The Millennium Coral Reef Mapping Project provides thematic maps of coral reefs worldwide at geomorphological scale. Maps were created by photo-interpretation of Landsat 7 and Landsat 8 satellite images. Maps are provided as standard Shapefiles usable in GIS software. The geomorphological classification scheme is hierarchical and includes 5 levels. The GIS products include for each polygon a number of attributes. The 5 level geomorphological attributes are provided (numerical codes or text). The Level 1 corresponds to the differentiation between oceanic and continental reefs. Then from Levels 2 to 5, the higher the level, the more detailed the thematic classification is. Other binary attributes specify for each polygon if it belongs to terrestrial area (LAND attribute), and sedimentary or hard-bottom reef areas (REEF attribute). Examples and more details on the attributes are provided in the references cited. The products distributed here were created by IRD, in their last version. Shapefiles for 29 atolls of Australia as mapped by the Global coral reef mapping project at geomorphological scale using LANDSAT satellite data (L7 and L8). Global coral reef mapping project at geomorphological scale using LANDSAT satellite data (L7 and L8). Funded by National Aeronautics and Space Administration, NASA grants NAG5-10908 (University of South Florida, PIs: Franck Muller-Karger and Serge Andréfouët) and CARBON-0000-0257 (NASA, PI: Julie Robinson) from 2001 to 2007. Funded by IRD since 2003 (in kind, PI: Serge Andréfouët).

This software contains the v1.0.0 release of Nilas: the south ocean mapping platform (https://nilas.org). This mapping tool (beta) has been developed by the Australian Antarctic Division for the Antarctic sea-ice zone to support their research and operational activities. Nilas displays multiple layers of physical and biogeochemical variables. These variables are primarily derived from remotely sensed products and updated as source data become available. The source code is well documented with both readme files and inline comments. This application is written primarily in javascript and was developed using Node.js, vite and a small amount of vue. The Nilas platform was based on the Leaflet open source library. It can be configured to display other Antarctic related geospatial products including raster and vector data.

See the related record, "AAS_4506_NILAS_DATA" for data from this project.

This dataset is designed to be used as a "graticule layer", allowing a graticule to be drawn on maps when using software packages that don't support their generation in other ways. It consists of lines spaced at 1km intervals, running north-south (attributed with Easting) and east-west (attributed with Northing). It is applicable for use where an MGA graticule is required. Can be projected to provide AMG graticules over non-MGA data (eg Geographic or AMG). This dataset forms part of a series of graticule layers, one for each common projection.

Area layers of US, Australia, and Canada building footprints for use with GIS mapping software, databases, and web applications.

A legacy of over 500 paper maps records geological lineament analysis of Australia conducted by the late Tim O'Driscoll in Western Mining Corporation Exploration Division during the 1960s to 1980s. The lineament interpretations were used to target mineral exploration, famously including the analysis that led to the discovery of the Olympic Dam deposit in South Australia. Papers discussing the lineament approach are collected in Bourne & Twidale (2007). Lineaments were interpreted from a range of data available at the time, including magnetic and gravity maps, topography, standard geological maps, and 'chicken track'interpretation of aerial photographs and early satellite images. This product comprises high quality digital scans of 130 of the original paper maps, rectified and georeferenced for use in GIS software. Geoscience Australia reproduces these maps and makes them available publicly for their historic and scientific interest. The paper originals are held in the Geoscience Australia library.

The physical properties of non-porous basement rocks are directly related to the mineralogy of those rocks. The MineralMapper3D software package originally developed by Nick Williams at the Predictive Mineral Discovery Cooperative Research Centre (pmd*CRC), Geoscience Australia, uses the physical properties of minerals to provide bounds on estimates of the abundance of specified minerals in non-porous basement rocks. This approach is applicable to both estimates of density and magnetic susceptibility derived from 3D inversions of gravity and magnetic data as well as physical measurements on specimens or down-hole derived physical properties.

