The Aboriginal Sites Decision Support Tool ASDST extends the Aboriginal Heritage Information Management System (AHIMS) by illustrating the potential distribution of site features recorded in AHIMS. ASDST was first developed in 2012 by the Office of Environment and Heritage (OEH) to support landscape planning of Aboriginal Heritage. The Tool produces a suite of raster GIS modelled outputs and is held in Esri GRID format. The first suite was published in 2016 as Version 7 at 100m resolution and in Lamberts Conic Conformal Projection (LCC). The current Version 7.5 was produced by the now Department of Planning, Industry and Environment (DPIE) in 2020 at 50m resolution in Geographic Coordinate System (GCS). Each layer covers the extent of NSW.

The suite of layers includes separate predictive layers for different Aboriginal site feature types. The feature codes used in layer naming conventions are:

• ALL = model for all feature types combined
• AFT = predicted likelihood for stone artefacts
• ART = predicted likelihood for rock art
• BUR = predicted likelihood of burials
• ETM = predicted likelihood of western mounds and shell
• GDG = predicted likelihood of grinding grooves
• HTH = predicted likelihood of hearths
• SHL = predicted likelihood of coastal middens
• STQ = predicted likelihood of stone quarries and
• TRE = predicted likelihood of scarred trees.

The feature models have been derived in two forms:

• The first form (“p1750XXX” where XXX denotes three letter feature code) predicts likelihood of feature distribution prior to European colonisation of NSW.

• The second form (“curr_XXX” where XXX denotes three letter feature code) predicts feature likelihood in the current landscape.

For both sets of feature likelihood layers, cell values range from 0 – 1000, where 0 indicates low likelihood and 1000 is high likelihood.

Please note the scale is likelihood and NOT probability. Likelihood is defined as a relative measure indicating the likelihood that a grid cell may contain the feature of interest relative to all other cells in the layer.

Additionally, there are other derived products as part of the suite. These are:

• drvd_imp = which is a model of accumulated impacts, derived by summing the difference between the pre colonisation and current version of all feature models. Cell values range from 0 – 1000, where 1000 is a high accumulated impact.

• drvd_rel = which is a model of the reliability of predictions based on an environmental distance algorithm that looks at recorded site density across the variables used in the models.

• drvd_srv = which is a survey priority map, which considers model reliability (data gap), current likelihood and accumulated impact. Cell values range from 0 – 1000 where 1000 indicates highest survey priority relative to the rest of the layer.

For more details see the technical reference on the ASDST website.

NB. Old layers with a suffix of “_v7” indicate they are part of ASDST Version 7 produced in 2016. The current models (Version 7.5) do not contain a version number in their name and will continue to be named generically in future versions for seamless access.

Updates applied to ASDST version 7.5

For all ASDST 7.5 data sets, the resolution was increased from a 100m cell to a 50m cell. All data sets were clipped and cleaned to a refined coastal mask. Cell gaps in the mask were filled using a Nibble algorithm. The pre-settlement data sets were derived by resampling the version 7 pre-settlement data sets to 50m cell size. The present-day data sets were derived from the version 7.5 pre-settlement layers and 2017-18 land-use mapping and applying the same version 7 parameters for estimating the preservation of each feature type on each land-use. For version 7.5, the model reliability data set was derived by resampling the version 7 data set to 50m cell size. Accumulated impact and survey priority version 7.5 data sets were derived by applying the version 7 processing algorithm but substituting the version 7.5 pre-settlement and present-day ASDST models.

The Soil and Land Information System (SALIS) of New South Wales (NSW) provides a substantial database of information on soils, landscapes, and other geographic features, and is used by the NSW Government, other organizations and individuals to improve planning and decision-making for natural resource management. SALIS contains: (1) physical and chemical soil profile data from more than 70,000 points across NSW; AND (2) several soil map data sets, including the NSW Soil Landscapes (based on 1:100,000 or 1:250,000 map tiles), NSW Soil and Land Resources (seamless coverages based on major catchment areas), and Land Systems of Western NSW. Data users can access soil and land information from SALIS free-of-charge using the eSPADE spatial viewer system, which provides access to both soil profile and soil map information from SALIS and other sources. Digital spatial soil data are also accessible from the NSW Office of Environment and Heritage (OEH) data download site. The SALIS database is constantly updated as new information on the State's soil resources becomes available.

Access API NSW Elevation and Depth Theme – Spot Heights Please Note WGS 84 service aligned to GDA94 This dataset has spatial reference [WGS 84 ≈ GDA94] which may result in misalignments when viewed in GDA2020 environments. A similar service with a ‘multiCRS’ suffix is available which can support GDA2020, GDA94 and WGS 84 ≈ GDA2020 environments. In due course, and allowing time for user feedback and testing, it is intended that the original service name will adopt the new multiCRS functionality. Metadata Portal Metadata Information Content TitleNSW Elevation and Depth Theme - Spot HeightContent TypeHosted Feature LayerDescriptionSpot Height is a point feature class representing individual points on the earth’s surface, the elevation of which has been related to a datum by ground or photogrammetric survey. It is a part of the NSW Elevation Theme.Elevation and Depth provides an authoritative digital representation of the Earth’s surface enabling evidence based decision making, policy development and an essential reference to other foundation datasets.Elevation and Depth underpins:Safe hydrographic, aeronautical and road navigationClimate science, including climate change adaptationEmergency management and natural hazard risk assessmentEnvironmental, including water managementDefinition of maritime and administrative boundariesDefence and national securityNatural resource exploration and exploitationData is as initially captured at 1:25 000, 1:50 000 and 1:100 000 scales from stereoscopic aerial photography.Initial Publication Date10/02/2020Data Currency01/01/3000Data Update FrequencyOtherContent SourceData provider filesFile TypeESRI File Geodatabase (*.gdb)Attribution© State of New South Wales (Spatial Services, a business unit of the Department of Customer Service NSW). For current information go to spatial.nsw.gov.auData Theme, Classification or Relationship to other DatasetsNSW Elevation and Depth Theme of the Foundation Spatial Data Framework (FSDF)AccuracyThis dataset was captured by utilising the best available source at a variety of scales and accuracies, ranging from 1:500 to 1:250 000 according to the National Mapping Council of Australia, Standards of Map Accuracy (1975). Therefore, the position of the feature instance will be within 0.5mm at map scale for 90% of the well-defined points. That is, 1:500 = 0.25m, 1:2000 = 1m, 1:4000 = 2m, 1:25000 = 12.5m, 1:50000 = 25m and 1:100000 = 50m. A program to upgrade the spatial location and accuracy of data is ongoing. Spatial Accuracy Horizontal: +/-1.25 @95% Confidence IntervalSpatial Accuracy Vertical: +/-0.9 @95% Confidence IntervalCalibration certification (Manufacturer/Cert. Company): DCS, Spatial Services.Spatial Reference System (dataset)GDA94Spatial Reference System (web service)EPSG:3857WGS84 Equivalent ToGDA94Spatial ExtentFull StateContent LineageFor additional information, please contact us via the Spatial Services Customer HubData ClassificationUnclassifiedData Access PolicyOpenData QualityFor additional information, please contact us via the Spatial Services Customer HubTerms and ConditionsCreative CommonsStandard and SpecificationAS/NZS ISO 19115 - ANZLIC Metadata Profile Version 1.1AS/NZS ISO 19131:2008 Geographic Information - Data product specificationsOGC compliant Web Map Services (WMS) and Web Feature Services (WFS)Metadata for the relevant Spatial Services datasets complies with AS/NZS ISO 19115-2, ANZLIC Metadata Profile v1.1 and ISO 19139 Intergovernmental Committee on Surveying and Mapping (ICSM): Guidelines for Digital Elevation DataDCS Spatial Services: Elevation Data Products Specification and Description (LiDAR)DCS Spatial Services: Elevation Data Products Specification and Description (Airborne Photogrammetry) Data CustodianDCS Spatial Services346 Panorama Ave Bathurst NSW 2795Point of ContactPlease contact us via the Spatial Services Customer HubData AggregatorDCS Spatial Services346 Panorama Ave Bathurst NSW 2795Data DistributorDCS Spatial Services346 Panorama Ave Bathurst NSW 2795Additional Supporting InformationData DictionariesTRIM Number

This data package contains three airborne geophysical datasets that have been acquired and processed from the Lower Macquarie River TEMPEST AEM survey flown in 2007, located to the north-west of Dubbo in the Central West region of New South Wales. The datasets are: a new Geoscience Australia layered earth inversion (GA-LEI) of the 2007 Lower Macquarie River TEMPEST Airborne Electromagnetic (AEM) survey; an airborne magnetic survey; and a digital elevation model (DEM). These data include enhancements of previously available datasets using more recent geophysical processing software advances.

