Fsdf

## Overview

Fsdf is a dataset for object detection tasks - it contains Dfbd annotations for 641 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

dfsdfsd. Visit https://dataone.org/datasets/sha256%3Ab61cfc01b78e0c5d5d257b8c376e3771aaaf7392b1304331210f8dc9caa31c9d for complete metadata about this dataset.

dfsdfsd. Visit https://dataone.org/datasets/sha256%3A1dc6350dd4462a68e073257d45ee86e8d74dc3f4742140c91b23cc0f229fd4e7 for complete metadata about this dataset.

Australia's Land Borders is a product within the Foundation Spatial Data Framework (FSDF) suite of datasets. It is endorsed by the ANZLIC - the Spatial Information Council and the Intergovernmental Committee on Surveying and Mapping (ICSM) as a nationally consistent and topologically correct representation of the land borders published by the Australian states and territories.

The purpose of this product is to provide: (i) a building block which enables development of other national datasets; (ii) integration with other geospatial frameworks in support of data analysis; and (iii) visualisation of these borders as cartographic depiction on a map. Although this dataset depicts land borders, it is not nor does it suggests to be a legal definition of these borders. Therefore it cannot and must not be used for those use-cases pertaining to legal context.

This product is constructed by Geoscience Australia (GA), on behalf of the ICSM, from authoritative open data published by the land mapping agencies in their respective Australian state and territory jurisdictions. Construction of a nationally consistent dataset required harmonisation and mediation of data issues at abutting land borders. In order to make informed and consistent determinations, other datasets were used as visual aid in determining which elements of published jurisdictional data to promote into the national product. These datasets include, but are not restricted to: (i) PSMA Australia's commercial products such as the cadastral (property) boundaries (CadLite) and Geocoded National Address File (GNAF); (ii) Esri's World Imagery and Imagery with Labels base maps; and (iii) Geoscience Australia's GEODATA TOPO 250K Series 3. Where practical, Land Borders do not cross cadastral boundaries and are logically consistent with addressing data in GNAF.

It is important to reaffirm that although third-party commercial datasets are used for validation, which is within remit of the licence agreement between PSMA and GA, no commercially licenced data has been promoted into the product. Australian Land Borders are constructed exclusively from published open data originating from state, territory and federal agencies.

This foundation dataset consists of edges (polylines) representing mediated segments of state and/or territory borders, connected at the nodes and terminated at the coastline defined as the Mean High Water Mark (MHWM) tidal boundary. These polylines are attributed to convey information about provenance of the source. It is envisaged that land borders will be topologically interoperable with the future national coastline dataset/s, currently being built through the ICSM coastline capture collaboration program. Topological interoperability will enable closure of land mass polygon, permitting spatial analysis operations such as vector overly, intersect, or raster map algebra. In addition to polylines, the product incorporates a number of well-known survey-monumented corners which have historical and cultural significance associated with the place name.

This foundation dataset is constructed from the best-available data, as published by relevant custodian in state and territory jurisdiction. It should be noted that some custodians - in particular the Northern Territory and New South Wales - have opted out or to rely on data from abutting jurisdiction as an agreed portrayal of their border. Accuracy and precision of land borders as depicted by spatial objects (features) may vary according to custodian specifications, although there is topological coherence across all the objects within this integrated product. The guaranteed minimum nominal scale for all use-cases, applying to complete spatial coverage of this product, is 1:25 000. In some areas the accuracy is much better and maybe approaching cadastre survey specification, however, this is an artefact of data assembly from disparate sources, rather than the product design. As the principle, no data was generalised or spatially degraded in the process of constructing this product.

Some use-cases for this product are: general digital and web map-making applications; a reference dataset to use for cartographic generalisation for a smaller-scale map applications; constraining geometric objects for revision and updates to the Mesh Blocks, the building blocks for the larger regions of the Australian Statistical Geography Standard (ASGS) framework; rapid resolution of cross-border data issues to enable construction and visual display of a common operating picture, etc.

