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.

Four ice monitoring stations were set up at Davis in 1993 (a fifth station was added after the first two months), with regular recordings of ice depth, snow cover and ablation made for each station by taking a sea ice core. Observations of the general condition of the drilled cores were also recorded. Observations were made at irregular intervals (roughly every 1-2 weeks). The observations for each individual day are listed, along with a summary table. These records are stored as handwritten files, and are archived at the Australian Antarctic Division.

The development of an operational sea ice mapping system. This metadata record refers to the development and testing of an prototype system, ICEMAPPER, to interpret NOAA AVHRR imagery on a semi-automatic basis, off the Southern Ocean near to the Antarctic coast. From the abstract of one of the referenced papers: This paper reports work towards the development of a semi-automated technique for creating sea-ice and cloud maps from Advanced Very High Resolution Radiometer (AVHRR) images of the Southern Ocean near to the Antarctic coast. The technique is implemented as a computer-based system which applies a number of classification rules to the five bands of an AVHRR image and classifies each pixel in the image as representing open water, low cloud, high cloud or one of several different sea ice concentration categories. The map produced by the system is then displayed and an experienced sea ice forecaster evaluates the result. If it is deemed satisfactory the map is saved on disk. If not, the expert can alter various parameters within the classification rules to produce a satisfactory map. Experience so far has shown that judicious, but reasonably minor, changes to the rule parameters can produce a satisfactory sea-ice map relatively quickly in most cases. The system is also capable of effectively distinguishing cloudy from clear pixels but it does not accurately distinguish high cloud from low cloud in some of the images. Current work is being undertaken to improve the cloud classification rules.

Metadata record for data expected from ASAC Project 2767 See the link below for public details on this project. A multidisciplinary survey of the processes linking sea ice with biological elements of Antarctic marine ecosystems was conducted in winter 2007. The survey provided large-scale information on sea ice biological and physical parameters in the 100-130 degree East sector off East Antarctica. The distribution of sea ice algae and krill were measured using various methods including ice coring surveys and trawls. These measurements were complemented by shipborne measurements and an intensive sea ice sampling program. Use of an ROV was attempted but did not result in quantitative/geo-referenced data. Under-ice video files are available from the Chief-Investigator. Individual word documents are available from this metadata record for each ice station. These contain information on the ice station number, date and time of record and the parameters/ samples.

Metadata record for data from ASAC Project 2702 See the link below for public details on this project. Sea-ice algae are the basis of the Antarctic food web and are essential for healthy functioning of the Antarctic ecosystem. These algae exploit a unique niche within this extreme environment. Using advanced photosynthetic analysis we will examine the mechanisms which influence the productivity of sea-ice algae. The objective of this project is to understand the processes of light acclimation and photo-protection employed by sea-ice algae under extremely low temperature conditions. Several new hypotheses have been proposed in a recent review of low temperature acclimation of higher plants (Oquist and Huner, 2003). To further understand the remarkable tolerance of sea-ice algae to photoinhibition, we propose to test several of these hypotheses. Sea-ice algae fix inorganic carbon that forms the basis of the Southern Ocean food web. Sea ice covers up to 20 million km2 of the Southern Ocean each year. Global climate change will decrease the sea-ice thickness and distribution (IPCC, 2001); however subtle changes in temperature and light penetration will also have profound negative impacts on the photosynthetic efficiency of the sea-ice microalgae before any macroscale changes take place. Sea-ice algae are essentially the only food source for invertebrates and fish for up to nine months of the year. During winter and spring, krill (Euphausia sp.) have been observed feeding directly on sea-ice algae. Further, changes in sea-ice productivity will have a cascade effect further up the food web. Therefore, understanding how physical driving forces (temperature and light) affect sea-ice algae productivity will be critical to our ability to predict the effects of climate change and sustainably manage this unique and vulnerable ecosystem. Our primary objective is: To understand the processes of light acclimation and photo-protection employed by sea-ice algae under extremely low temperature conditions, with an aim to better understanding the potential implications of global climate change on the Antarctic sea-ice ecosystem.

Metadata record for data from ASAC Project 2695 See the link below for public details on this project. Variations in the winter extent of sea ice are thought to have profound effects on biological productivity, such as algal growth and the reproduction of Antarctic krill, with subsequent flow-on effects through the food web. This pilot study aims to measure the winter foraging patterns of Weddell seals (Leptonychotes weddellii) as a first step in investigating their role in the winter sea-ice zone. Our specific objectives are to: 1. Obtain satellite tracks from a sample of adult female Weddell seals 2. Collect diving behaviour (dive depth, duration and frequency) from a sub-set of these seals 3. Collect high precision water temperature data from a subset of these seals These data will enable us to assess the feasibility of including Weddell seals as a candidate species in a long-term study of winter sea-ice and predator performance. This project has now been merged into project number 2794 (ASAC_2794). It also contains data collected as part of project 1171 (ASAC_1171). The download file contains 13 Access Databases containing data from this project. An excel spreadsheet summarising the databases is also included. The data have also been loaded into the Australian Antarctic Data Centre's ARGOS tracking database. The database can be accessed at the provided URL.