This metadata briefly describes the contents of the data package. The user guide included in the package contains more detailed information about the individual datasets and available technical reports.

The AEM dataset comprises the final Geoscience Australia layered earth inversion (GA-LEI) of the Lower Macquarie River TEMPEST AEM survey data, produced in 2008. The main data products from the GA-LEI inversion are: point located inversion output data; horizontal layer conductivity grids below ground surface; horizontal conductivity-depth slice grids of various regular depth intervals below ground surface; vertical conductivity-depth sections along each flight line; AEM survey outline and flight line vector GIS data; and borehole comparison logs. The GA-LEI AEM data are derived from the 'Lower Macquarie River TEMPEST AEM Survey, NSW, 2007 Final Data (P1140)', available as Geoscience Australia product number 67211 (GeoCat #67211). The GA-LEI has been demonstrated to generate more accurate conductivity predictions than other algorithms for similar TEMPEST surveys.

The airborne magnetics and DEM data in this data package includes the corresponding data from GeoCat #67211, with additional raster and image formats to facilitate accessibility on a range of geographic information system platforms.

The point located data are stored in ASCII files (.asc) formatted with space-delimited columns with an associated comprehensive header (.hdr) file. The gridded data are stored in ER Mapper and ESRI grid formats as binary floating point raster grid files. The image data are stored in GeoTIFF format with associated world (.tfw) files and (.png) legends. The vector data are stored in ESRI shapefiles (.shp) Technical reports are stored in Portable Document Format (.pdf). The datasets are compressed in ZIP files.

The TEMPEST time domain airborne electromagnetic (AEM) survey was flown by Fugro Airborne Surveys over the Lower Macquarie River catchment in 2007. The survey was commissioned by the Australian Government Department of Agriculture, Fisheries and Forestry through the Bureau of Rural Sciences (BRS), now known as the Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) and funded under the National Action Plan for Salinity and Water Quality. Geoscience Australia (GA) provided several geophysical services in relation to the survey including survey planning, technical system selection, data quality control and layer earth inversion of the resultant data. Format conversion of the magnetics and DEM data in this product was performed by ABARES from data provided by GA.

Export Data Access API NSW Elevation and Depth Theme – Relative Heights Please Note WGS 84 service aligned to GDA94 This dataset has spatial reference [WGS 84 ≈ GDA94] which may result in misalignments when viewed in GDA2020 environments. A similar service with a ‘multiCRS’ suffix is available which can support GDA2020, GDA94 and WGS 84 ≈ GDA2020 environments. In due course, and allowing time for user feedback and testing, it is intended that the original service name will adopt the new multiCRS functionality. Metadata Portal Metadata Information Content TitleNSW Elevation and Depth ThemeContent TypeHosted Feature LayerDescriptionRelative Height is a point feature class representing relative heights of a vertical face of a cliff.Elevation and Depth provides an authoritative digital representation of the Earth’s surface enabling evidence based decision making, policy development and an essential reference to other foundation datasets.Elevation and Depth underpins:Safe hydrographic, aeronautical and road navigationClimate science, including climate change adaptationEmergency management and natural hazard risk assessmentEnvironmental, including water managementDefinition of maritime and administrative boundariesDefence and national securityNatural resource exploration and exploitationData is as initially captured at 1:25 000, 1:50 000 and 1:100 000 scales from stereoscopic aerial photography.Initial Publication Date03/02/2020Data Currency01/01/3000Data Update FrequencyOtherContent SourceData provider filesFile TypeESRI File Geodatabase (*.gdb)Attribution© State of New South Wales (Spatial Services, a business unit of the Department of Customer Service NSW). For current information go to spatial.nsw.gov.auData Theme, Classification or Relationship to other DatasetsNSW Elevation and Depth Theme of the Foundation Spatial Data Framework (FSDF)AccuracyThis dataset was captured by utilising the best available source at a variety of scales and accuracies, ranging from 1:500 to 1:250 000 according to the National Mapping Council of Australia, Standards of Map Accuracy (1975). Therefore, the position of the feature instance will be within 0.5mm at map scale for 90% of the well-defined points. That is, 1:500 = 0.25m, 1:2000 = 1m, 1:4000 = 2m, 1:25000 = 12.5m, 1:50000 = 25m and 1:100000 = 50m. A program to upgrade the spatial location and accuracy of data is ongoing. Spatial Accuracy Horizontal: +/-1.25 @95% Confidence IntervalSpatial Accuracy Vertical: +/-0.9 @95% Confidence IntervalCalibration certification (Manufacturer/Cert. Company): DCS, Spatial Services.Spatial Reference System (dataset)GDA94Spatial Reference System (web service)EPSG:3857WGS84 Equivalent ToGDA94Spatial ExtentFull StateContent LineageFor additional information, please contact us via the Spatial Services Customer HubData ClassificationUnclassifiedData Access PolicyOpenData QualityFor additional information, please contact us via the Spatial Services Customer HubTerms and ConditionsCreative CommonsStandard and SpecificationAS/NZS ISO 19115 - ANZLIC Metadata Profile Version 1.1AS/NZS ISO 19131:2008 Geographic Information - Data product specificationsOGC compliant Web Map Services (WMS) and Web Feature Services (WFS)Metadata for the relevant Spatial Services datasets complies with AS/NZS ISO 19115-2, ANZLIC Metadata Profile v1.1 and ISO 19139 Intergovernmental Committee on Surveying and Mapping (ICSM): Guidelines for Digital Elevation DataDCS Spatial Services: Elevation Data Products Specification and Description (LiDAR)DCS Spatial Services: Elevation Data Products Specification and Description (Airborne Photogrammetry) Data CustodianDCS Spatial Services346 Panorama Ave Bathurst NSW 2795Point of ContactPlease contact us via the Spatial Services Customer HubData AggregatorDCS Spatial Services346 Panorama Ave Bathurst NSW 2795Data DistributorDCS Spatial Services346 Panorama Ave Bathurst NSW 2795Additional Supporting InformationData DictionariesTRIM Number

Access API NSW Elevation and Depth Theme – 10m Historical Contours Please Note WGS 84 service aligned to GDA94 This dataset has spatial reference [WGS 84 ≈ GDA94] which may result in misalignments when viewed in GDA2020 environments. A similar service with a ‘multiCRS’ suffix is available which can support GDA2020, GDA94 and WGS 84 ≈ GDA2020 environments. In due course, and allowing time for user feedback and testing, it is intended that the original service name will adopt the new multiCRS functionality. Metadata Portal Metadata InformationContent TitleNSW Elevation and Depth Theme - 10M Historical ContoursContent TypeHosted Feature LayerDescription10m Historical Contours are virtual imaginary lines on the ground, joining points of an equal elevation.10m Historical Contours were captured in a verity of methods and scales, initially captured at 1:25 000, 1:50 000 and 1:100 000 scales from stereoscopic aerial photography or Ortho image trace methods.These contours were digitised into the vector data product over a number of years with the processing being completed 2003 through to 2017.Feature reliability date of the original contours rage from 1971 through to 2008.Contours are virtual imaginary lines on the ground, joining points of an equal elevation in relation to the Australian Height Datum (AHD). A contour can be a standard contour, depression contour or an ancillary contour. It is a part of the NSW Elevation and Depth Theme.Elevation and Depth provides an authoritative digital representation of the Earth’s surface enabling evidence based decision making, policy development and an essential reference to other foundation datasets.Elevation and Depth underpins:Safe hydrographic, aeronautical and road navigationClimate science, including climate change adaptationEmergency management and natural hazard risk assessmentEnvironmental, including water managementDefinition of maritime and administrative boundariesDefense and national securityNatural resource exploration and exploitation Initial Publication Date03/02/2020Data Currency01/01/3000Data Update FrequencyOtherContent SourceData provider filesFile TypeESRI File Geodatabase (*.gdb)Attribution© State of New South Wales (Spatial Services, a business unit of the Department of Customer Service NSW). For current information go to spatial.nsw.gov.auData Theme, Classification or Relationship to other DatasetsNSW Elevation and Depth Theme of the Foundation Spatial Data Framework (FSDF)AccuracyThis dataset was captured by utilising the best available source at a variety of scales and accuracies, ranging from 1:500 to 1:250 000 according to the National Mapping Council of Australia, Standards of Map Accuracy (1975). Therefore, the position of the feature instance will be within 0.5mm at map scale for 90% of the well-defined points. That is, 1:500 = 0.25m, 1:2000 = 1m, 1:4000 = 2m, 1:25000 = 12.5m, 1:50000 = 25m and 1:100000 = 50m. A program to upgrade the spatial location and accuracy of data is ongoing. Spatial Reference System (dataset)GDA94Spatial Reference System (web service)EPSG:3857WGS84 Equivalent ToGDA94Spatial ExtentFull StateContent LineageFor additional information, please contact us via the Spatial Services Customer HubData ClassificationUnclassifiedData Access PolicyOpenData QualityFor additional information, please contact us via the Spatial Services Customer HubTerms and ConditionsCreative CommonsStandard and SpecificationAS/NZS ISO 19115 - ANZLIC Metadata Profile Version 1.1AS/NZS ISO 19131:2008 Geographic Information - Data product specificationsOGC compliant Web Map Services (WMS) and Web Feature Services (WFS)Metadata for the relevant Spatial Services datasets complies with AS/NZS ISO 19115-2, ANZLIC Metadata Profile v1.1 and ISO 19139 Intergovernmental Committee on Surveying and Mapping (ICSM): Guidelines for Digital Elevation DataDCS Spatial Services: Elevation Data Products Specification and Description (LiDAR)DCS Spatial Services: Elevation Data Products Specification and Description (Airborne Photogrammetry) Data CustodianDCS Spatial Services346 Panorama Ave Bathurst NSW 2795Point of ContactPlease contact us via the Spatial Services Customer HubData AggregatorDCS Spatial Services346 Panorama Ave Bathurst NSW 2795Data DistributorDCS Spatial Services346 Panorama Ave Bathurst NSW 2795Additional Supporting InformationData DictionariesTRIM Number