Abstract The Mineral Potential web service provides access to digital datasets used in the assessment of mineral potential in Australia. The service includes maps showing the potential for carbonatite-related rare earth element mineral systems in Australia. Maps showing the potential for carbonatite-related rare earth element (REE) mineral systems in Australia. Model 2 integrates four components: sources of metals, energy drivers, lithospheric architecture, and ore deposition. Supporting datasets including the input maps used to generate the mineral potential maps, an assessment criteria table that contains information on the map creation, and data uncertainty maps are available here Uncertainty Maps. The data uncertainty values range between 0 and 1, with higher uncertainty values being located in areas where more input maps are missing data or have unknown values. Map images provided in the extended abstract have the same colour ramp and equalised histogram stretch, plus a gamma correction of 0.5 not present in the web map service maps, which was applied using Esri ArcGIS Pro software. The extended abstract is avalable here Alkaline Rocks Atlas Legend

Currency Date modified: 16 August 2023 Next modification date: As Needed Data extent Spatial extent North: -9° South: -44° East: 154° West: 112° Source Information Catalog entry: Carbonatite-related rare earth element mineral potential maps Lineage Statement Product Created 20 April 2023 Product Published 16 August 2023 A large number of published datasets were individually transformed to summarise our current understanding of the spatial extents of key mineral system mappable criteria. These individual layers were integrated using statistically derived importance weightings combined with expert reliability weightings within a mineral system component framework to produce national-scale mineral potential assessments for Australian carbonatite-related rare earth element mineral systems. Contact Geoscience Australia, clientservices@ga.gov.au

The Revised Universal Soil Loss Equation (RUSLE) estimates the annual soil loss that is due to erosion using a factor-based approach with rainfall, soil erodibility, slope length, slope steepness and cover management and conservation practices as inputs. The collection is (i) a set of maps that represent the RUSLE factors, (ii) a map of the RUSLE estimates of soil erosion in Australia and (iii) a map of the uncertainty in the estimates of erosion. Lineage: The methods for the creation of these data sets are described in the following publication: Teng H, Viscarra Rossel RA, Shi Z, Behrens T, Chappell A and Bui E 2016 Assimilating satellite imagery and visible-near infrared spectroscopy to model and map soil loss by water erosion in Australia. Environmental Modelling & Software 77: 156-167.

Author: Joseph Kerski, post_secondary_educator, Esri and University of DenverGrade/Audience: high school, ap human geography, post secondary, professional developmentResource type: lessonSubject topic(s): population, maps, citiesRegion: africa, asia, australia oceania, europe, north america, south america, united states, worldStandards: All APHG population tenets. Geography for Life cultural and population geography standards. Objectives: 1. Understand how population change and demographic characteristics are evident at a variety of scales in a variety of places around the world. 2. Understand the whys of where through analysis of change over space and time. 3. Develop skills using spatial data and interactive maps. 4. Understand how population data is communicated using 2D and 3D maps, visualizations, and symbology. Summary: Teaching and learning about demographics and population change in an effective, engaging manner is enriched and enlivened through the use of web mapping tools and spatial data. These tools, enabled by the advent of cloud-based geographic information systems (GIS) technology, bring problem solving, critical thinking, and spatial analysis to every classroom instructor and student (Kerski 2003; Jo, Hong, and Verma 2016).

The eAtlas delivers its mapping products via two Web Mapping Services, a legacy server (from 2008-2011) and a newer primary server (2011+) to which all new content it added. This record describes the legacy WMS.

This service delivers map layers associated with the eAtlas project (http://eatlas.org.au), which contains map layers of environmental research focusing on the Great Barrier Reef. The majority of the layers corresponding to Glenn De'ath's interpolated maps of the GBR developed under the MTSRF program (2008-2010).

This web map service is predominantly maintained for the legacy eAtlas map viewer (http://maps.eatlas.org.au/geoserver/www/map.html). All the these legacy map layers are available through the new eAtlas mapping portal (http://maps.eatlas.org.au), however the legends have not been ported across.

This WMS is implemented using GeoServer version 1.7 software hosted on a server at the Australian Institute of Marine Science.

For ArcMap use the following steps to add this service: 1. "Add Data" then choose GIS Servers from the "Look in" drop down. 2. Click "Add WMS Server" then set the URL to "http://maps.eatlas.org.au/geoserver/wms?"

Note: this service has around 460 layers of which approximately half the layers correspond to Standard Error maps, which are WRONG (please ignore all *Std_Error layers.

This services is operated by the Australian Institute of Marine Science and co-funded by the MTSRF program.

