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  • This data set contains the results from a study of the behaviour of Weddell seals (Leptonychotes weddelli) at the Vestfold Hills, Prydz Bay, Antarctica. Three satellite transmitters were deployed on tagged female Weddell seals at the Vestfold Hills mid-winter (June) 1999. The transmitters were recovered in December, late in the pupping season. In total, the three transmitters were deployed and active 170 days, 175 days and 180 days. I used the first two classes of data to get fixes with a standard deviation less than 1 km. Most seal holes were more that 1 km apart (see Entry: wed_survey) so at this resolution we can distinguish between haul-out sites. We examine the number and range of locations used by the individual seals. We use all data collectively to look at diurnal and seasonal changes in haul-out bouts. None of the seals were located at sites outside the area of fast ice at the Vestfold Hills, although one seal was sighted on new fast-ice (20 - 40 cm thick). Considering the long bouts in the water, and that we only tracked haul-out locations, the results do not eliminate the possibility that the seals made long trips at sea. The original data are stored by the Australian Antarctic Division in the ARGOS system on the mainframe Alpha. The transmitter numbers are 23453, 7074 and 7075.

  • From the abstract of some of the referenced papers: An expert system is being developed which will apply knowledge-based techniques to the automated interpretation of remotely sensed sea-ice images taken over East Antarctica by the NOAA series of meteorological satellites. It is capable of accepting satellite images, deriving characteristic features from them and then performing knowledge-based reasoning to identify regions of cloud, land, open water and various categories of sea-ice. XXXXXXXXXXXXX This paper describes the system design of SPARTEX, a system developed to use information from remote sensing and geographic information systems linked to expert systems. It aims to automate the process of classifying information about the actual or potential use of part of the earth's surface. See the link below for public details on this project.

  • An occupancy survey in December 2009-February 2010 and January 2011 found a total of 6 islands along the Knox coast had populations of breeding Adelie penguins. The survey in 2009/10 was conducted from a fixed wing aircraft and oblique aerial photographs were taken of occupied sites. The aerial photographs were geo-referenced to satellite images or the coastline shapefile from the Landsat Image Mosaic of Antarctica (LIMA, tile E157) and the boundaries of penguin colonies were digitised from the geo-referenced photos. Details for each island are: Merrit: Photographs taken on 1 February 2010 and geo-referenced to LIMA tile E157 Cape Nutt: Photographs taken on 5 January 2010 and geo-referenced to a Quickbird satellite image taken on 17 February 2011 Ivanoff Head: Photographs taken on 27 December 2009 and geo-referenced to LIMA tile E157 Please refer to the Seabird Conservation Team Data Sharing Policy for use, acknowledgement and availability of data prior to downloading data.

  • This dataset contains the results from satellite tracking the movements of Adelie Penguins (Pygoscellis adeliae) from Edmonson Point in the Terra Nova Bay region, Antarctica. By the use of satellite fixes the foraging locations of the penguins were determined. Monitoring took place between 1994 and 2001. This work was completed as part of ASAC project 2205 (ASAC_2205), 'Adelie penguin research and monitoring in support of the CCAMLR Ecosystem Monitoring Project'.

  • GEBCO’s (General Bathymetric Chart of the Oceans) gridded bathymetric data set, the GEBCO_2019 Grid, is a global terrain model for ocean and land, providing elevation data, in meters, on a 15 arc-second interval grid. The GEBCO 2019 grid is reformatted as a Cloud Optimised GeoTIFF suitable for online requests and republished for use primarily by software development. Original GEBCO grid was obtained from