The Aboriginal Sites Decision Support Tool ASDST extends the Aboriginal Heritage Information Management System (AHIMS) by illustrating the potential distribution of site features recorded in AHIMS. ASDST was first developed in 2012 by the Office of Environment and Heritage (OEH) to support landscape planning of Aboriginal Heritage. The Tool produces a suite of raster GIS modelled outputs and is held in Esri GRID format. The first suite was published in 2016 as Version 7 at 100m resolution and in Lamberts Conic Conformal Projection (LCC). The current Version 7.5 was produced by the now Department of Planning, Industry and Environment (DPIE) in 2020 at 50m resolution in Geographic Coordinate System (GCS). Each layer covers the extent of NSW.

The suite of layers includes separate predictive layers for different Aboriginal site feature types. The feature codes used in layer naming conventions are:

• ALL = model for all feature types combined
• AFT = predicted likelihood for stone artefacts
• ART = predicted likelihood for rock art
• BUR = predicted likelihood of burials
• ETM = predicted likelihood of western mounds and shell
• GDG = predicted likelihood of grinding grooves
• HTH = predicted likelihood of hearths
• SHL = predicted likelihood of coastal middens
• STQ = predicted likelihood of stone quarries and
• TRE = predicted likelihood of scarred trees.

The feature models have been derived in two forms:

• The first form (“p1750XXX” where XXX denotes three letter feature code) predicts likelihood of feature distribution prior to European colonisation of NSW.

• The second form (“curr_XXX” where XXX denotes three letter feature code) predicts feature likelihood in the current landscape.

For both sets of feature likelihood layers, cell values range from 0 – 1000, where 0 indicates low likelihood and 1000 is high likelihood.

Please note the scale is likelihood and NOT probability. Likelihood is defined as a relative measure indicating the likelihood that a grid cell may contain the feature of interest relative to all other cells in the layer.

Additionally, there are other derived products as part of the suite. These are:

• drvd_imp = which is a model of accumulated impacts, derived by summing the difference between the pre colonisation and current version of all feature models. Cell values range from 0 – 1000, where 1000 is a high accumulated impact.

• drvd_rel = which is a model of the reliability of predictions based on an environmental distance algorithm that looks at recorded site density across the variables used in the models.

• drvd_srv = which is a survey priority map, which considers model reliability (data gap), current likelihood and accumulated impact. Cell values range from 0 – 1000 where 1000 indicates highest survey priority relative to the rest of the layer.

For more details see the technical reference on the ASDST website.

NB. Old layers with a suffix of “_v7” indicate they are part of ASDST Version 7 produced in 2016. The current models (Version 7.5) do not contain a version number in their name and will continue to be named generically in future versions for seamless access.

Updates applied to ASDST version 7.5

For all ASDST 7.5 data sets, the resolution was increased from a 100m cell to a 50m cell. All data sets were clipped and cleaned to a refined coastal mask. Cell gaps in the mask were filled using a Nibble algorithm. The pre-settlement data sets were derived by resampling the version 7 pre-settlement data sets to 50m cell size. The present-day data sets were derived from the version 7.5 pre-settlement layers and 2017-18 land-use mapping and applying the same version 7 parameters for estimating the preservation of each feature type on each land-use. For version 7.5, the model reliability data set was derived by resampling the version 7 data set to 50m cell size. Accumulated impact and survey priority version 7.5 data sets were derived by applying the version 7 processing algorithm but substituting the version 7.5 pre-settlement and present-day ASDST models.

The Aboriginal Sites Decision Support Tool ASDST extends the Aboriginal Heritage Information Management System (AHIMS) by illustrating the potential distribution of site features recorded in AHIMS. Show full descriptionThe Aboriginal Sites Decision Support Tool ASDST extends the Aboriginal Heritage Information Management System (AHIMS) by illustrating the potential distribution of site features recorded in AHIMS. ASDST was first developed in 2012 by the Office of Environment and Heritage (OEH) to support landscape planning of Aboriginal Heritage. The Tool produces a suite of raster GIS modelled outputs and is held in Esri GRID format. The first suite was published in 2016 as Version 7 at 100m resolution and in Lamberts Conic Conformal Projection (LCC). The current Version 7.5 was produced by the now Department of Planning, Industry and Environment (DPIE) in 2020 at 50m resolution in Geographic Coordinate System (GCS). Each layer covers the extent of NSW. The suite of layers includes separate predictive layers for different Aboriginal site feature types. The feature codes used in layer naming conventions are: ALL = model for all feature types combined AFT = predicted likelihood for stone artefacts ART = predicted likelihood for rock art BUR = predicted likelihood of burials ETM = predicted likelihood of western mounds and shell GDG = predicted likelihood of grinding grooves HTH = predicted likelihood of hearths SHL = predicted likelihood of coastal middens STQ = predicted likelihood of stone quarries and TRE = predicted likelihood of scarred trees. The feature models have been derived in two forms: The first form (“p1750XXX” where XXX denotes three letter feature code) predicts likelihood of feature distribution prior to European colonisation of NSW. The second form (“curr_XXX” where XXX denotes three letter feature code) predicts feature likelihood in the current landscape. For both sets of feature likelihood layers, cell values range from 0 – 1000, where 0 indicates low likelihood and 1000 is high likelihood. Please note the scale is likelihood and NOT probability. Likelihood is defined as a relative measure indicating the likelihood that a grid cell may contain the feature of interest relative to all other cells in the layer. Additionally, there are other derived products as part of the suite. These are: drvd_imp = which is a model of accumulated impacts, derived by summing the difference between the pre colonisation and current version of all feature models. Cell values range from 0 – 1000, where 1000 is a high accumulated impact. drvd_rel = which is a model of the reliability of predictions based on an environmental distance algorithm that looks at recorded site density across the variables used in the models. drvd_srv = which is a survey priority map, which considers model reliability (data gap), current likelihood and accumulated impact. Cell values range from 0 – 1000 where 1000 indicates highest survey priority relative to the rest of the layer. For more details see the technical reference on the ASDST website. NB. Old layers with a suffix of “_v7” indicate they are part of ASDST Version 7 produced in 2016. The current models (Version 7.5) do not contain a version number in their name and will continue to be named generically in future versions for seamless access. Updates applied to ASDST version 7.5 For all ASDST 7.5 data sets, the resolution was increased from a 100m cell to a 50m cell. All data sets were clipped and cleaned to a refined coastal mask. Cell gaps in the mask were filled using a Nibble algorithm. The pre-settlement data sets were derived by resampling the version 7 pre-settlement data sets to 50m cell size. The present-day data sets were derived from the version 7.5 pre-settlement layers and 2017-18 land-use mapping and applying the same version 7 parameters for estimating the preservation of each feature type on each land-use. For version 7.5, the model reliability data set was derived by resampling the version 7 data set to 50m cell size. Accumulated impact and survey priority version 7.5 data sets were derived by applying the version 7 processing algorithm but substituting the version 7.5 pre-settlement and present-day ASDST models.

The Aboriginal Sites Decision Support Tool ASDST extends the Aboriginal Heritage Information Management System (AHIMS) by illustrating the potential distribution of site features recorded in AHIMS. ASDST was first developed in 2012 by the Office of Environment and Heritage (OEH) to support landscape planning of Aboriginal Heritage. The Tool produces a suite of raster GIS modelled outputs and is held in Esri GRID format. The first suite was published in 2016 as Version 7 at 100m resolution and in Lamberts Conic Conformal Projection (LCC). The current Version 7.5 was produced by the now Department of Planning, Industry and Environment (DPIE) in 2020 at 50m resolution in Geographic Coordinate System (GCS). Each layer covers the extent of NSW.