The data on this CDROM is a digital re-production of the 1st edition 1990 geological outcrop map of the Quartz 1:100,000 map sheet 5951. A scanned image of the hardcopy map was digitised using Microstation and ArcInfo software. Digital standards are based on Geoscience Digital Data Dictionary for GIS Products Version 2004.01 for Geology and Lithology layers. The finished product has been provided as ArcView shapefiles and ArcInfo export files on CD-ROM. Internal quality assurance has been performed on the coverages. Stratigraphic nomenclature used is current as of June 15, 2005.

The eAtlas delivers its mapping products via two Web Mapping Services, a legacy server (from 2008-2011) and a newer primary server (2011+) to which all new content it added. This record describes the primary WMS.

This service delivers map layers associated with the eAtlas project (http://eatlas.org.au), which contains map layers of environmental research focusing on the Great Barrier Reef and its neighbouring coast, the Wet Tropics rainforests and Torres Strait. It also includes lots of reference datasets that provide context for the research data. These reference datasets are sourced mostly from state and federal agencies. In addition to this a number of reference basemaps and associated layers are developed as part of the eAtlas and these are made available through this service.

This services also delivers map layers associated with the Torres Strait eAtlas.

This web map service is predominantly set up and maintained for delivery of visualisations through the eAtlas mapping portal (http://maps.eatlas.org.au) and the Australian Ocean Data Network (AODN) portal (http://portal.aodn.org.au). Other portals are free to use this service with attribution, provided you inform us with an email so we can let you know of any changes to the service.

This WMS is implemented using GeoServer version 2.3 software hosted on a server at the Australian Institute of Marine Science. Associated with each WMS layer is a corresponding cached tiled service which is much faster then the WMS. Please use the cached version when possible.

The layers that are available can be discovered by inspecting the GetCapabilities document generated by the GeoServer. This XML document lists all the layers, their descriptions and available rendering styles. Most WMS clients should be able to read this document allowing easy access to all the layers from this service.

For ArcMap use the following steps to add this service: 1. "Add Data" then choose GIS Servers from the "Look in" drop down. 2. Click "Add WMS Server" then set the URL to "http://maps.eatlas.org.au/maps/wms?"

Note: this service has over 1000 layers and so retrieving the capabilities documents can take a while.

This services is operated by the Australian Institute of Marine Science and co-funded by the National Environmental Research Program Tropical Ecosystems hub.

The Digital Earth Australia (DEA) Coastlines Explorer application shows annual shorelines and rates of coastal change along the entire Australian coastline from 1988 to the present.The application uses satellite data from Geoscience Australia's DEA program and tidal modelling to map the shoreline at mean sea level for each year. It enables annual analysis of coastal retreat and growth at both local and national scales. Patterns of coastal change can be mapped historically and updated regularly as new data becomes available. This allows current rates of coastal change to be compared with those from previous years or decades.Mapping shoreline positions each year provides valuable insights into whether changes are caused by specific events or gradual processes. This information helps scientists, managers and policy makers assess the impacts of various coastal drivers impacting our coastlines and supports planning and forecasting for future scenarios.The DEA Coastlines Explorer application contains three layers:DEA Coastlines annual shorelinesDEA Coastlines rates of coastal changeDEA Coastlines coastal change hotspotsDEA Coastlines annual shorelinesThis layer shows the position of the Australian coastline each year since 1988. It represents the most typical location of the shoreline at mean sea level.Each year's coastline is shown as a line on the map. If the line is dashed, it means there is lower certainty in the accuracy of that year's data.DEA Coastlines rates of coastal changeThis layer provides robust rates of coastal change for every 30 m along Australia’s non-rocky coastlines. The most recent annual shoreline is used as a baseline for measuring rates of change.Points are shown where the rate of change is statistically significant (p-value ≤ 0.01) and data quality is high (certainty = "good"). Each point shows the annual rates of change (in metres per year) and an uncertainty estimate (95% confidence interval).For example, for a point labelled -10.0 m (±1.0 m) there is a 95% chance the shoreline is retreating at a rate between -9.0 and -11.0 metres per year.DEA Coastlines coastal change hotspotThis merged layer summarises coastal change within moving 1 km, 5 km, and 10 km windows along the coastline. This layer helps visualise regional and national patterns of coastal change.Each layer includes all attributes from the DEA Coastlines rates of coastal change dataset, plus additional attributes that highlight significant coastal change.For more information, visit the DEA Coastlines - DEA Knowledge Hub.Key FeaturesTimeline: To analyse and visualise temporal data patterns over multiple years.Bookmark: Feature to guide users through the data and insights. CurrencyDate modified: 15 July 2025Modification frequency: As needed. Refer to individual layers for layer currency. ChangelogVersion 1.0.1 (2025-10-09) ArcGIS Experience Builder app configured with the following: Filter drop downs on add data widget updated to new spatial data theme terminology Version 1.0.0 (2025-07-15)Experience Builder application created with the following features:LegendLayerAdd dataBasemapPrintShareBookmarksTimelineDrawSelectMeasureCoordinatesTable ContactDigital Earth Australia, earth.observation@ga.gov.au

PLEASE NOTE: These data do not include data over Tasmania. Please see links relevant to that area.

