Abstract:
This dataset contains 92 georeferenced GeoTIFF products comprising 46 orthophotos and 46 digital surface models (DSMs) derived from low-cost UAV surveys of landfast sea ice in the Pond Inlet / Mittimatalik area, northeastern Baffin Island, Nunavut, Canada. The files span three field seasons in April 2023, April 2024, and March-April 2025 and are organised by year and product type. Filenames show acquisitions from DJI Mini 2 and DJI Mini 3 platforms. Red-green-blue (RGB) source imagery was first pre-processed with a complex double dual-tree wavelet workflow to generate wavelet-enhanced RGB inputs and then processed in WebODM Lightning with auto-boundary, DSM generation, nominal 5 cm orthophoto/digital elevation model resolution, and rolling-shutter correction. All final DSM GeoTIFFs were subsequently post-processed with a custom relative-elevation workflow, producing wavelet-enhanced DSMs that emphasise landfast sea-ice surface variability at length scales of less than about 50 m. Orthophotos are 4-band red-green-blue-alpha (RGBA) GeoTIFFs and DSMs are single-band Float32 GeoTIFFs. The products are georeferenced in World Geodetic System 1984 / Universal Transverse Mercator (WGS 84 / UTM) zones 17N and 18N and support analysis of sea-ice roughness, morphology, environmental conditions, and the use of low-cost sensors for characterising landfast sea ice across multiple years. The dataset was produced within the Sikuttiaq project co-led by Andrew Arreak and Michel Tsamados.
This research and the resulting dataset were supported by the Canada-Inuit Nunangat United Kingdom (CINUK) Arctic Research Programme, a multilateral collaboration between United Kingdom Research and Innovation (UKRI), the National Research Council of Canada (NRC), Polar Knowledge Canada (POLAR), Inuit Tapiriit Kanatami (ITK), Parks Canada, and Fonds de recherche du Quebec (FRQ). Funding was provided under Natural Environment Research Council (NERC), UKRI, Grant Reference NE/X004643/1, for the project "Empowering our communities to map rough ice and slush for safer sea-ice travel in Inuit Nunangat" (Sikuttiaq). The project is co-led by Andrew Arreak (SmartICE) and Michel Tsamados (University College London) and focuses on Inuit-led sea-ice monitoring and travel safety.
Keywords:
Newman, T., & Tsamados, M. (2026). Wavelet-enhanced digital surface models and orthophotos of landfast sea ice from low cost unmanned aerial vehicle (UAV) surveys near Pond Inlet, Nunavut, Canada, 2023-2025 (Version 1.0) [Data set]. NERC EDS UK Polar Data Centre. https://doi.org/10.5285/364d6aeb-34de-4fa2-8221-d8c9e30d0cce
| Access Constraints: | This data is under embargo until 2027-04-07 |
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| Use Constraints: | This data is governed by the NERC data policy http://www.nerc.ac.uk/research/sites/data/policy/ and supplied under Open Government Licence v.3 http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/. |
| Creation Date: | 2026-04-15 |
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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 PDC |
| Role(s) | Metadata Author |
| Organisation | British Antarctic Survey |
| Name | Thomas Newman |
| Role(s) | Investigator, Technical Contact |
| Organisation | University College London |
| Name | Michel Tsamados |
| Role(s) | Investigator |
| Organisation | University College London |
| Parent Dataset: | N/A |
| Reference: | Selesnick, I. W. (2004). The double-density dual-tree DWT. IEEE Transactions on Signal Processing, 52(5), 1304-1314. https://doi.org/10.1109/TSP.2004.826174 Selesnick, I. W. DoubleSoftware MATLAB resources for double-density and dual-tree wavelet transforms. https://eeweb.engineering.nyu.edu/iselesni/DoubleSoftware/index.html |