The suite of layers includes separate predictive layers for different Aboriginal site feature types. The feature codes used in layer naming conventions are:

• ALL = model for all feature types combined
• AFT = predicted likelihood for stone artefacts
• ART = predicted likelihood for rock art
• BUR = predicted likelihood of burials
• ETM = predicted likelihood of western mounds and shell
• GDG = predicted likelihood of grinding grooves
• HTH = predicted likelihood of hearths
• SHL = predicted likelihood of coastal middens
• STQ = predicted likelihood of stone quarries and
• TRE = predicted likelihood of scarred trees.

The feature models have been derived in two forms:

• The first form (“p1750XXX” where XXX denotes three letter feature code) predicts likelihood of feature distribution prior to European colonisation of NSW.

• The second form (“curr_XXX” where XXX denotes three letter feature code) predicts feature likelihood in the current landscape.

For both sets of feature likelihood layers, cell values range from 0 – 1000, where 0 indicates low likelihood and 1000 is high likelihood.

Please note the scale is likelihood and NOT probability. Likelihood is defined as a relative measure indicating the likelihood that a grid cell may contain the feature of interest relative to all other cells in the layer.

Additionally, there are other derived products as part of the suite. These are:

• drvd_imp = which is a model of accumulated impacts, derived by summing the difference between the pre colonisation and current version of all feature models. Cell values range from 0 – 1000, where 1000 is a high accumulated impact.

• drvd_rel = which is a model of the reliability of predictions based on an environmental distance algorithm that looks at recorded site density across the variables used in the models.

• drvd_srv = which is a survey priority map, which considers model reliability (data gap), current likelihood and accumulated impact. Cell values range from 0 – 1000 where 1000 indicates highest survey priority relative to the rest of the layer.

For more details see the technical reference on the ASDST website.

NB. Old layers with a suffix of “_v7” indicate they are part of ASDST Version 7 produced in 2016. The current models (Version 7.5) do not contain a version number in their name and will continue to be named generically in future versions for seamless access.

Updates applied to ASDST version 7.5

For all ASDST 7.5 data sets, the resolution was increased from a 100m cell to a 50m cell. All data sets were clipped and cleaned to a refined coastal mask. Cell gaps in the mask were filled using a Nibble algorithm. The pre-settlement data sets were derived by resampling the version 7 pre-settlement data sets to 50m cell size. The present-day data sets were derived from the version 7.5 pre-settlement layers and 2017-18 land-use mapping and applying the same version 7 parameters for estimating the preservation of each feature type on each land-use. For version 7.5, the model reliability data set was derived by resampling the version 7 data set to 50m cell size. Accumulated impact and survey priority version 7.5 data sets were derived by applying the version 7 processing algorithm but substituting the version 7.5 pre-settlement and present-day ASDST models.

Access API Access 5m DEM Service Access NSW Elevation Service Access ELVIS PlatformNSW Elevation and Depth Theme Please Note WGS 84 service aligned to GDA94 This dataset has spatial reference [WGS …Show full description Access API Access 5m DEM Service Access NSW Elevation Service Access ELVIS PlatformNSW Elevation and Depth Theme Please Note WGS 84 service aligned to GDA94 This dataset has spatial reference [WGS 84 ≈ GDA94] which may result in misalignments when viewed in GDA2020 environments. A similar service with a ‘multiCRS’ suffix is available which can support GDA2020, GDA94 and WGS 84 ≈ GDA2020 environments. In due course, and allowing time for user feedback and testing, it is intended that the original service name will adopt the new multiCRS functionally.Elevation and Depth is the measurement of the Earth’s surface above or below a vertical datum to obtain the height of the land. Data is collected using a range of sensors including: laser, sonar, radar and optical. Technical methodologies are used to derive spot heights, raster surfaces, contours, triangulated irregular networks and digital elevation models. Datasets that form the Elevation and Depth theme include: Historical Contours (2m Urban, 10m and 20m) Current 2m Contours (State wide) Spot Heights Relative Heights Point cloud (LiDAR and Photogrammetrically derived) (available for download from Geoscience Australia ELVIS Platform) Digital Elevation Model (available for download from Geoscience Australia ELVIS Platform)Point Clouds - The point cloud data set consists of point clouds captured from LiDAR (Light Detection and Ranging) and derived from airborne imagery using photogrammetric techniques. Spatial Services Point Cloud data is available for on demand download from Geoscience Australia ELVIS Platform. Digital Elevation Models - Digital Elevation Models (DEM) are derived from Spatial Services’ (SS) point cloud data. The DEM is a bare earth representation of the earth’s surface where all the above ground feature has been removed. Spatial Services have a number of different Digital Elevation Models Digital Elevation Model derived from LiDARAre 1m or 2m resolution and is not hydrologically enforced (breaklines) or hydrologically conditioned (identification andanalysis of sinks). Digital Elevation Model derived Photogrammetry Data is 5m resolution. Areas of no data caused by steep slopes, shadow and vegetation have been interpolated or filled-in with another data source and will not be as accurate as the bare open ground areas. The data is not hydrologically enforced (breaklines) or hydrologically conditioned (identification and analysis of sinks).Spatial Services Digital Elevation Model data is available for on demand download from. Geoscience Australia ELVIS Platform as 2km x 2km tiles. You can also access the NSW 5 Metre Digital Elevation Model Service in the Spatial Collaboration Portal: Elevation and Depth provides an accurate representation of the Earth’s surface enabling evidence-based decision making, 3D modelling, planning and earth surface representation. Elevation and Depth underpins: · Safe hydrographic· Aeronautical and road navigation· Climate science, including climate change adaptation· Emergency management and natural hazard risk assessment· Environmental, including water management· Engineering projects and infrastructure development· Definition of maritime and administrative boundaries· Natural resource exploration Update frequencies vary for each dataset. Individual current status can be found under each Spatial data profile. The objective is to maintain elevation datasets to meet the FDSI requirements of key data users. Current programs include:· Aerial LiDAR capture program across NSW.· DEM and Point Cloud generation from photogrammetric techniques. Longer term programs include:· Update of contour data using updated DEM data generated from LiDAR and Photogrammetry.· Hydrological enforcement using improved surface models. MetadataType Esri Map ServiceUpdate Frequency As required Contact Details Contact us via the Spatial Services Customer Hub Relationship to Themes and Datasets Elevation and Depth Theme of the Foundation Spatial Data FrameworkAccuracy The dataset maintains a positional relationship to, and alignment with, the drainage and topographic digital datasets. these data sets were captured primarily by digitising from the best available aerial photography at scales and accuracies, ranging from 1:500 to 1:250 000 according to the National Mapping Council of Australia, Standards of Map Accuracy (1975). Therefore, the position of the feature instance will be within 0.5mm at map scale for 90% of the well-defined points. That is, 1:500 = 0.25m, 1:2000 = 1m, 1:4000 = 2m, 1:25000 = 12.5m, 1:50000 = 25m and 1:100000 = 50m. A program of positional upgrade (accuracy improvement) is currently underway.Spatial Reference System (dataset) Geocentric Datum of Australia 1994 (GDA94), Australian Height Datum (AHD) Spatial Reference System    (web service) EPSG 4326: WGS 84 Geographic 2D WGS 84 Equivalent ToGDA94 Spatial Extent Full State Standards and Specifications AS/NZS ISO 19115 - ANZLIC Metadata Profile Version 1.1AS/NZS ISO 19131:2008 Geographic Information - Data product specificationsOGC compliant Web Map Services (WMS) and Web Feature Services (WFS) Metadata for the relevant Spatial Services datasets complies with AS/NZS ISO 19115-2, ANZLIC Metadata Profile v1.1 and ISO 19139 Intergovernmental Committee on Surveying and Mapping (ICSM): Guidelines for Digital Elevation Data DCS Spatial Services Elevation Data Products Specification and Description (LiDAR) DCS Spatial Services Elevation Data Products Specification and Description (Airborne Photogrammetry)Distributors Service Delivery, DCS Spatial Services 346 Panorama Ave Bathurst NSW 2795Dataset Producers and Contributors Administrative Spatial Programs, DCS Spatial Services 346 Panorama Ave Bathurst NSW 2795