This foundation dataset will be maintained at irregular intervals, for example if a state or territory jurisdiction decides to publish or republish their land borders. If there is a new version of this dataset, past version will be archived and information about the changes will be made available in the change log.

Explore the historical Whois records related to fsdf.space (Domain). Get insights into ownership history and changes over time.

Investigate historical ownership changes and registration details by initiating a reverse Whois lookup for the name Fsdf sdkjgf.

The Foundation Facility Point product contains five facility types, Private Hospitals, Public Hospitals, Aged Care Facilities, Educational Facilities and Emergency Management Facilities. The Foundation Facility Point Database presents the spatial location; in point format, of publicly available data. Facility Points are derived from various sources and consistency is mixed across Australia.

The Fire Affected Sites LiDAR dataset is high resolution digital information available as classified point cloud data or a 1 metre Digital Elevation Model (DEM) and can be downloaded on a 1 km tile …Show full descriptionThe Fire Affected Sites LiDAR dataset is high resolution digital information available as classified point cloud data or a 1 metre Digital Elevation Model (DEM) and can be downloaded on a 1 km tile basis from http://elevation.fsdf.org.au. The data was collected between 2016 and 2017 over four sites within Tasmania and covers the Lake Mackenzie Road, Lake Bill, Maxwell and Gordon Road areas.

This collection provides a seamlessly merged, hydrologically robust Digital Elevation Model (DEM) for the Murray Darling Basin (MDB), Australia, at 5 m and 25 m grid cell resolution.

This composite DEM has been created from all the publicly available high resolution DEMs in the Geoscience Australia (GA) elevation data portal Elvis (https://elevation.fsdf.org.au/) as at November 2022. The input DEMs, also sometimes referred to as digital terrain models (DTMs), are bare-earth products which represent the ground surface with buildings and vegetation removed. The DEMs were either from lidar (0.5 to 2 m resolution) or photogrammetry (5 m resolution) and totalled 852 individual DEMs.

The merging process involved ranking the DEMs, pairing the DEMs with overlaps, and adjusting and smoothing the elevations of the lower ranked DEM to make the edge elevations compatible with the higher-ranked DEM. This method is adapted from Gallant 2019 with modifications to work with hundreds of DEMs and have a variable number of gaussian smoothing steps.

Where there were gaps in the high-resolution DEM extents, the Forests and Buildings removed DEM (FABDEM; Hawker et al. 2022), a bare-earth radar-derived, 1 arc-second resolution global elevation model was used as the underlying base DEM. FABDEM is based on the Copernicus global digital surface model.

Additionally, hillshade datasets created from both the 5 m and 25 m DEMs are provided.

Note: the FABDEM dataset is available publicly for non-commercial purposes and consequently the data files available with this Collection are also available with a Creative Commons NonCommercial ShareAlike 4.0 Licence (CC BY-NC-SA 4.0). See https://data.bris.ac.uk/datasets/25wfy0f9ukoge2gs7a5mqpq2j7/license.txt Lineage: For a more detailed lineage see the supporting document Composite_MDB_DEM_Lineage.

DATA SOURCES 1. Geoscience Australia elevation data (https://elevation.fsdf.org.au/) via Amazon Web Service s3 bucket. Of the 852 digital elevation models (DEMs) from the GA elevation data portal, 601 DEMs were from lidar and 251 were from photogrammetry. The latest date of download was Nov 2022. The oldest input DEM was from 2008 and the newest from 2022.