GEODATA TOPO 250K Series 3 is a vector representation of the major topographic features appearing on the 1:250,000 scale NATMAPs supplied in KML format and is designed for use in a range of commercial GIS software. Data is arranged within specific themes. All data is based on the GDA94 coordinate system.

GEODATA TOPO 250K Series 3 is available as a free download product in Personal Geodatabase, ArcView Shapefile or MapInfo TAB file formats. Each package includes data arranged in ten main themes - cartography, elevation, framework, habitation, hydrography, infrastructure, terrain, transport, utility and vegetation. Data is also available as GEODATA TOPO 250K Series 3 for Google Earth in kml format for use on Google Earth TM Mapping Service.

Product Specifications

Themes: Cartography, Elevation, Framework, Habitation, Hydrography, Infrastructure, Terrain, Transport, Utility and Vegetation

Coverage: National (Powerlines not available in South Australia)

Currency: Data has a currency of less than five years for any location

Coordinates: Geographical

Datum: Geocentric Datum of Australia (GDA94)

Formats: Personal Geodatabase, kml, Shapefile and MapInfo TAB

Release Date: 26 June 2006

This DVD contains:

1/ The movie "Revealing Australia's Hidden Secrets" (GeoCat No. 68258) - which tells the story of the making of the Radiometric Map of Australia.

2/ Geoscience Australia's World Wind Viewer Application - an application based on NASA's World Wind that allows users to view data such as Radioelements, Gravity and Magnetic Anomaly over the Australian Terrain with Satellite imagery.

The application is designed to work in standalone or offline mode - not connected to the internet - in which case it will show the Geoscience Australia data layers referenced below which are included on the DVD. When connected to the internet the application will display satellite imagery and terrain data and will cache this data to display when offline.

The application references: a/ RADIOMETRIC MAP OF AUSTRALIA - 2ND EDITION, 2010 - GeoCat No. 70791 b/ MAGNETIC ANOMALY MAP OF AUSTRALIA - 5TH EDITION, 2004 - GeoCat No. 70282 c/ GRAVITY ANOMALY MAP OF THE AUSTRALIAN REGION - 3RD EDITION, 2008 GeoCat No. 65682

Abstract This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied. This layer contains sun-shaded images of depth, isopach and two way time grids generated from seismic interpretation to the following horizons: Top Winton Formation, Base of Tertiary, Top Cadnaowie Formation, Top Hutton Sandstone, Base Eromanga Basin (also referred to as Top Cooper Basin), Top Nappamerri Group, Top or near Top Permian Sediments, Toolachee Formation, Top Daralingie Unconformity & Correlative Unconformities level, Top Daralingie Sandstone Sediments, Top Patchawarra Formation, Base Patchawarra Formation, Glacial Sediments of Tirrawarra Sandstone or Merrimelia Formation and Basement or Top Warburton Basin in the Cooper Basin area in the north-east of South Australia. These grids form part of a database of seismically mapped subsurface depth, isopach and time grids, contours, faults and polygons interpreted from seismic mapping over the Cooper Basin area. The sun-shaded seismic mapping images in this layer were created from Petrosys grids using ERMapper software. The image files (Georeferenced - TIFF format) are in GDA94 Geodetic projection. Depths are in metres below MSL datum. ## Dataset History These data sets are derived from well tops, seismic sections and some open file industry interpretations. Petrosys mapping and interpretation software were utilised for the entire project. Interpretations derived from basic seismic data, with some reference to open file industry and other data. Interpreted, compiled and edited by DMITRE. Final files produced by Energy Resources Division, DMITRE. ## Dataset Citation "SA Department for Manufacturing, Innovation, Trade, Resources and Energy" (2010) Cooper Basin Seismic Mapping Grids, South Australia. Bioregional Assessment Source Dataset. Viewed 27 November 2017, http://data.bioregionalassessments.gov.au/dataset/cdd1625e-64e1-41da-bff4-2e26d0fd4ad1.