The Aboriginal Sites Decision Support Tool ASDST extends the Aboriginal Heritage Information Management System (AHIMS) by illustrating the potential distribution of site features recorded in AHIMS.\r ASDST was first developed in 2012 by the Office of Environment and Heritage (OEH) to support landscape planning of Aboriginal Heritage. The Tool produces a suite of raster GIS modelled outputs and is held in Esri GRID format. The first suite was published in 2016 as Version 7 at 100m resolution and in Lamberts Conic Conformal Projection (LCC). The current Version 7.5 was produced by the now Department of Planning, Industry and Environment (DPIE) in 2020 at 50m resolution in Geographic Coordinate System (GCS). Each layer covers the extent of NSW. \r \r The suite of layers includes separate predictive layers for different Aboriginal site feature types. The feature codes used in layer naming conventions are:\r \r * ALL = model for all feature types combined \r * AFT = predicted likelihood for stone artefacts \r * ART = predicted likelihood for rock art \r * BUR = predicted likelihood of burials \r * ETM = predicted likelihood of western mounds and shell \r * GDG = predicted likelihood of grinding grooves \r * HTH = predicted likelihood of hearths \r * SHL = predicted likelihood of coastal middens \r * STQ = predicted likelihood of stone quarries and \r * TRE = predicted likelihood of scarred trees. \r \r The feature models have been derived in two forms:\r \r * The first form (“p1750XXX” where XXX denotes three letter feature code) predicts likelihood of feature distribution prior to European colonisation of NSW. \r \r * The second form (“curr_XXX” where XXX denotes three letter feature code) predicts feature likelihood in the current landscape. \r \r For both sets of feature likelihood layers, cell values range from 0 – 1000, where 0 indicates low likelihood and 1000 is high likelihood. \r \r Please note the scale is likelihood and NOT probability. Likelihood is defined as a relative measure indicating the likelihood that a grid cell may contain the feature of interest relative to all other cells in the layer. \r \r Additionally, there are other derived products as part of the suite. These are: \r \r * drvd_imp = which is a model of accumulated impacts, derived by summing the difference between the pre colonisation and current version of all feature models. Cell values range from 0 – 1000, where 1000 is a high accumulated impact.\r \r * drvd_rel = which is a model of the reliability of predictions based on an environmental distance algorithm that looks at recorded site density across the variables used in the models.\r \r * drvd_srv = which is a survey priority map, which considers model reliability (data gap), current likelihood and accumulated impact. Cell values range from 0 – 1000 where 1000 indicates highest survey priority relative to the rest of the layer.\r \r For more details see the technical reference on the ASDST website.\r \r NB. Old layers with a suffix of “_v7” indicate they are part of ASDST Version 7 produced in 2016. The current models (Version 7.5) do not contain a version number in their name and will continue to be named generically in future versions for seamless access.\r \r Updates applied to ASDST version 7.5\r \r For all ASDST 7.5 data sets, the resolution was increased from a 100m cell to a 50m cell. All data sets were clipped and cleaned to a refined coastal mask. Cell gaps in the mask were filled using a Nibble algorithm. The pre-settlement data sets were derived by resampling the version 7 pre-settlement data sets to 50m cell size. The present-day data sets were derived from the version 7.5 pre-settlement layers and 2017-18 land-use mapping and applying the same version 7 parameters for estimating the preservation of each feature type on each land-use. For version 7.5, the model reliability data set was derived by resampling the version 7 data set to 50m cell size. Accumulated impact and survey priority version 7.5 data sets were derived by applying the version 7 processing algorithm but substituting the version 7.5 pre-settlement and present-day ASDST models.\r

The Aboriginal Sites Decision Support Tool ASDST extends the Aboriginal Heritage Information Management System (AHIMS) by illustrating the potential distribution of site features recorded in AHIMS. Show full descriptionThe Aboriginal Sites Decision Support Tool ASDST extends the Aboriginal Heritage Information Management System (AHIMS) by illustrating the potential distribution of site features recorded in AHIMS. ASDST was first developed in 2012 by the Office of Environment and Heritage (OEH) to support landscape planning of Aboriginal Heritage. The Tool produces a suite of raster GIS modelled outputs and is held in Esri GRID format. The first suite was published in 2016 as Version 7 at 100m resolution and in Lamberts Conic Conformal Projection (LCC). The current Version 7.5 was produced by the now Department of Planning, Industry and Environment (DPIE) in 2020 at 50m resolution in Geographic Coordinate System (GCS). Each layer covers the extent of NSW. The suite of layers includes separate predictive layers for different Aboriginal site feature types. The feature codes used in layer naming conventions are: ALL = model for all feature types combined AFT = predicted likelihood for stone artefacts ART = predicted likelihood for rock art BUR = predicted likelihood of burials ETM = predicted likelihood of western mounds and shell GDG = predicted likelihood of grinding grooves HTH = predicted likelihood of hearths SHL = predicted likelihood of coastal middens STQ = predicted likelihood of stone quarries and TRE = predicted likelihood of scarred trees. The feature models have been derived in two forms: The first form (“p1750XXX” where XXX denotes three letter feature code) predicts likelihood of feature distribution prior to European colonisation of NSW. The second form (“curr_XXX” where XXX denotes three letter feature code) predicts feature likelihood in the current landscape. For both sets of feature likelihood layers, cell values range from 0 – 1000, where 0 indicates low likelihood and 1000 is high likelihood. Please note the scale is likelihood and NOT probability. Likelihood is defined as a relative measure indicating the likelihood that a grid cell may contain the feature of interest relative to all other cells in the layer. Additionally, there are other derived products as part of the suite. These are: drvd_imp = which is a model of accumulated impacts, derived by summing the difference between the pre colonisation and current version of all feature models. Cell values range from 0 – 1000, where 1000 is a high accumulated impact. drvd_rel = which is a model of the reliability of predictions based on an environmental distance algorithm that looks at recorded site density across the variables used in the models. drvd_srv = which is a survey priority map, which considers model reliability (data gap), current likelihood and accumulated impact. Cell values range from 0 – 1000 where 1000 indicates highest survey priority relative to the rest of the layer. For more details see the technical reference on the ASDST website. NB. Old layers with a suffix of “_v7” indicate they are part of ASDST Version 7 produced in 2016. The current models (Version 7.5) do not contain a version number in their name and will continue to be named generically in future versions for seamless access. Updates applied to ASDST version 7.5 For all ASDST 7.5 data sets, the resolution was increased from a 100m cell to a 50m cell. All data sets were clipped and cleaned to a refined coastal mask. Cell gaps in the mask were filled using a Nibble algorithm. The pre-settlement data sets were derived by resampling the version 7 pre-settlement data sets to 50m cell size. The present-day data sets were derived from the version 7.5 pre-settlement layers and 2017-18 land-use mapping and applying the same version 7 parameters for estimating the preservation of each feature type on each land-use. For version 7.5, the model reliability data set was derived by resampling the version 7 data set to 50m cell size. Accumulated impact and survey priority version 7.5 data sets were derived by applying the version 7 processing algorithm but substituting the version 7.5 pre-settlement and present-day ASDST models.

The Aboriginal Sites Decision Support Tool ASDST extends the Aboriginal Heritage Information Management System (AHIMS) by illustrating the potential distribution of site features recorded in AHIMS. ASDST was first developed in 2012 by the Office of Environment and Heritage (OEH) to support landscape planning of Aboriginal Heritage. The Tool produces a suite of raster GIS modelled outputs and is held in Esri GRID format. The first suite was published in 2016 as Version 7 at 100m resolution and in Lamberts Conic Conformal Projection (LCC). The current Version 7.5 was produced by the now Department of Planning, Industry and Environment (DPIE) in 2020 at 50m resolution in Geographic Coordinate System (GCS). Each layer covers the extent of NSW.

The suite of layers includes separate predictive layers for different Aboriginal site feature types. The feature codes used in layer naming conventions are:

• ALL = model for all feature types combined
• AFT = predicted likelihood for stone artefacts
• ART = predicted likelihood for rock art
• BUR = predicted likelihood of burials
• ETM = predicted likelihood of western mounds and shell
• GDG = predicted likelihood of grinding grooves
• HTH = predicted likelihood of hearths
• SHL = predicted likelihood of coastal middens
• STQ = predicted likelihood of stone quarries and
• TRE = predicted likelihood of scarred trees.

The feature models have been derived in two forms:

• The first form (“p1750XXX” where XXX denotes three letter feature code) predicts likelihood of feature distribution prior to European colonisation of NSW.

• The second form (“curr_XXX” where XXX denotes three letter feature code) predicts feature likelihood in the current landscape.

For both sets of feature likelihood layers, cell values range from 0 – 1000, where 0 indicates low likelihood and 1000 is high likelihood.

Please note the scale is likelihood and NOT probability. Likelihood is defined as a relative measure indicating the likelihood that a grid cell may contain the feature of interest relative to all other cells in the layer.