These data give the maximum extent of sea ice in the southern hemisphere by day and by winter season and the mean maximum extent by month. Data cover the 1979/1980 to 2007/2008 seasons. The data are available in csv files and, in the case of the mean monthly data, as point and line shapefiles.

Water depth measurements were taken in Long Fjord during early winter in 2007. The measurements were collected by Graham Cook, station leader at Davis Station in the Australian Antarctic Territory. The measurements were made by dropping a weighted line off the back of a quad bike, after drilling a hole through the sea ice. Measurements were made approximately every 100 metres. The download file contains a csv spreadsheet which lists each waypoint, plus the corresponding water depth and any comments. The text file contains the waypoint information collected by the Garmin GPS unit. Data in the text file are comma separated and are interpreted as follows: WP,D,001 (waypoint) , -68.51341000, 78.06903000,(Latitude and Longitude) 05/25/2007, 10:25:35, (Date and time Downloaded to Computer) 24-MAY-07 11:40:42 (Date and time of reading). Time is in local time. Vegetation was found on the weight that we used when we first started at the seaward end of the Fjord and then again in shallow water between Brookes Hut and a small island 800 or 900 metres out from Brookes. The weight is quite smooth and does not pick up a lot. The reference given below provides some further information about previously collected bathymetry data in Long Fjord. Furthermore, also see the metadata records: 'Bathymetric data of Long and Tryne Fjords at Vestfold Hills, Antarctica, collected in December 1999 [VH_bathy_99]' 'Interpolated bathymetry of Long and Tryne Fjords, Vestfold Hills, Antarctica [long_tryne_bathy]' The fields in this dataset are: Waypoint Latitude Longitude Water Depth Date Time

In September 2006, twenty-three scientists from six countries attended an Experts Workshop on Bioregionalisation of the Southern Ocean held in Hobart, Australia. The workshop was hosted by the Antarctic Climate and Ecosystems Cooperative Research Centre, and WWF-Australia, and sponsored by Antarctic expedition cruise operator, Peregrine Adventures. The workshop was designed to assist with the development of methods that might be used to partition the Southern Ocean for the purposes of large-scale ecological modelling, ecosystem-based management, and consideration of marine protected areas. The aim of the workshop was to bring together scientific experts in their independent capacity to develop a 'proof of concept' for a broad-scale bioregionalisation of the Southern Ocean, using physical environmental data and satellite-measured chlorophyll concentration as the primary inputs. Issues examined during the workshop included the choice of data and extraction of relevant parameters to best capture ecological properties, the use of data appropriate for end-user applications, and the relative utility of taking a hierarchical, non-hierarchical, or mixed approach to regionalisation. The final method involved the use of a clustering procedure to classify individual sites into groups that are similar to one another within a group, and reasonably dissimilar from one group to the next, according to a selected set of parameters (e.g. depth, ice coverage, temperature). The workshop established a proof of concept for bioregionalisation of the Southern Ocean, demonstrating that this analysis can delineate bioregions that agree with expert opinion at the broad scale. Continuation of this work will be an important contribution to the achievement of a range of scientific, management and conservation objectives, including large-scale ecological modelling, ecosystem-based management and the development of an ecologically representative system of marine protected areas. This metadata record provides links to the report from that workshop, the appendices to that report, and the ArcGIS files and Matlab code used during the workshop. The report is in PDF format. The Appendices to the report are in PDF format and contain: Appendix 1: Approaches to bioregionalisation - examples presented during the workshop Antarctic Environmental Domains Analysis CCAMLR Small-Scale Management Units for the fishery Antarctic krill in the SW Atlantic Australian National Bioregionalisation: Pelagic Regionalisation Selecting Marine Protected Areas in New Zealand's EEZ Appendix 2: Technical information on approach to bioregionalisation Appendix 3: Descriptions of datasets used in the analysis Appendix 4: Results of secondary regionalisation using ice and chlorophyll data Appendix 5: Biological datasets of potential use in further bioregionalisation work Appendix 6: Details of datasets, Matlab code and ArcGIS shapefiles included on the CD The ArcGIS archive is in zip format and contains the shapefiles and other ArcGIS resources used to produce the figures in the report. The Matlab archive is in zip format and contains the Matlab code and gridded data sets used during the workshop. See the readme.txt file in this archive for more information. Description of datasets Sea surface temperature (SST) Mean annual sea surface temperatures were obtained from the NOAA Pathfinder satellite annual climatology (Casey and Cornillon 1999). This climatology was calculated over the period 1985-1997 on a global 9km grid. Monthly values were averaged to obtain an annual climatology. Casey, K.S. and P. Cornillon (1999) A comparison of satellite and in situ based sea surface temperature climatologies, J. Climate, vol. 12, no. 6, pp. 1848-1863. Bathymetry Depth data were obtained from the GEBCO digital atlas (IOC, IHO and BODC, 2003). These data give water depth in metres and are provided on a 1-minute global grid. Centenary Edition of the GEBCO Digital Atlas, published on CD-ROM on behalf of the Intergovernmental Oceanographic Commission and the International Hydrographic Organization as part of the General Bathymetric Chart of the Oceans, British Oceanographic Data Centre, Liverpool, U.K. See http://www.gebco.net and https://www.bodc.ac.uk/projects/data_management/international/gebco/ A metadata record can be obtained from: http://data.aad.gov.au/aadc/metadata/metadata_redirect.cfm?md=AMD/AU/gebco_bathy_polygons Nutrient concentrations Silicate and nitrate concentrations were obtained from the WOCE global hydrographic climatology (Gouretski and Koltermann, 2004). This climatology provides oceanographic data on a 0.5 degree regular grid on a set of 45 standard levels covering the depth range from the sea surface to 6000m. The silicate and nitrate concentrations were calculated from seawater samples collected using bottles from stationary ships. The nutrient concentrations at the 200m depth level were used here; concentrations are expressed in micro mol/kg. https://odv.awi.de/data/ocean/woce-global-hydrographic-climatology/ Gouretski, V.V., and K.P. Koltermann, 2004: WOCE Global Hydrographic Climatology. Technical Report, 35, Berichte des Bundesamtes fur Seeschifffahrt und Hydrographie. Insolation (PAR) The mean summer climatology of the photosynthetically-active radiation (PAR) at the ocean surface was obtained from satellite estimates (Frouin et al.). These PAR estimates are obtained from visible wavelengths and so are not available over cloud- or ice-covered water, or in low-light conditions including the austral winter. Hence in the sea ice zone, this climatology represents the average PAR calculated over the period for which the water was not ice-covered. https://oceancolor.gsfc.nasa.gov/cgi/l3 Robert Frouin, Bryan Franz, and Menghua Wang. Algorithm to estimate PAR from SeaWiFS data Version 1.2 - Documentation. Chlorophyll-a Mean summer surface chlorophyll-a concentrations were calculated from the SeaWiFS summer means. We used the mean of the 1998-2004 summer values. Chlorophyll concentrations are expressed in mg/m^3. https://oceancolor.gsfc.nasa.gov/cgi/l3 Sea ice We calculated the mean fraction (0-1) of the year for which the ocean was covered by at least 15% sea ice. These calculations were based on satellite-derived estimates of sea ice concentration spanning 1979-2003. http://nsidc.org/data/nsidc-0079.html Comiso, J. (1999, updated 2005). Bootstrap sea ice concentrations for NIMBUS-7 SMMR and DMSP SSM/I. Boulder, CO, USA: National Snow and Ice Data Center. Digital media. Southern Ocean Fronts These are the front positions as published by Orsi et al. (1995). Orsi A, Whitworth T, III, Nowlin WD, Jr (1995) On the meridional extent and fronts of the Antarctic Circumpolar Current. Deep-Sea Research 42:641-673 Use of these data are governed by the following conditions: 1. The data are provided for non-commercial use only. 2. Any publication derived using the datasets should acknowledge the Australian Antarctic Data Centre as having provided the data and the original source (see the relevant metadata record listed in the description below for the proper citation).