  • Maps of East Antarctic landfast sea-ice extent, generated from approx. 250,000 1 km visible/thermal infrared cloud-free MODIS composite imagery (augmented with AMSR-E 6.25-km sea-ice concentration composite imagery when required). Because of imperfections in the MODIS composite images (typically caused by inaccurate cloud masking, persistent cloud in a given region, and/or a highly dynamic fast-ice edge), automation of the fast-ice extent retrieval process was not possible. Each image was thus classified manually. A study of errors/biases of this process revealed that most images were able to be classified with a 2-sigma accuracy of +/- ~3%. More details are provided in Fraser et al., (2010). *Version 1.2 with extra QC around the Mawson coast and Lutzow-Holm Bay The directory named "pngs" contains browsable maps of fast-ice extent, in the form of Portable Network Graphics (PNG) images. Each of the 159 consecutive images (20-day intervals from Day Of Year (DOY) 61-80, 2000 to DOY 341-366, 2008) contains a map of fast-ice extent along the East Antarctic coast, generated from MODIS and AMSR-E imagery. The colour scale is as follows: Dark blue: Fast ice, as classified from a single 20-day MODIS composite image Red: Fast ice, as classified using the previous or next 20-day MODIS composite images Yellow: Fast ice, as classified using a single 20-day AMSR-E composite image White: Antarctic continent (including ice shelves), as defined using the Mosaic of Antarctica product. Light blue: Southern ocean/pack ice/icebergs These maps are also provided as unformatted binary fast ice images, in the directory named "imgs". These .img files are all flat binary images of dimension 4300 * 425 pixels. The data type is 8-bit byte. Within the .img files, the value for each pixel indicates its cover: 0: Southern Ocean, pack ice or icebergs, corresponding to light blue in the PNG files. 1: Antarctic continent (including ice shelves), as defined using the Mosaic of Antarctica product, corresponding to white in the PNG files. 2: Fast ice, as classified from a single 20-day MODIS composite image, corresponding to dark blue in the PNG files 3: Fast ice, as classified using a single 20-day AMSR-E composite image, corresponding to yellow in the PNG files 4: Fast ice, as classified using the previous or next 20-day MODIS composite images, corresponding to red in the PNG files To assist in georeferencing these data, files containing information on the latitude and longitude of each pixel are provided in the directory named "geo". These files are summarised as follows: lats.img: File containing the latitude of the centre of each pixel. File format is unformatted 32-bit floating point, 4300 * 425 pixels. lons.img: File containing the longitude of the centre of each pixel. File format is unformatted 32-bit floating point, 4300 * 425 pixels. The .gpd Grid Point Descriptor file used to build the projection is also included. It contains parameters which you can use for matching your projection. To refer to the time series, climatology, or maps of average persistence, please reference this paper: Fraser, A. D., R. A. Massom, K. J. Michael, B. K. Galton-Fenzi, and J. L. Lieser, East Antarctic landfast sea ice distribution and variability, 2000-08, Journal of Climate 25, 4, pp. 1137-1156, 2012 In addition, please cite the following reference when describing the process of generating these maps: Fraser, A. D., R. A. Massom, and K. J. Michael, Generation of high-resolution East Antarctic landfast sea-ice maps from cloud-free MODIS satellite composite imagery, Elsevier Remote Sensing of Environment, 114 (12), 2888-2896, doi:10.1016/j.rse.2010.07.006, 2010. To reference the techniques for generating the MODIS composite images, please use the following reference: Fraser, A. D., R. A. Massom, and K. J. Michael, A method for compositing polar MODIS satellite images to remove cloud cover for landfast sea-ice detection, IEEE Transactions on Geoscience and Remote Sensing, 47 (9), pp. 3272-3282, doi:10.1109/TGRS.2009.2019726, 2009. Please contact Alex Fraser ( for further information.

  • This study employs data from two satellite-borne instruments namely, the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) and the Total Ozone Mapping Spectrometer (TOMS). This work was completed as part of an honours project under ASAC project 2210 (UV climate over the Southern Ocean south of Australia, and its biological impact). Further information about the project is available in the word document available for download (extract from the honours thesis). The fields in this dataset are: Region Year Day (Julian Day) Pixels (number of cloud free pixels from SeaWiFS sensor that were available for analysis) Mean Chlorophyll (milligrams per cubic metre) (derived from cloud free pixels) Standard Deviation Ozone (dobson units) from the TOMS sensor (average for whole region).

  • Despite being a ubiquitous and abundant component of the Southern Ocean ecosystem, pack-ice seals (crabeater, Ross and leopard seals) are notoriously difficult to census as they are sparsely distributed over large regions of remote pack-ice. Historically, population censuses have been made from ship- or helicopter-based surveys, which are expensive and logistically difficult, and this inevitably leads to data which are limited, in time and space. High resolution images allow us now to accurately census seals e.g. elephant and Weddell seals at unprecedented spatial and temporal scales. Using this technology promises to provide regular estimates of the numbers of pack-ice seals in important regions such as Prydz Bay This study will develop techniques to survey pack-ice seals from high resolution satellite images, including automatic detection functions and a preliminary habitat model based on the characteristics of the ice contained in the images.

