Marine debris washing up on beaches on Bird Island has been monitored since 1989 with over 9,000 items of debris recovered up until present day. In addition to the raw data, a summary of the data by year or by debris description is available. Occasions when no debris was found, or it was not possible to carry out a survey, are recorded in the metadata. This data is submitted to the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) as part of their Marine Debris Programme.

Incidences of Antarctic Fur Seals entangled in man-made debris have been recorded since 2008 at Grytviken, South Georgia. The majority of entanglements have been Antarctic Fur Seals caught in plastic packaging bands, synthetic line and fishing nets. Where possible these are removed by scientists working at the research base. This data is collected as part of CCAMLR''s Marine Debris Programme.

The presence of marine debris and other material from human activity within bird colonies on Bird Island has been recorded since 1992. Bird colonies on the Island are regulary monitored for the presence of debris as part of CCAMLR''s Marine Debris Program. Debris can be found within the colonies, entangling the birds, or within diet samples. Where possible, all debris are removed. The date of survey, debris type and debris dimensions are recorded. This data is submitted to the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) as part of their Marine Debris Programme.

This annotated dataset comprises locational data of beluga whales along the eastern shore of the Yugor Penisula and in the inner part of Baydaratskaya Bay in the southern Kara Sea (Russia) as detected from Very High Resolution (VHR) satellite imagery on July 4th and 9th, 2016. Images were manually scanned and whales detected through the use of grids. Additional metadata includes information on image type and model, and whale distinctive characteristics (e.g., fluke or blow). This work supports the ''training'' of machine learning algorithms for automatic detection of whales from satellite imagery. This study was possible thanks to imagery support from MAXAR Technologies/Digital Globe Foundation for the VHR images and core funding from British Antarctic Survey, Natural Environment Research Council, as part of the ''Wildlife from Space'' project.

This annotated dataset comprises locational data of grey whales in lagoons San Ignacio and Ojo de Liebre in Baja California Sur as detected from Very High Resolution (VHR) satellite imagery in January 2009, 2013 and 2015. Images were manually scanned and whales detected through the use of grids. Additional metadata includes information on image type and model, and whale distinctive characteristics (e.g., fluke or blow). This work supports the '' training'' of machine learning algorithms for automatic detection of whales from satellite imagery. This study formed part of the Ecosystems component of the British Antarctic Survey Polar Science for Planet Earth Programme, funded by The Natural Environment Research Council. The work was supported by the UKRI Centre for Doctoral Training in Application of Artificial Intelligence to the study of Environmental Risks (reference EP/S022961/1).

This dataset comprises video and imagery captured around Rothera Point, Adelaide Island on the West Antarctic Peninsula between November 2023 and February 2024. The data was captured as part of a biodiversity survey on an area to the North of Rothera Research Station. Operations were conducted off small boats and allowed data to be collected in shallow waters between 10 m and 60 m water depth. The dataset includes: seabed imagery captured using a down-facing drop camera, video footage from a Boxfish Luna remotely operated underwater vehicle (ROV), timelapse imagery from a camera installed on the Rothera Research station watch tower and video and imagery of a sediment profiler experiment of the seabed. Data were collected by personnel at BAS, funded by the Antarctic Infrastructure Modernisation Project (AIMP) Runway Project.