Additionally, there are other derived products as part of the suite. These are:

• drvd_imp = which is a model of accumulated impacts, derived by summing the difference between the pre colonisation and current version of all feature models. Cell values range from 0 – 1000, where 1000 is a high accumulated impact.

• drvd_rel = which is a model of the reliability of predictions based on an environmental distance algorithm that looks at recorded site density across the variables used in the models.

• drvd_srv = which is a survey priority map, which considers model reliability (data gap), current likelihood and accumulated impact. Cell values range from 0 – 1000 where 1000 indicates highest survey priority relative to the rest of the layer.

For more details see the technical reference on the ASDST website.

NB. Old layers with a suffix of “_v7” indicate they are part of ASDST Version 7 produced in 2016. The current models (Version 7.5) do not contain a version number in their name and will continue to be named generically in future versions for seamless access.

Updates applied to ASDST version 7.5

For all ASDST 7.5 data sets, the resolution was increased from a 100m cell to a 50m cell. All data sets were clipped and cleaned to a refined coastal mask. Cell gaps in the mask were filled using a Nibble algorithm. The pre-settlement data sets were derived by resampling the version 7 pre-settlement data sets to 50m cell size. The present-day data sets were derived from the version 7.5 pre-settlement layers and 2017-18 land-use mapping and applying the same version 7 parameters for estimating the preservation of each feature type on each land-use. For version 7.5, the model reliability data set was derived by resampling the version 7 data set to 50m cell size. Accumulated impact and survey priority version 7.5 data sets were derived by applying the version 7 processing algorithm but substituting the version 7.5 pre-settlement and present-day ASDST models.

The Aboriginal Sites Decision Support Tool ASDST extends the Aboriginal Heritage Information Management System (AHIMS) by illustrating the potential distribution of site features recorded in AHIMS. ASDST was first developed in 2012 by the Office of Environment and Heritage (OEH) to support landscape planning of Aboriginal Heritage. The Tool produces a suite of raster GIS modelled outputs and is held in Esri GRID format. The first suite was published in 2016 as Version 7 at 100m resolution and in Lamberts Conic Conformal Projection (LCC). The current Version 7.5 was produced by the now Department of Planning, Industry and Environment (DPIE) in 2020 at 50m resolution in Geographic Coordinate System (GCS). Each layer covers the extent of NSW.

The suite of layers includes separate predictive layers for different Aboriginal site feature types. The feature codes used in layer naming conventions are:

• ALL = model for all feature types combined
• AFT = predicted likelihood for stone artefacts
• ART = predicted likelihood for rock art
• BUR = predicted likelihood of burials
• ETM = predicted likelihood of western mounds and shell
• GDG = predicted likelihood of grinding grooves
• HTH = predicted likelihood of hearths
• SHL = predicted likelihood of coastal middens
• STQ = predicted likelihood of stone quarries and
• TRE = predicted likelihood of scarred trees.

The feature models have been derived in two forms:

• The first form (“p1750XXX” where XXX denotes three letter feature code) predicts likelihood of feature distribution prior to European colonisation of NSW.

• The second form (“curr_XXX” where XXX denotes three letter feature code) predicts feature likelihood in the current landscape.

For both sets of feature likelihood layers, cell values range from 0 – 1000, where 0 indicates low likelihood and 1000 is high likelihood.

Please note the scale is likelihood and NOT probability. Likelihood is defined as a relative measure indicating the likelihood that a grid cell may contain the feature of interest relative to all other cells in the layer.

Additionally, there are other derived products as part of the suite. These are:

• drvd_imp = which is a model of accumulated impacts, derived by summing the difference between the pre colonisation and current version of all feature models. Cell values range from 0 – 1000, where 1000 is a high accumulated impact.

• drvd_rel = which is a model of the reliability of predictions based on an environmental distance algorithm that looks at recorded site density across the variables used in the models.

• drvd_srv = which is a survey priority map, which considers model reliability (data gap), current likelihood and accumulated impact. Cell values range from 0 – 1000 where 1000 indicates highest survey priority relative to the rest of the layer.

For more details see the technical reference on the ASDST website.

NB. Old layers with a suffix of “_v7” indicate they are part of ASDST Version 7 produced in 2016. The current models (Version 7.5) do not contain a version number in their name and will continue to be named generically in future versions for seamless access.

Updates applied to ASDST version 7.5

For all ASDST 7.5 data sets, the resolution was increased from a 100m cell to a 50m cell. All data sets were clipped and cleaned to a refined coastal mask. Cell gaps in the mask were filled using a Nibble algorithm. The pre-settlement data sets were derived by resampling the version 7 pre-settlement data sets to 50m cell size. The present-day data sets were derived from the version 7.5 pre-settlement layers and 2017-18 land-use mapping and applying the same version 7 parameters for estimating the preservation of each feature type on each land-use. For version 7.5, the model reliability data set was derived by resampling the version 7 data set to 50m cell size. Accumulated impact and survey priority version 7.5 data sets were derived by applying the version 7 processing algorithm but substituting the version 7.5 pre-settlement and present-day ASDST models.

The Aboriginal Sites Decision Support Tool ASDST extends the Aboriginal Heritage Information Management System (AHIMS) by illustrating the potential distribution of site features recorded in AHIMS. ASDST was first developed in 2012 by the Office of Environment and Heritage (OEH) to support landscape planning of Aboriginal Heritage. The Tool produces a suite of raster GIS modelled outputs and is held in Esri GRID format. The first suite was published in 2016 as Version 7 at 100m resolution and in Lamberts Conic Conformal Projection (LCC). The current Version 7.5 was produced by the now Department of Planning, Industry and Environment (DPIE) in 2020 at 50m resolution in Geographic Coordinate System (GCS). Each layer covers the extent of NSW.

The suite of layers includes separate predictive layers for different Aboriginal site feature types. The feature codes used in layer naming conventions are:

• ALL = model for all feature types combined
• AFT = predicted likelihood for stone artefacts
• ART = predicted likelihood for rock art
• BUR = predicted likelihood of burials
• ETM = predicted likelihood of western mounds and shell
• GDG = predicted likelihood of grinding grooves
• HTH = predicted likelihood of hearths
• SHL = predicted likelihood of coastal middens
• STQ = predicted likelihood of stone quarries and
• TRE = predicted likelihood of scarred trees.

The feature models have been derived in two forms:

• The first form (“p1750XXX” where XXX denotes three letter feature code) predicts likelihood of feature distribution prior to European colonisation of NSW.

• The second form (“curr_XXX” where XXX denotes three letter feature code) predicts feature likelihood in the current landscape.

For both sets of feature likelihood layers, cell values range from 0 – 1000, where 0 indicates low likelihood and 1000 is high likelihood.

Please note the scale is likelihood and NOT probability. Likelihood is defined as a relative measure indicating the likelihood that a grid cell may contain the feature of interest relative to all other cells in the layer.

Additionally, there are other derived products as part of the suite. These are:

• drvd_imp = which is a model of accumulated impacts, derived by summing the difference between the pre colonisation and current version of all feature models. Cell values range from 0 – 1000, where 1000 is a high accumulated impact.

• drvd_rel = which is a model of the reliability of predictions based on an environmental distance algorithm that looks at recorded site density across the variables used in the models.

• drvd_srv = which is a survey priority map, which considers model reliability (data gap), current likelihood and accumulated impact. Cell values range from 0 – 1000 where 1000 indicates highest survey priority relative to the rest of the layer.

For more details see the technical reference on the ASDST website.

NB. Old layers with a suffix of “_v7” indicate they are part of ASDST Version 7 produced in 2016. The current models (Version 7.5) do not contain a version number in their name and will continue to be named generically in future versions for seamless access.

Updates applied to ASDST version 7.5

For all ASDST 7.5 data sets, the resolution was increased from a 100m cell to a 50m cell. All data sets were clipped and cleaned to a refined coastal mask. Cell gaps in the mask were filled using a Nibble algorithm. The pre-settlement data sets were derived by resampling the version 7 pre-settlement data sets to 50m cell size. The present-day data sets were derived from the version 7.5 pre-settlement layers and 2017-18 land-use mapping and applying the same version 7 parameters for estimating the preservation of each feature type on each land-use. For version 7.5, the model reliability data set was derived by resampling the version 7 data set to 50m cell size. Accumulated impact and survey priority version 7.5 data sets were derived by applying the version 7 processing algorithm but substituting the version 7.5 pre-settlement and present-day ASDST models.