The complete infilled K, eTh and eU grids are based on the Radiometric Map of Australia (radmapv4) 2019 (Poudjom Djomani and Minty, 2019a, b, c) with gaps in coverage infilled using environmental correlation machine learning prediction. The radiometric, or gamma-ray spectrometric method, measures the natural variations in the gamma-rays detected near the Earth's surface as the result of the natural radioactive decay of potassium (K), uranium (U) and thorium (Th). However because Uranium and Thorium abundances are calculated by measuring gamma emission associated with their daughter radionuclides they are typically expressed as equivalent eU and eTh. The 2019 radiometric grid is compiled from airborne geophysical surveys conducted by Commonwealth, State and Northern Territory Governments and the private sector. Over 600 airborne gamma-ray spectrometric surveys were merged and gridded to a cell size of approximately 100m (0.001 degrees) to produce the Radiometric Map of Australia (radmapv4) 2019.

Gamma-rays emitted from the surface mainly relate to the mineralogy and geochemistry of the bedrock and weathered materials or regolith. To infill gaps in the national gamma-ray grid (radmapv4 -2019) we have compiled a set of national covariates or predictive datasets that capture landscape processes, regolith and geology that are likely correlated to the distribution of K, eTh and eU at the surface. These datasets include satellite imagery (to map surface mineralogy and vegetation), terrain attributes (e.g. slope, relief), gravity (Lane et al, 2020) and surface geology. A boosted regression tree algorithm called XGBoost (open-source software library for gradient boosting machine learning) was used to train relationships between airborne estimates of K, eTh and eU with the covariate datasets. The training set used the Australia Wide Airborne Geophysical Survey (AWAGS) (Milligan et al., 2009). Local model predictions were generated for gaps in the 2019 version of the national grid by clipping subsets of the AWAGS survey lines and in places extracting additional training survey sites from nearby surveys. The strength of the correlations between the training observation and the covariates were highest in semi-arid areas with decreasing correlations from K through to eTh and eU. Modelled grids of K, eTh and eU were merged with the Radiometric Map of Australia (radmapv4 -2019) using the grid merge module in Intrepid Geophysics software. The first step was to scale the modelled dataset to the reference dataset, then apply a DC shift. The second step was to surface adjust the grid, which computes a two dimensional surface calculated from the differences in its value between the reference grid, it then fits a difference surface with the largest mean signal value and reiterates this process until the difference is within a pre-defined threshold. The third step is to merge the modelled dataset with the Radiometric Map of Australia (radmapv4) 2019, using a feathering process where measured radiometric values are ranked higher over the modelled data.


The complete infill radiometric grids have been generated for regolith (including soils) and geological mapping and can be used as a seamless dataset for predictive modelling using machine learning. The product can be seen as an interim dataset until the gaps are filled in through new airborne survey acquisition. It is important to recognise that the infill grids are based on correlations between airborne flight-line estimates of the radioelements and covariate thematic datasets. Responses and patterns observed within these gap areas are therefore not reflecting measurements using the airborne spectrometry. Equally, the covariate approach should not be expected to confidently identify gamma-ray ‘outliers’ or anomalies that have been used in other geophysical survey approaches.

Lane, R. J. L., Wynne, P. E., Poudjom Djomani, Y. H., Stratford, W. R., Barretto, J. A., and Caratori Tontini, F., 2020, 2019 Australian National Gravity Grids: Geoscience Australia, eCat Reference Number 133023, https://pid.geoscience.gov.au/dataset/ga/133023

Milligan, P., Minty, B., Richardson, M and Franklin, R. 2009 The Australia-Wide Airborne Geophysical Survey - accurate continental magnetic coverage, ASEG, Extended Abstracts, 2009:1, 1-9

Poudjom Djomani, Y., Minty, B.R.S. 2019a. Radiometric Grid of Australia (Radmap) v4 2019 unfiltered pct potassium. Geoscience Australia, eCat reference number 131978. http://dx.doi.org/10.26186/5dd4a7851e8db

Poudjom Djomani Y., Minty, B.R.S. 2019b. Radiometric Grid of Australia (Radmap) v4 2019 unfiltered ppm thorium. Geoscience Australia, ecat reference number 131988. http://dx.doi.org/10.26186/5dd4a821a334d