1. FABDEM - Forests and buildings removed DEM based on the 1 arc-second Copernicus global digital surface model. Hawker, L., Uhe, P., Paulo, L., Sosa, J., Savage, J., Sampson, C., Neal, J., 2022. A 30 m global map of elevation with forests and buildings removed. Environ. Res. Lett. 17, 024016. https://doi.org/10.1088/1748-9326/ac4d4f

METHODS Part I. Preprocessing The input DEMs were prepared for merging with the following steps: 1. Metadata for all input DEMs was collated in a single file and the DEMs were ranked from finest resolution/newest to coarsest resolution/oldest 2. Tiled input DEMs were combined into single files 3. Input DEMs were reprojected to GA LCC conformal conic projection (EPSG:7845) and bilinearly resampled to 5 m 4. Input DEMs were shifted vertically to the Australian Vertical Working Surface (AVWS; EPSG:9458) 5. The input DEMs were stacked (without any merging and/or smoothing at DEM edges) based on rank so that higher ranking DEMs preceded the lower ranking DEMs, i.e. the elevation value in a grid cell came from the highest rank DEM which had a value in that cell 6. An index raster dataset was produced, where the value assigned to each grid cell was the rank of the DEM which contributed the elevation value to the stacked DEM (see Collection Files - Index_5m_resolution) 7. A metadata file describing each input dataset was linked to the index dataset via the rank attribute (see Collection Files - Metadata)

Vertical height reference surface https://icsm.gov.au/australian-vertical-working-surface

Part II. DEM Merging The method for seamlessly merging DEMs to create a composite dataset is based on Gallant 2019, with modifications to work with hundreds of input DEMs. Within DEM pairs, the elevations of the lower ranked DEM are adjusted and smoothed to make the edge elevations compatible with the higher-ranked DEM. Processing was on the CSIRO Earth Analytics and Science Innovation (EASI) platform. Code was written in python and dask was used for task scheduling.

Part III. Postprocessing 1. A minor correction was made to the 5 m composite DEM in southern Queensland to replace some erroneous elevation values (-8000 m a.s.l.) with the nearest values from the surrounding grid cells 2. A 25 m version of the composite DEM was created by aggregating the 5m DEM, using a 5 x 5 grid cell window and calculating the mean elevation 3. Hillshade datasets were produced for the 5 m and 25 m DEMs using python code from https://github.com/UP-RS-ESP/DEM-Consistency-Metrics

Part IV. Validation Six validation areas were selected across the MDB for qualitative checking of the output at input dataset boundaries. The hillshade datasets were used to look for linear artefacts. Flow direction and flow accumulation rasters and drainage lines were derived from the stacked DEM (step 5 in preprocessing) and the post-merge composite DEM. These were compared to determine whether the merging process had introduced additional errors.

OUTPUTS 1. seamlessly merged composite DEMs at 5 m and 25 m resolutions (geotiff) 2. hillshade datasets for the 5 m and 25 m DEMs (geotiff) 3. index raster dataset at 5 m resolution (geotiff) 4. metadata file containing input dataset information and rank (the rank column values link to the index raster dataset values) 5. figure showing a map of the index dataset and 5m composite DEM (jpeg)

DATA QUALITY STATEMENT Note that we did not attempt to improve the quality of the input DEMs, they were not corrected prior to merging and any errors will be retained in the composite DEM.

Sfsf

## Overview

Sfsf is a dataset for object detection tasks - it contains Fsdf annotations for 5,268 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

