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Data Publisher for Earth & Environmental Science

Halle, Danielle: Machine Learning-Based Monitoring of Surface Melt on Devon Ice Cap, Nunavut, Canada Using Sentinel-1 (2015-2024) [dataset]. PANGAEA, https://doi.pangaea.de/10.1594/PANGAEA.993072 (dataset in review)

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Abstract:
This dataset provides record of glacier surface melt conditions on Devon Ice Cap, Nunavut, Canada, derived from sub-weekly Sentinel-1 synthetic aperture radar (SAR) Extra Wide (EW) mode imagery and digital elevation model (DEM) derivatives for the period 2015–2024. A convolutional neural network (CNN) was trained using 8,297 manually labelled samples to classify four surface classes: glacier ice, slush, wet snow/firn, and dry snow. The repository includes ~300 classified raster products for each acquisition period. All data are georeferenced, time-stamped, and formatted for direct integration into GIS and remote sensing workflows.
This dataset can be used for melt onset, extent, and duration across a decade of observations and supports applications in surface mass balance assessment, firn evolution studies, and the development and benchmarking of machine learning approaches for SAR-based cryospheric monitoring in the Canadian Arctic Archipelago.
Keyword(s):
Canadian Arctic Archipelago; Convolutional neural network; glacier ice; Melt season
Related to:
Halle, Danielle; Van Wychen, W; Kelly, R; Danielson, B; Burgess, D; Maslov, K A; Schellenberger, Thomas (in press): Machine Learning-Based Monitoring of Surface Melt on Devon Ice Cap, Nunavut, Canada Using Sentinel-1 (2015-2024). Canadian Journal of Remote Sensing
Coverage:
Latitude: 75.271873 * Longitude: -82.447105
Date/Time Start: 2015-06-15T00:00:00 * Date/Time End: 2024-09-07T00:00:00
Event(s):
Nunavut_2015-2024 * Latitude: 75.271873 * Longitude: -82.447105 * Date/Time Start: 2015-06-15T00:00:00 * Date/Time End: 2024-09-07T00:00:00 * Method/Device: Synthetic Aperture Radar (SAR), Sentinel, 1 [Extra Wide (EW) mode imagery and digital elevation model (DEM)]
Comment:
All files are named with the following naming convention and extension:
pred_stacked_[YYYY][MM][DD][HH][MM][YYYY][MM][DD][HH][MM]_Sentinel-1_EW_HH+HV_HH-_decibel_gamma0_bands.tif
Parameter(s):
#NameShort NameUnitPrincipal InvestigatorMethod/DeviceComment
1Binary ObjectBinaryHalle, DanielleSynthetic Aperture Radar (SAR), Sentinel, 1 [Extra Wide (EW) mode imagery and digital elevation model (DEM)]
2Binary Object (File Size)Binary (Size)BytesHalle, DanielleSynthetic Aperture Radar (SAR), Sentinel, 1 [Extra Wide (EW) mode imagery and digital elevation model (DEM)]
3Binary Object (MD5 Hash)Binary (Hash)Halle, DanielleSynthetic Aperture Radar (SAR), Sentinel, 1 [Extra Wide (EW) mode imagery and digital elevation model (DEM)]
4Binary Object (Media Type)Binary (Type)Halle, DanielleSynthetic Aperture Radar (SAR), Sentinel, 1 [Extra Wide (EW) mode imagery and digital elevation model (DEM)]
License:
Creative Commons Attribution 4.0 International (CC-BY-4.0) (License comes into effect after moratorium ends)
Status:
Curation Level: Basic curation (CurationLevelB)
Size:
228 data points

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