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| Quality: | Quality control included validation of derived imagery, completion checks on WebODM Lightning task outputs, and screening of products by environmental conditions. Orthophotos are 4-band red-green-blue-alpha (RGBA) GeoTIFFs with no data value 0; DSMs are single-band Float32 GeoTIFFs with nodata value -9999. Nominal spatial resolution is 5cm. No real-time kinematic/post-processed kinematic (RTK/PPK), surveyed checkpoints, or georeferencing ground control points (GCPs) were used in WebODM Lightning processing. Checkerboard targets were deployed in the field for checks such as white balance rather than for georeferencing control. The absolute horizontal positional accuracy of the GeoTIFF products is limited by the onboard non-real-time kinematic drone Global Positioning System (GPS) used during image acquisition and photogrammetric reconstruction. Relative horizontal accuracy of surface features within individual products is of the order of 15 cm, expressed here as horizontal circular error at 90% confidence (Horizontal CE90, metres) calculated internally by WebODM Lightning software. A detailed accuracy assessment is the subject of an upcoming publication. |
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| Lineage/Methodology: | Source UAV JPEG imagery of landfast sea ice was collected and organised by survey date and site. For photogrammetric data collection, the UAVs were flown at a standard flight altitude of 100 m, with nadir-looking photographs acquired at 85% front overlap and 85% side overlap. A complex double dual-tree wavelet workflow, based on the double-density dual-tree discrete wavelet transform described by Selesnick (2004) and translated to Python from MATLAB software released by Ivan W. Selesnick, was used to generate wavelet-enhanced RGB inputs from the source JPEGs before photogrammetric processing in WebODM Lightning. The WebODM Lightning processing used auto-boundary, 5 cm orthophoto and DSM resolution, DSM generation, and rolling-shutter correction. The objective was to derive surface products that capture sea-ice roughness using low-cost UAV-based sensors. The orthophotos are WebODM Lightning orthophoto GeoTIFFs. The DSMs were post processed from the raw WebODM Lightning DSM outputs using a custom relative-elevation workflow in which missing or nodata pixels were filled using nearest-neighbour assignment, an approximation-only wavelet surface was generated at fixed level J = 10 and subtracted from the DSM, values outside the convex hull of photo capture locations were masked, and the half-sample mode of valid in-hull elevations was subtracted from the final DSM. The resulting DSM band values represent relative elevations intended to capture variability on scales of less than about 50 m rather than absolute terrain elevations. Survey naming is not consistent across years. Site labels reflect year-specific priorities and roughness conditions rather than a stable multi-year site numbering system. |
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| Temporal Coverage: | |
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| Start Date | 2023-04-18 |
| End Date | 2025-04-07 |
| Spatial Coverage: | |
| Latitude | |
| Southernmost | 72.71555 |
| Northernmost | 72.82264 |
| Longitude | |
| Westernmost | -78.51375 |
| Easternmost | -77.81989 |
| 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 |
| Vertical Resolution | N/A |
| Vertical Resolution Range | < 1 meter |
| Temporal Resolution | N/A |
| Temporal Resolution Range | N/A |
| Location: | |
| Location | Canada |
| Detailed Location | Pond Inlet (Mittimatalik) region, northeastern Baffin Island, Nunavut |
| Data Collection: | DJI Mini 2 with onboard camera model FC7303, firmware/software v01.43.0074, 4000 x 3000 JPEG output, focal length 4.5 mm (24 mm equivalent), and f/2.8 aperture. DJI Mini 3 with onboard camera model FC3682, firmware/software v01.64.0152, 4000 x 3000 JPEG output, focal length 6.7 mm (24 mm equivalent), and f/1.7 aperture. Processing software: WebODM Lightning Engine (LGT) version 4.1.5, plus custom wavelet pre-processing and DSM post-processing workflows, which were not versioned. |
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| Data Storage: | The release contains 92 GeoTIFF files totaling approximately 9.44 GB (gigabytes): 46 orthophotos and 46 DSMs. Orthophotos are 4-band Byte RGBA GeoTIFFs; DSMs are single band Float32 GeoTIFFs. Counts by year: 2023: 12 files (6 orthophoto/DSM pairs) 2024: 66 files (33 orthophoto/DSM pairs) 2025: 14 files (7 orthophoto/DSM pairs) |
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