🇦🇺 Australia English Content TitleLocal Government AreasContent TypeHosted Feature LayerDescriptionNSW Local Government Area is a dataset within the Administrative Boundaries Theme (FSDF). It depicts polygons of gazetted boundaries defining the Local Government Area. It contains all of the cadastral line data or topographic features which are used to define the boundaries between adjoining shires, municipalities, cities (Local Government Act) and the unincorporated areas of NSW.The dataset also contains Council Names, ABS Codes, Ito Codes, Vg Codes, and Wb Codes. Any changes that occur to the dataset should have a reference in the authority of reference feature class in the Land Parcel and Property.Features are positioned in topological alignment within the extents of the land parcel and property polygons for each Local Government Area and are held in alignment, including changes resulting cadastral maintenance and upgrades.Initial Publication Date05/02/2020Data Currency01/01/3000Data Update FrequencyDailyContent 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 Administrative Boundaries Theme of the Foundation Spatial Data Framework (FSDF)AccuracyThe dataset maintains a positional relationship to, and alignment with, the Lot and Property digital datasets. This dataset was captured by digitising the best available cadastral mapping 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 of positional upgrade (accuracy improvement) is currently underway. A program to upgrade the spatial location and accuracy of data is ongoing.Spatial Reference System (dataset)GDA94Spatial Reference System (web service)OtherWGS84 Equivalent ToGDA2020Spatial ExtentFull stateContent LineagePlease contact us via the Spatial Services Customer HubData ClassificationUnclassifiedData Access PolicyOpenData QualityPlease contact us via the Spatial Services Customer HubTerms and ConditionsCreative CommonsStandard and SpecificationOpen Geospatial Consortium (OGC) implemented and compatible for consumption by common GIS platforms. Available as either cache or non-cache, depending on client use or requirement.Data CustodianDCS Spatial Services346 Panorama AveBathurst NSW 2795Point of ContactPlease contact us via the Spatial Services Customer HubData AggregatorDCS Spatial Services346 Panorama AveBathurst NSW 2795Data DistributorDCS Spatial Services346 Panorama AveBathurst NSW 2795Additional Supporting InformationData DictionariesTRIM Number

Access APINSW Features of Interest Category - Justice Facilities Please Note WGS 84 = GDA94 service This dataset has a spatial reference of [WGS 84 = GDA94] and can NOT be easily consumed into …Show full description Access APINSW Features of Interest Category - Justice Facilities Please Note WGS 84 = GDA94 service This dataset has a spatial reference of [WGS 84 = GDA94] and can NOT be easily consumed into GDA2020 environments. A similar service with a ‘multiCRS’ suffix is available which can support GDA2020, GDA94 and WGS84 = GDA2020 environments. In due course, and allowing time for user feedback and testing, it is intended that these original services will adopt the new multiCRS functionally. The Features of Interest – Justice Services is a point feature dataset that represents the location of Court Houses, Gaols and other Justice related datasets which are crucial to delivery of Education Services to NSW.The Features of Interest category Justice Services is part of the Building Complex feature class and is represented as a community facility.Features that make up the NSW Features of interest Category - Justice Services include:Court House - A facility used for holding courts of law and the operation or administration of judicial authorities and commissions. This point feature dataset is part of the NSW Features of interest Category. Court house data points are positioned within the cadastral parcel in which they are located.Gaol - A facility for the confinement or safe custody of criminals and others committed by law. This point feature dataset is part of the NSW Features of interest Category. Gaol data points are positioned within the cadastral parcel in which they are located.These features do not fit within one of the ten foundation spatial data themes and are therefore classified as a category. They have historically been captured by Spatial Services as part of the NSW topographic mapping program and therefore warrant inclusion.MetadataType Esri Map Service Update Frequency As required Contact Details Contact us via the Spatial Services Customer Hub Relationship to Themes and Datasets Features of Interest Category of the Foundation Spatial Data Framework (FSDF) Accuracy The dataset maintains a positional relationship to, and alignment with, a range of themes from the NSW FSDF including, transport, imagery, positioning, water and land cover. This dataset was captured by digitising the best available cadastral mapping 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 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: WGS84 Geographic 2D WGS84 Equivalent To GDA94 Spatial Extent Full state Standards and Specifications Open Geospatial Consortium (OGC) implemented and compatible for consumption by common GIS platforms. Available as either cache or non-cache, depending on client use or requirement. 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 Digital Elevation Model Imagery Catalog layer describes precision elevation datasets acquired from LiDAR and aerial / satellite sensors currently archived in the department. Precision elevation products are defined as Digital Terrain Models (or bare Earth Digital Elevation Models) captured from either LiDAR sources or photogrammetrically derived from aerial photography. LiDAR classified point clouds and derived Digital Terrain Models under a CC-BY license have been uploaded to the ELVIS Elevation and Depth Online Portal (https://elevation.fsdf.org.au/).