The Aboriginal Sites Decision Support Tool ASDST extends the Aboriginal Heritage Information Management System (AHIMS) by illustrating the potential distribution of site features recorded in AHIMS.\r ASDST was first developed in 2012 by the Office of Environment and Heritage (OEH) to support landscape planning of Aboriginal Heritage. The Tool produces a suite of raster GIS modelled outputs and is held in Esri GRID format. The first suite was published in 2016 as Version 7 at 100m resolution and in Lamberts Conic Conformal Projection (LCC). The current Version 7.5 was produced by the now Department of Planning, Industry and Environment (DPIE) in 2020 at 50m resolution in Geographic Coordinate System (GCS). Each layer covers the extent of NSW. \r \r The suite of layers includes separate predictive layers for different Aboriginal site feature types. The feature codes used in layer naming conventions are:\r \r * ALL = model for all feature types combined \r * AFT = predicted likelihood for stone artefacts \r * ART = predicted likelihood for rock art \r * BUR = predicted likelihood of burials \r * ETM = predicted likelihood of western mounds and shell \r * GDG = predicted likelihood of grinding grooves \r * HTH = predicted likelihood of hearths \r * SHL = predicted likelihood of coastal middens \r * STQ = predicted likelihood of stone quarries and \r * TRE = predicted likelihood of scarred trees. \r \r The feature models have been derived in two forms:\r \r * The first form (“p1750XXX” where XXX denotes three letter feature code) predicts likelihood of feature distribution prior to European colonisation of NSW. \r \r * The second form (“curr_XXX” where XXX denotes three letter feature code) predicts feature likelihood in the current landscape. \r \r For both sets of feature likelihood layers, cell values range from 0 – 1000, where 0 indicates low likelihood and 1000 is high likelihood. \r \r Please note the scale is likelihood and NOT probability. Likelihood is defined as a relative measure indicating the likelihood that a grid cell may contain the feature of interest relative to all other cells in the layer. \r \r Additionally, there are other derived products as part of the suite. These are: \r \r * drvd_imp = which is a model of accumulated impacts, derived by summing the difference between the pre colonisation and current version of all feature models. Cell values range from 0 – 1000, where 1000 is a high accumulated impact.\r \r * drvd_rel = which is a model of the reliability of predictions based on an environmental distance algorithm that looks at recorded site density across the variables used in the models.\r \r * drvd_srv = which is a survey priority map, which considers model reliability (data gap), current likelihood and accumulated impact. Cell values range from 0 – 1000 where 1000 indicates highest survey priority relative to the rest of the layer.\r \r For more details see the technical reference on the ASDST website.\r \r NB. Old layers with a suffix of “_v7” indicate they are part of ASDST Version 7 produced in 2016. The current models (Version 7.5) do not contain a version number in their name and will continue to be named generically in future versions for seamless access.\r \r Updates applied to ASDST version 7.5\r \r For all ASDST 7.5 data sets, the resolution was increased from a 100m cell to a 50m cell. All data sets were clipped and cleaned to a refined coastal mask. Cell gaps in the mask were filled using a Nibble algorithm. The pre-settlement data sets were derived by resampling the version 7 pre-settlement data sets to 50m cell size. The present-day data sets were derived from the version 7.5 pre-settlement layers and 2017-18 land-use mapping and applying the same version 7 parameters for estimating the preservation of each feature type on each land-use. For version 7.5, the model reliability data set was derived by resampling the version 7 data set to 50m cell size. Accumulated impact and survey priority version 7.5 data sets were derived by applying the version 7 processing algorithm but substituting the version 7.5 pre-settlement and present-day ASDST models.\r

The Aboriginal Sites Decision Support Tool ASDST extends the Aboriginal Heritage Information Management System (AHIMS) by illustrating the potential distribution of site features recorded in AHIMS.\r ASDST was first developed in 2012 by the Office of Environment and Heritage (OEH) to support landscape planning of Aboriginal Heritage. The Tool produces a suite of raster GIS modelled outputs and is held in Esri GRID format. The first suite was published in 2016 as Version 7 at 100m resolution and in Lamberts Conic Conformal Projection (LCC). The current Version 7.5 was produced by the now Department of Planning, Industry and Environment (DPIE) in 2020 at 50m resolution in Geographic Coordinate System (GCS). Each layer covers the extent of NSW. \r \r The suite of layers includes separate predictive layers for different Aboriginal site feature types. The feature codes used in layer naming conventions are:\r \r * ALL = model for all feature types combined \r * AFT = predicted likelihood for stone artefacts \r * ART = predicted likelihood for rock art \r * BUR = predicted likelihood of burials \r * ETM = predicted likelihood of western mounds and shell \r * GDG = predicted likelihood of grinding grooves \r * HTH = predicted likelihood of hearths \r * SHL = predicted likelihood of coastal middens \r * STQ = predicted likelihood of stone quarries and \r * TRE = predicted likelihood of scarred trees. \r \r The feature models have been derived in two forms:\r \r * The first form (“p1750XXX” where XXX denotes three letter feature code) predicts likelihood of feature distribution prior to European colonisation of NSW. \r \r * The second form (“curr_XXX” where XXX denotes three letter feature code) predicts feature likelihood in the current landscape. \r \r For both sets of feature likelihood layers, cell values range from 0 – 1000, where 0 indicates low likelihood and 1000 is high likelihood. \r \r Please note the scale is likelihood and NOT probability. Likelihood is defined as a relative measure indicating the likelihood that a grid cell may contain the feature of interest relative to all other cells in the layer. \r \r Additionally, there are other derived products as part of the suite. These are: \r \r * drvd_imp = which is a model of accumulated impacts, derived by summing the difference between the pre colonisation and current version of all feature models. Cell values range from 0 – 1000, where 1000 is a high accumulated impact.\r \r * drvd_rel = which is a model of the reliability of predictions based on an environmental distance algorithm that looks at recorded site density across the variables used in the models.\r \r * drvd_srv = which is a survey priority map, which considers model reliability (data gap), current likelihood and accumulated impact. Cell values range from 0 – 1000 where 1000 indicates highest survey priority relative to the rest of the layer.\r \r For more details see the technical reference on the ASDST website.\r \r NB. Old layers with a suffix of “_v7” indicate they are part of ASDST Version 7 produced in 2016. The current models (Version 7.5) do not contain a version number in their name and will continue to be named generically in future versions for seamless access.\r \r Updates applied to ASDST version 7.5\r \r For all ASDST 7.5 data sets, the resolution was increased from a 100m cell to a 50m cell. All data sets were clipped and cleaned to a refined coastal mask. Cell gaps in the mask were filled using a Nibble algorithm. The pre-settlement data sets were derived by resampling the version 7 pre-settlement data sets to 50m cell size. The present-day data sets were derived from the version 7.5 pre-settlement layers and 2017-18 land-use mapping and applying the same version 7 parameters for estimating the preservation of each feature type on each land-use. For version 7.5, the model reliability data set was derived by resampling the version 7 data set to 50m cell size. Accumulated impact and survey priority version 7.5 data sets were derived by applying the version 7 processing algorithm but substituting the version 7.5 pre-settlement and present-day ASDST models.\r

The Aboriginal Sites Decision Support Tool ASDST extends the Aboriginal Heritage Information Management System (AHIMS) by illustrating the potential distribution of site features recorded in AHIMS.\r ASDST was first developed in 2012 by the Office of Environment and Heritage (OEH) to support landscape planning of Aboriginal Heritage. The Tool produces a suite of raster GIS modelled outputs and is held in Esri GRID format. The first suite was published in 2016 as Version 7 at 100m resolution and in Lamberts Conic Conformal Projection (LCC). The current Version 7.5 was produced by the now Department of Planning, Industry and Environment (DPIE) in 2020 at 50m resolution in Geographic Coordinate System (GCS). Each layer covers the extent of NSW. \r \r The suite of layers includes separate predictive layers for different Aboriginal site feature types. The feature codes used in layer naming conventions are:\r \r * ALL = model for all feature types combined \r * AFT = predicted likelihood for stone artefacts \r * ART = predicted likelihood for rock art \r * BUR = predicted likelihood of burials \r * ETM = predicted likelihood of western mounds and shell \r * GDG = predicted likelihood of grinding grooves \r * HTH = predicted likelihood of hearths \r * SHL = predicted likelihood of coastal middens \r * STQ = predicted likelihood of stone quarries and \r * TRE = predicted likelihood of scarred trees. \r \r The feature models have been derived in two forms:\r \r * The first form (“p1750XXX” where XXX denotes three letter feature code) predicts likelihood of feature distribution prior to European colonisation of NSW. \r \r * The second form (“curr_XXX” where XXX denotes three letter feature code) predicts feature likelihood in the current landscape. \r \r For both sets of feature likelihood layers, cell values range from 0 – 1000, where 0 indicates low likelihood and 1000 is high likelihood. \r \r Please note the scale is likelihood and NOT probability. Likelihood is defined as a relative measure indicating the likelihood that a grid cell may contain the feature of interest relative to all other cells in the layer. \r \r Additionally, there are other derived products as part of the suite. These are: \r \r * drvd_imp = which is a model of accumulated impacts, derived by summing the difference between the pre colonisation and current version of all feature models. Cell values range from 0 – 1000, where 1000 is a high accumulated impact.\r \r * drvd_rel = which is a model of the reliability of predictions based on an environmental distance algorithm that looks at recorded site density across the variables used in the models.\r \r * drvd_srv = which is a survey priority map, which considers model reliability (data gap), current likelihood and accumulated impact. Cell values range from 0 – 1000 where 1000 indicates highest survey priority relative to the rest of the layer.\r \r For more details see the technical reference on the ASDST website.\r \r NB. Old layers with a suffix of “_v7” indicate they are part of ASDST Version 7 produced in 2016. The current models (Version 7.5) do not contain a version number in their name and will continue to be named generically in future versions for seamless access.\r \r Updates applied to ASDST version 7.5\r \r For all ASDST 7.5 data sets, the resolution was increased from a 100m cell to a 50m cell. All data sets were clipped and cleaned to a refined coastal mask. Cell gaps in the mask were filled using a Nibble algorithm. The pre-settlement data sets were derived by resampling the version 7 pre-settlement data sets to 50m cell size. The present-day data sets were derived from the version 7.5 pre-settlement layers and 2017-18 land-use mapping and applying the same version 7 parameters for estimating the preservation of each feature type on each land-use. For version 7.5, the model reliability data set was derived by resampling the version 7 data set to 50m cell size. Accumulated impact and survey priority version 7.5 data sets were derived by applying the version 7 processing algorithm but substituting the version 7.5 pre-settlement and present-day ASDST models.\r

