: Melt Pond and Lead Detection in Melting Ice using ICESat-2 Altimetry and Very-High-Resolution (VHR) Aerial Imagery. https://doi.org/10.22541/essoar.170365363.32462108/v1
Chen, Dong; Loboda, Tatiana V; Silva, Julie A; Tonellato, Maria R (2021): Characterizing Small-Town Development Using Very High Resolution Imagery within Remote Rural Settings of Mozambique. Remote Sensing, 13(17), 3385, https://doi.org/10.3390/rs13173385
Farrell, Sinead L; Duncan, Kyle; Buckley, Ellen M; Richter‐Menge, J; Li, Ruohan (2020): Mapping Sea Ice Surface Topography in High Fidelity With ICESat‐2. Geophysical Research Letters, 47(21), e2020GL090708, https://doi.org/10.1029/2020GL090708
Documentation:
University of Maryland Classified LVIS Georeferenced Imagery of Arctic Summer Sea Ice, Version 1: User Guide. Dataset Description_v5.pdf
Funding:
National Aeronautics and Space Administration (NASA), grant/award no. 80NSSC22K0815: Enhancing Laser altimeter Elevation measurements through Validation of Arctic summer sea ice as Temperatures Evolve
Coverage:
Median Latitude: 82.795000 * Median Longitude: -28.760000 * South-bound Latitude: 78.670000 * West-bound Longitude: -73.360000 * North-bound Latitude: 86.920000 * East-bound Longitude: 15.840000
Date/Time Start: 2022-07-11T14:02:19 * Date/Time End: 2022-07-26T15:39:01
Event(s):
Parameter(s):
# | Name | Short Name | Unit | Principal Investigator | Method/Device | Comment |
---|---|---|---|---|---|---|
1 | DATE/TIME | Date/Time | Chen, Dong | Geocode | ||
2 | Raster graphic, GeoTIFF format | GeoTIFF | Chen, Dong | |||
3 | Raster graphic, GeoTIFF format (File Size) | GeoTIFF (Size) | Bytes | Chen, Dong |
License:
Creative Commons Attribution 4.0 International (CC-BY-4.0)
Status:
Curation Level: Basic curation (CurationLevelB)
Size:
1387 data points