Poudjom Djomani, Y., Minty, B.R.S. 2019c. Radiometric Grid of Australia (Radmap) v4 2019 filtered ppm uranium. Geoscience Australia, eCat reference number 131974. http://dx.doi.org/10.26186/5dd48ee78c980

Wildfire Risk Mapping Software Market Outlook

According to our latest research, the wildfire risk mapping software market size reached USD 1.42 billion in 2024 globally. Demonstrating robust momentum, the market is expected to expand at a CAGR of 15.7% from 2025 to 2033, ultimately achieving a forecasted value of USD 5.3 billion by 2033. This rapid growth is primarily driven by the increasing frequency and severity of wildfires worldwide, escalating demand for advanced risk assessment tools, and the integration of artificial intelligence and geospatial analytics into wildfire management systems. As per our latest research, the wildfire risk mapping software market is poised to transform how governments, insurance companies, utilities, and forestry organizations prepare for and respond to wildfire threats over the coming decade.

One of the most significant growth drivers for the wildfire risk mapping software market is the alarming rise in wildfire incidents globally. Climate change has led to prolonged droughts, higher temperatures, and unpredictable weather patterns, all of which contribute to more frequent and intense wildfires. These environmental changes have put immense pressure on governments and organizations to adopt sophisticated risk management technologies. Wildfire risk mapping software leverages advanced data analytics, satellite imagery, and predictive modeling to provide real-time risk assessments, helping stakeholders make informed decisions regarding resource allocation, evacuation planning, and post-fire recovery. As wildfires increasingly threaten both rural and urban areas, the adoption of these technologies is seen as not just beneficial, but essential for public safety and environmental preservation.

Another crucial factor propelling market growth is the surge in regulatory requirements and insurance industry demands. Governments worldwide are implementing stricter mandates for wildfire risk assessment and mitigation, particularly in regions prone to catastrophic fires such as California, Australia, and Southern Europe. Insurance companies are also leveraging wildfire risk mapping software to accurately price policies, assess liabilities, and minimize financial losses. The ability of these solutions to integrate with Geographic Information Systems (GIS), weather forecasting, and historical fire data enables insurers and policymakers to proactively identify high-risk zones and implement preventive measures. This regulatory and commercial push is significantly accelerating the adoption of wildfire risk mapping software across a diverse range of end-users.

Technological advancements play a pivotal role in shaping the wildfire risk mapping software market. The integration of artificial intelligence, machine learning, and cloud-based platforms has revolutionized the capabilities of these solutions. Modern wildfire risk mapping software can now process vast datasets in real time, offering predictive insights and automated alerts to stakeholders. The growing adoption of drones and remote sensing technologies further enhances the accuracy and granularity of risk assessments. Moreover, the increasing availability of open-source geospatial data and APIs is fostering innovation and reducing entry barriers for new market entrants. These technological trends are expected to continue driving market expansion, as organizations seek more efficient and scalable solutions for wildfire risk management.

From a regional perspective, North America dominates the global wildfire risk mapping software market, accounting for the largest share in 2024. The region's leadership is attributed to frequent wildfire incidents in the United States and Canada, significant government investments in disaster management infrastructure, and a mature insurance sector. Europe follows closely, with growing adoption in Mediterranean countries and the implementation of EU-wide wildfire prevention policies. The Asia Pacific region is witnessing the fastest growth, driven by increasing wildfire activity in Australia, Southeast Asia, and parts of China, coupled with rising awareness about environmental sustainability. Latin America and the Middle East & Africa are also emerging as promising markets, fueled by expanding forestry management initiatives and international cooperation on wildfire mitigation.

Component Analysis

The component segment of the wildfire risk mapping software market is bifurcated into software and se

Digital Geology and Lithology maps of the Strangways Range Region in the eastern Arunta Region of the Northern Territory have been produced from a scanned image of the first edition map published by the Bureau of Mineral Resources in 1984. The image was digitised using Microstation and ArcInfo software, and attributed to meet standards for Version 2004.01 of the Geoscience Australia Digital Data Dictionary for GIS Produces as closely as possible. The finished product has been provided as ArcView shape files and ArcInfo export files on CD-ROM. Extensive internal quality assurance and quality control processes have been used to verify the data.