This vector contains the boundary and flight lines of Infill Area D. Infill Area D is part of the MinEx Collaborative Research Centre (CRC) Cobar Airborne Electromagnetic (AEM) survey. This survey was a collaboration between the Geological Survey of NSW (GSNSW) and Geoscience Australia. Infill D was funded by Legacy Minerals Pty. Ltd. Regional lines were funded by GSNSW.

Hydrogeochemistry is the sampling and analysis of water to test its chemical properties. The chemistry of bore water can provide clues to the properties of the underlying rocks it has flowed through. Hydrogeochemistry data provides useful information about the quality of groundwater and the processes affecting it. The data is useful for landholders and local government agencies in assessing groundwater resources and their suitability for human and animal consumption, and for industry, other government agencies and scientists to assist with targeting and assessment of natural resources in the earth’s crust. The hydrogeochemistry data presented here has been sourced from various entities including the Geological Survey of New South Wales (GSNSW), Water NSW, CSIRO, and Geoscience Australia (GA). GSNSW and GA collect hydrogeochemistry data on a project basis. CSIRO has curated a groundwater hydrochemistry dataset by collating and standardising data from most State and Territory lead water agencies. Data within NSW will be continually added to this dataset as it is collected or acquired by GSNSW in the future. The hydrogeochemistry dataset presented here includes the following data: • Field measurements and laboratory analyses, such as pH, electrical conductivity, and total dissolved solids (TDS, a measure of salinity) • Major and minor ions, such as sodium and calcium • Trace element metals and non-metals, such as gold, silver, copper and zinc • Stable and radioactive isotopes, such as oxygen-18, carbon-14, and sulphur-34 In addition to this, CSIRO has calculated variables such as saturation indices, which are derived from the hydrochemistry measurements. Information for methodologies used by CSIRO, including the saturation indices, is available from the CSIRO Research Publications Repository.

This layer shows the boundary of the AusLAMP NSW survey and the station locations. Data were acquired by a collaboration between GSNSW and Geoscience Australia. Data were used to create a 3D resistivity model of the crust from 10 km depth to 200 km depth.

Wind farms dataset displays the location of wind farms in NSW. Wind Farms contain wind turbines, which can be up to 200m tall.

Locations of geotechnical reports, plans and heritage documents compiled from NSW Public Works records. These reports are considered historic records.

Map blocks and map units are based on a system originally devised by the British Ordinance Survey. Each 1:1 million scale map sheet is subdivided into 3456 graticular map blocks, each measuring 5’ of latitude by 5’ of longitude. These map blocks are further subdivided into 25 1’ by 1’ map units. A map unit is approximately 3 square kilometres in size.

The NSW Seamless Geology Project was originally a five-year initiative of the Geological Survey of New South Wales which commenced in late 2013 and aimed to provide a statewide compilation of the best available digital geological mapping data in an internally consistent format. The overarching aims of the NSW Seamless Geology Project were to: (i) compile the different original scales, formats and rock unit naming conventions into a consistent, statewide format; (ii) edge-match the geology across existing map sheets; and (iii) interpret the basement geology under cover. The resulting geodatabase comprises a series of layers which include: (i) solid basement geology; (ii) cover rocks (defined as undeformed and unmetamorphosed); (iii) Mesozoic igneous rocks; and (iv) Cenozoic sedimentary and igneous rocks. Due to the size of the project, the work was divided into UTM zones, starting in the east with Zone 56, then moving west to Zone 54, and finishing with Zone 55. The western half of Zone 55 was completed in 2018, after which the results were merged with the previously completed Zones to produce version 1 of the NSW Seamless Geology dataset. Completion of this stage saw the end of phase 1 of the Seamless Geology Project, but it is intended that the Seamless Geology dataset will be continually updated and refined as new digital geological mapping data becomes available. Updates to the Seamless Geology dataset generally occur on an annual basis. Version 2.6 is the 8th major update to the NSW Seamless Geology and was released in 2026. This release includes major remapping of the northern Rockley–Gulgong Volcanic Belt; a significant upgrade to the mapping of Broughton Island; significant updates to the Lachlan Orogen and Cenozoic Sedimentary Province in the Canbelego 1:100,000 map sheet area; and attribute updates, data additions, and minor error fixes to all layers. Murray Basin During editing for version 2.1 of the Seamless Geology, the Cenozoic Murray Basin of southwest NSW was divided into its constituent units (formation or group level), with particular emphasis on the Loxton Sands, an economically significant unit containing numerous heavy mineral sand placer deposits and a number of mines producing rutile, zircon, and ilmenite. The Murray Basin linework was edited to reconcile the data with mapping in the existing NSW Seamless Geology dataset. See the lineage section for further details.

Pseudocolour image of the ratio between uranium and potassium within the upper 20 centimetres of the ground. This image was generated using normalised input grids to avoid ‘divide by zero’ errors. Cooler colours indicate lower abundances of uranium relative to potassium and warmer colours represent the opposite. Variations in U/K ratio are caused varied mineral compositions in host rocks and soils. This statewide image was generated by merging many individual airborne radiometric surveys.

This layer shows a depth slice from a 3D resistivity model of the crust derived from an inversion of the AusLAMP NSW long period MT data.