  • Public summary for project 2128: The aim of this study is to relate the foraging behaviour of Antarctic fur seals breeding on the Kerguelen Plateau at Iles Kerguelen and Heard Island, to the distribution of prey species at sea. Specifically this project seeks to examine the relationship between predators and prey, and how their locations at sea vary according to the position of major productive zones, such as the Antarctic Polar Frontal Zone. This project will provide important data on the relationship between predators and their prey and the developing commercial fisheries in the region. These data are central to improved conservation and management of marine resources on the Kerguelen Plateau. Variations made to the work plan The original comparative aspects of the program planned for the 1999/00 season, where fur seals from Iles Kerguelen and Heard Island were to be satellite tracked simultaneously could not be undertaken because of original 1999/00 field season to Heard Island was re-scheduled to 2000/01. Fortunately the project collaborator Dr Christophe Guinet (French CEBC-CNRS) agreed to extend the work program at Iles Kerguelen another season, and the comparative and integrated fur seal-prey-fisheries study over the Kerguelen Plateau was undertaken the following season (2000/01). Details of this study are presented in ASAC project 1251 (CI - Goldsworthy)and 1085 (CI-Robertson). Significant findings: The distribution of the foraging activity of Antarctic fur seal females was investigated at Cap Noir (49 degrees 07 S, 70 degrees 45E), Kerguelen Island in February 1998. Eleven females were fitted with a satellite transmitter and Time Depth recorder. The two sets of data were combined to locate spatially the diving activity of the seals. The fish component of the fur seal diet was determined by the occurrence of otolotihs found in 55 scats collected during the study period at the breeding colony. Oceanographic parameters were obtained simultaneously through direct sampling and satellite imagery. The mesopelagic fish community was sampled on 20 stations along four transects where epipelagic trawls were conducted at night at 50 meters of depth. We then investigated, using geographic information systems, the relationship between the spatial distribution of the diving activity of the fur seals and oceanographic factors that included sea surface temperature, surface chlorophyll concentration, prey distribution and bathymetry obtained at the same spatio-temporal scale as the spatial distribution of the diving activity of our study animals. An inverse relationship was found between the main fish species preyed by fur seal and those sampled in trawl nets. However, the diving activity of Antarctic fur seal females was found to be significantly related to oceanographic conditions, fish-prey distribution and to the distance from the colony but these relationships changed with the spatial scale investigated. A probabilistic model of the Kerguelen Plateau was developed that predicted where females should concentrate their foraging activity according to the oceanographic conditions of the year, and the locations of their breeding colonies. Maternal allocation in growth of the pup was measured in Antarctic fur seals (Arctocephalus gazella) at Iles Kerguelen during the 1997 austral summer. Absolute mass gain of pups following a maternal foraging trip was independent of the sex of the pup but was positively related to the foraging trip duration and to maternal length. However, daily mass gain, i.e. the absolute mass gain of the pup divided by the foraging trip duration, decreased with increasing foraging trip duration but increased with maternal length. While fasting, the daily mass loss of the pup was related to the sex of the pup and initial body mass, with both heavier pups and female pups losing more mass per day than lighter pups and male pups. The mass specific rate of mass loss was significantly higher in female pups than in male pups. Over the study period, the mean growth rate was zero with no difference between female and male pups. The growth rate in mass of the pup was positively related to maternal length but not maternal condition, negatively related to the foraging trip duration of the mother and the initial mass of the pup. This indicated that during the study period heavier pups grew more slowly due to their higher rate of daily mass loss during periods of fasting . Interestingly, for a given maternal length, the mean mass of the pup during the study period was higher for male than for female pups, despite the same rate of daily mass gain. Such differences are likely to result from sex differences in the mass specific rate of mass loss. As female pups lose a greater proportion of their mass per day, a zero growth rate i.e. mass gain only compensates for mass loss, is reached at a lower mass in female pups compared to male pups. Our results indicate that there are no differences in maternal allocation according to the sex of the pup but suggest that both sexes follow a different growth strategy. Results are in line with the objectives of the project. animal_id (identifier of the individual animal) location_class (the Argos location class quality, 0-3) latitude (decimal degrees) longitude (decimal degrees) observation_date (the date of observation, in ISO8601 format yyyy-mm-ddTHH:MM:SSZ. This information is also separated into the year, month, day, etc components) observation_date_year (the year of the observation date) observation_date_month (the month of the observation date) observation_date_day (the day of the observation date) observation_date_hour (the hour of the observation date) observation_date_minute (the minute of the observation date) observation_date_time_zone (the time zone of the observation date) deployment_longitude (location that the tracker was deployed, decimal longitude) deployment_latitude (location that the tracker was deployed, decimal latitude) trip (the identifier of the trip made by this animal) at_sea (whether this point was at sea (1) or on land (0)) complete (was this trip complete - i.e. did the animal return to the colony) scientific_name (scientific name of the tracked animal)

  • This dataset contains the results from satellite tracking the movements of Adelie Penguins (Pygoscelis adeliae) from Magnetic Island near Davis Station, Antarctica. By the use of satellite fixes the foraging locations of the penguins were determined. Monitoring occurred during the 1993-94 and 1994-95 summer seasons. This work was completed as part of ASAC project 2205 (ASAC_2205), 'Adelie penguin research and monitoring in support of the CCAMLR Ecosystem Monitoring Project'. Further work in the Davis area was completed under other projects.