The Aboriginal Sites Decision Support Tool ASDST extends the Aboriginal Heritage Information Management System (AHIMS) by illustrating the potential distribution of site features recorded in AHIMS. ASDST was first developed in 2012 by the Office of Environment and Heritage (OEH) to support landscape planning of Aboriginal Heritage. The Tool produces a suite of raster GIS modelled outputs and is held in Esri GRID format. The first suite was published in 2016 as Version 7 at 100m resolution and in Lamberts Conic Conformal Projection (LCC). The current Version 7.5 was produced by the now Department of Planning, Industry and Environment (DPIE) in 2020 at 50m resolution in Geographic Coordinate System (GCS). Each layer covers the extent of NSW.

The suite of layers includes separate predictive layers for different Aboriginal site feature types. The feature codes used in layer naming conventions are:

• ALL = model for all feature types combined
• AFT = predicted likelihood for stone artefacts
• ART = predicted likelihood for rock art
• BUR = predicted likelihood of burials
• ETM = predicted likelihood of western mounds and shell
• GDG = predicted likelihood of grinding grooves
• HTH = predicted likelihood of hearths
• SHL = predicted likelihood of coastal middens
• STQ = predicted likelihood of stone quarries and
• TRE = predicted likelihood of scarred trees.

The feature models have been derived in two forms:

• The first form (“p1750XXX” where XXX denotes three letter feature code) predicts likelihood of feature distribution prior to European colonisation of NSW.

• The second form (“curr_XXX” where XXX denotes three letter feature code) predicts feature likelihood in the current landscape.

For both sets of feature likelihood layers, cell values range from 0 – 1000, where 0 indicates low likelihood and 1000 is high likelihood.

Please note the scale is likelihood and NOT probability. Likelihood is defined as a relative measure indicating the likelihood that a grid cell may contain the feature of interest relative to all other cells in the layer.

Additionally, there are other derived products as part of the suite. These are:

• drvd_imp = which is a model of accumulated impacts, derived by summing the difference between the pre colonisation and current version of all feature models. Cell values range from 0 – 1000, where 1000 is a high accumulated impact.

• drvd_rel = which is a model of the reliability of predictions based on an environmental distance algorithm that looks at recorded site density across the variables used in the models.

• drvd_srv = which is a survey priority map, which considers model reliability (data gap), current likelihood and accumulated impact. Cell values range from 0 – 1000 where 1000 indicates highest survey priority relative to the rest of the layer.

For more details see the technical reference on the ASDST website.

NB. Old layers with a suffix of “_v7” indicate they are part of ASDST Version 7 produced in 2016. The current models (Version 7.5) do not contain a version number in their name and will continue to be named generically in future versions for seamless access.

Updates applied to ASDST version 7.5

For all ASDST 7.5 data sets, the resolution was increased from a 100m cell to a 50m cell. All data sets were clipped and cleaned to a refined coastal mask. Cell gaps in the mask were filled using a Nibble algorithm. The pre-settlement data sets were derived by resampling the version 7 pre-settlement data sets to 50m cell size. The present-day data sets were derived from the version 7.5 pre-settlement layers and 2017-18 land-use mapping and applying the same version 7 parameters for estimating the preservation of each feature type on each land-use. For version 7.5, the model reliability data set was derived by resampling the version 7 data set to 50m cell size. Accumulated impact and survey priority version 7.5 data sets were derived by applying the version 7 processing algorithm but substituting the version 7.5 pre-settlement and present-day ASDST models.

The Aboriginal Sites Decision Support Tool ASDST extends the Aboriginal Heritage Information Management System (AHIMS) by illustrating the potential distribution of site features recorded in AHIMS.\r ASDST was first developed in 2012 by the Office of Environment and Heritage (OEH) to support landscape planning of Aboriginal Heritage. The Tool produces a suite of raster GIS modelled outputs and is held in Esri GRID format. The first suite was published in 2016 as Version 7 at 100m resolution and in Lamberts Conic Conformal Projection (LCC). The current Version 7.5 was produced by the now Department of Planning, Industry and Environment (DPIE) in 2020 at 50m resolution in Geographic Coordinate System (GCS). Each layer covers the extent of NSW. \r \r The suite of layers includes separate predictive layers for different Aboriginal site feature types. The feature codes used in layer naming conventions are:\r \r * ALL = model for all feature types combined \r * AFT = predicted likelihood for stone artefacts \r * ART = predicted likelihood for rock art \r * BUR = predicted likelihood of burials \r * ETM = predicted likelihood of western mounds and shell \r * GDG = predicted likelihood of grinding grooves \r * HTH = predicted likelihood of hearths \r * SHL = predicted likelihood of coastal middens \r * STQ = predicted likelihood of stone quarries and \r * TRE = predicted likelihood of scarred trees. \r \r The feature models have been derived in two forms:\r \r * The first form (“p1750XXX” where XXX denotes three letter feature code) predicts likelihood of feature distribution prior to European colonisation of NSW. \r \r * The second form (“curr_XXX” where XXX denotes three letter feature code) predicts feature likelihood in the current landscape. \r \r For both sets of feature likelihood layers, cell values range from 0 – 1000, where 0 indicates low likelihood and 1000 is high likelihood. \r \r Please note the scale is likelihood and NOT probability. Likelihood is defined as a relative measure indicating the likelihood that a grid cell may contain the feature of interest relative to all other cells in the layer. \r \r Additionally, there are other derived products as part of the suite. These are: \r \r * drvd_imp = which is a model of accumulated impacts, derived by summing the difference between the pre colonisation and current version of all feature models. Cell values range from 0 – 1000, where 1000 is a high accumulated impact.\r \r * drvd_rel = which is a model of the reliability of predictions based on an environmental distance algorithm that looks at recorded site density across the variables used in the models.\r \r * drvd_srv = which is a survey priority map, which considers model reliability (data gap), current likelihood and accumulated impact. Cell values range from 0 – 1000 where 1000 indicates highest survey priority relative to the rest of the layer.\r \r For more details see the technical reference on the ASDST website.\r \r NB. Old layers with a suffix of “_v7” indicate they are part of ASDST Version 7 produced in 2016. The current models (Version 7.5) do not contain a version number in their name and will continue to be named generically in future versions for seamless access.\r \r Updates applied to ASDST version 7.5\r \r For all ASDST 7.5 data sets, the resolution was increased from a 100m cell to a 50m cell. All data sets were clipped and cleaned to a refined coastal mask. Cell gaps in the mask were filled using a Nibble algorithm. The pre-settlement data sets were derived by resampling the version 7 pre-settlement data sets to 50m cell size. The present-day data sets were derived from the version 7.5 pre-settlement layers and 2017-18 land-use mapping and applying the same version 7 parameters for estimating the preservation of each feature type on each land-use. For version 7.5, the model reliability data set was derived by resampling the version 7 data set to 50m cell size. Accumulated impact and survey priority version 7.5 data sets were derived by applying the version 7 processing algorithm but substituting the version 7.5 pre-settlement and present-day ASDST models.\r