High resolution digital aerial photography of Adelie penguin colonies, Davis Station, Heidemann Valley, and other various areas, LIDAR scanning of portions of the Vestfold Hills, Rauer Islands and sea ice in front of the Amery Ice Shelf, conducted from 2009/11/17 to 2009/11/23. Some of the aerial photography has been conducted in support of various AAS projects: AAS 3012 (ASAC_3012) AAS 2722 (ASAC_2722) AAS 1034 (ASAC_1034) AAS 3130 (ASAC_3130) A short list of the work carried out: - Long duration over water/sea ice flights for the purposes of "Investigation of physical and biological processes in the Antarctic sea ice zone during spring using in situ, aircraft and underwater observations". - Over-flights at 750m over specific islands in the Vestfold Hills and Rauer Islands known to hold Adelie colonies. - Transects of flights were performed over Davis station, at 500m altitude, taking photos and LIDAR measurements. - The evaluation of the APPLS equipment (camera, LIDAR, electronics, software) was performed and in parallel to the other tasks. - Production a digital elevation model of the Heidemann Bay Area. - Aerial photography / LIDAR of moss beds in the Vestfold Hills area. - The Marine Plain area, south east of Davis, was mapped using LIDAR and aerial imagery for the purposes of general Antarctic information. - The Vestfold Lakes, particularly Lake Druzby, Watts Lake, Lake Nicholson and Crooked Lake provide interesting aerial imagery. - The opportunity was taken to visit the plateau skiway (at 'Woop woop') and estimate the effort in opening the skiway later in the season. - Fly over and photograph the length of the resupply fuel hose from the AA to the shore. - The Russian 'Progress 1 and 2', and Chinese Zhong Shan stations were over flown and aerial imagery collected. Taken from the report: This document describes the results of the use of the APPLS (Aerial Photographic Pyrometer Laser System) at Davis during resupply 2009/2010 (November 17 to 24, 2009). This document is primarily for Science Technical Support use. Portions of the report can be used to provide information on the results obtained to other parts of AAD.