The data contains Aerial imagery of Ynyslas Dunes, Wales saved in a GeoTiff format. The imagery covers 8000 m2 of a discrete coastal sand dune at northern distal end of a spit in Dyfi National Nature Reserve. Data was collected during a six-minute flight on 5th February 2020 made by a DJI Mavic Pro 2 uncrewed aerial vehicle (UAV). The flight was planned with Pix4DCapture based on a ground pixel resolution of 0.01 m. Lateral and longitudinal overlap was set to 80%. Prior to flying, eight (5.8 per 100 photos) Ground Control Points (GCPs) were evenly distributed throughout the dune and their location surveyed using a differential global positioning system (DGPS). Orthorectification and mosaicking of the aerial imagery collected was performed using Pix4Dmapper utilising a fully automated workflow based on Structure-from-Motion (SFM) digital photogrammetry algorithms. The data was collected to test the accuracy and repeatability of bare sand and vegetation cover in dunes mapped from aerial imagery. Data was collected and processed by Dr Ryan Wilson (University of Huddersfield) and interpreted by Dr Thomas Smyth (University of Huddersfield). The work was supported by the Natural Environment Research Council NE/T00410X/1. Full details about this dataset can be found at https://doi.org/10.5285/ac7071cb-79a3-400d-9f17-13dc4a657083

This dataset contains the post-processed GNSS/INS buoy data for a kinematic correction of a moving base station. The GNSS/INS buoys were deployed on sea ice during the 2019-20 MOSAiC expedition. These buoys recorded raw GNSS/INS data at a sampling rate of 10 Hz. For the kinematic correction, two buoys (with overlapping measurements of each other) were selected, and one of the buoys was used as a moving "base" and the other as the "rover". The post-processed dataset contains kinematically corrected latitude, longitude and velocity of the rover, as well as the baseline distance between the rover and base. The main objective of the kinematic correction is to create high-precision and high-frequency data to measure ice dynamics at a few centimetre accuracies. The buoys were assembled by the University of Huddersfield team and the deployment was done by the MOSAiC ice team throughout the expedition. This work was funded by NERC MOSAiC program NE/S002545/1.

This dataset contains the floe size distribution (FSD) data derived from multi-satellite imagery data acquired across the Arctic Ocean. Satellite imagery data includes high-resolution visible images from the USGS Global Fiducials Library (MEDEA), TerraSAR-X/TanDEM-X and Worldview-3 (WV3). The derived data contain floe size (calliper diameter), shape factor, minor/major axis, perimeter and area of the floes. This data set has been used to investigate the characteristics of the FSD during major seasonal evaluation stages of Arctic sea ice floes. The retrieval of the FSD data was done by the University of Huddersfield team. This work was funded by NERC MOSAiC program NE/S002545/1.

This dataset contains the floe size distribution (FSD) data derived from high-resolution satellite imagery data acquired at two fixed locations in the Arctic Ocean. Satellite imagery data include MEDEA images and WorldView images. These satellite images have a spatial resolution of 1 m or higher, thus providing the FSD information, especially for small floes. The derived data contain floe size (calliper diameter), shape factor, minor/major axis, perimeter and area of the floes. This dataset has been used to evaluate the sea ice models with the FSD parameterisations. The retrieval of the FSD data was done by the University of Huddersfield team. This work was funded by NERC standard grant NE/R000654/1 and NERC MOSAiC program NE/S002545/1.

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.

This dataset contains the raw data from GNSS/INS (Global Navigation Satellite System/Inertial Navigation System) buoys deployed during the 2019-2020 MOSAiC expedition. These buoys recorded the data from GNSS and Sensors. The raw GNSS data contain time, latitude, longitude, velocity, and fix type. The raw Sensors data contain time, acceleration, gyroscope, magnetometer, and temperature. These data were sampled at 10 Hz. The original data was in ANPP format (see advancednavigation.com), which have been converted to structured ASCII formats (such as RINEX, CSV) using Spatial Manager software. The buoys were assembled by the University of Huddersfield team and the deployment was done by the MOSAiC ice team throughout the expedition. This work was funded by NERC MOSAiC program NE/S002545/1.

This data contains values of bare sand area, modelled wind speed, aspect and slope at a 2.5 m spatial resolution for four UK coastal dune fields, Abberfraw (Wales), Ainsdale (England), Morfa Dyffryn (Wales), Penhale (England). Data is stored as a .csv file. Data is available for 620,756.25 m2 of dune at Abberfraw, 550,962.5 m2 of dune at Ainsdale, 1,797,756.25 m2 of dune at Morfa Dyffryn and 2,275,056.25 m2 of dune at Penhale. All values were calculated from aerial imagery and digital terrain models collected between 2014 and 2016. For each location, areas of bare sand were mapped in QGIS using the semi-automatic classification plugin (SCP) and the minimum distance algorithm on true-colour RGB images. The slope and aspect of the dune surface at each site was calculated in QGIS from digital terrain models. Wind speed at 0.4 m above the surface of the digital terrain model at each site was calculated using a steady state computational fluid dynamics (CFD). Data was collected to statistically test the relationship between bare sand and three abiotic physical factors on coastal dunes (wind speed, dune slope and dune slope aspect). Vertical aerial imagery was sourced from EDINA Aerial Digimap Service and digital terrain models from EDINA LIDAR Digimap Service. Wind speed data was generated and interpreted by Dr Thomas Smyth (University of Huddersfield). Full details about this dataset can be found at https://doi.org/10.5285/972599af-0cc3-4e0e-a4dc-2fab7a6dfc85

20 Ice Trackers were deployed at the MOSAiC drifting site. The deployment of the trackers was made from the helicopter onboard RV Polarstern during Leg 5 of the expedition. The data contain the GPS positioning of the trackers (and the motion of the ice on which the trackers were deployed). The data record starts from early September 2020 and lasted until July 2021 for the longest-surviving trackers. The trackers started their drift near the North Pole and move to the south through the Fram Strait. The deployment of the trackers was done in collaboration with the MOSAiC ice team. This work was funded by NERC MOSAiC program NE/S002545/1.

The dataset (FSD-GFL-res2m-Preponding) contains sea-ice floe ice distribution (FSD) data derived from the Global Fiducials Library (GFL) imagery during the pre-ponding period at the three fiducial sites, using the algorithms described in Hwang et al. (2017). The GFL imagery is 1-m resolution declassified National Technical Means satellite imagery, also known as the Literal Image Derived Products (LIDPs) (Kwok, 2014). The FSD data derived from the GFL imagery cover the period of 2000 to 2014 at the three fiducial sites at Chukchi Sea (70 deg N and 170 deg W), East Siberian Sea (82 deg N and 150 deg E), and Fram Strait (84.9 deg N and 0.5 deg E). For the production of this dataset, the spatial resolution of the GFL imagery degraded to 2 meters ("res2m") for fast processing. The FSD data are produced for robust model calibration and validation for FSD parameterisations within sea-ice models, and also to improve our understanding of spatial and temporal variations of FSD across the Arctic Ocean. The FSD data have been generated by B. Hwang. This FSD dataset is produced as part of NERC MIZ NE/R000654/1 (Towards a marginal Arctic sea ice cover).