Palm Beach, NSW

This model is concerned with Palm Beach's unique topography, which has been relatively well preserved despite being smothered by countless affluent estates.

This exploded axonometric file examines the distribution of vegetation, conservation land, and how the built environment interacts with this based on the best available point cloud data. Developed using CloudCompare and QGIS to colourise, manipulate, and clean the data to its final presentable format.

This information should provide a more intimate method for prospective home buyers, environmental conservation committees, and council members to gain a better understanding of the land from a unique perspective.

Note: Sketchfab limits non-premium account uploads to 50MB so point-count has been reduced to allow for this parameter.

Data: https://elevation.fsdf.org.au/

Source: Objaverse 1.0 / Sketchfab

Export DataAccess API NSW Administrative Boundaries 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' functionality. Metadata Portal Metadata Information Content TitleNSW Administrative Boundaries ThemeContent TypeHosted Feature LayerDescriptionThe Administrative Boundaries theme from NSW Foundation Spatial Data Framework (FSDF) is a collection of legislative, regulatory, political, maritime and general administrative boundaries sourced from local and state boundary datasets.They include:Parish CountySuburbLocal Government AreaState Electoral DistrictFederal Electoral DivisionMines Subsidence District NSW Parks and Wildlife Service ReserveState ForestState BorderDomestic Water Front PrecinctThe Administrative Boundaries theme is used to show administrative areas that represent:Voting DistrictsRedistributionsZoning Socio-Economic analysisRegional PlanningService DistributionLocal and State Government BoundariesIn addition, Administrative Boundaries can also be used for analysis and to look at trends over time. Administrative boundary data in combination with geo-coded address data, demographic information and agency specific business information underpins the ability to perform high quality spatial analysis.The use of this data in combination with other data includes:Evidence-based development and assessment of government policyProviding the ability to undertake spatial accountingRegional analysis for government, health, education, business and a range of other purposesSupport for emergency managementMarket catchment analysis, micromarketing, customer analysis and market segmentationEmergency management. Update frequencies vary for each dataset. Individual current status can be found under each spatial data profile. Initial Publication Date04/02/2020Data 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 Administrative Boundaries Theme of the Foundation Spatial Data Framework (FSDF)AccuracyThe dataset maintains a positional relationship to, and alignment with, the Lot and Property digital datasets. This dataset was captured by digitising the best available cadastral mapping 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 SpecificationOpen Geospatial Consortium (OGC) implemented and compatible for consumption by common GIS platforms. Available as either cache or non-cache, depending on client use or requirement.Information about the Feature Class and Domain Name descriptions for the NSW Administrative Boundaries Theme can be found in the NSW Cadastral Data Dictionary.Some of Spatial Services Datasets are designed to work together for example NSW Address Point and NSW Address String (table), NSW Property (Polygon) and NSW Property Lot (table) and NSW Lot (polygons). To do this you need to add a Spatial Join.A Spatial Join is a GIS operation that affixes data from one feature layer’s attribute table to another from a spatial perspective.To see how NSW Address, Property, Lot Geometry data and tables can be spatially joined, download the Data Model Document. Data CustodianDCS Spatial Services346 Panorama AveBathurst NSW 2795Point of ContactPlease contact us via the Spatial Services Customer HubData AggregatorDCS Spatial Services346 Panorama AveBathurst NSW 2795Data DistributorDCS Spatial Services346 Panorama AveBathurst NSW 2795Additional Supporting InformationData DictionariesData Model Document. TRIM Number

The Tasmania 2 metre Digital Elevation Model (DEM) is a regular grid of ground level elevation values spaced at 2 metre intervals across the extent of the land area of Tasmania and most of the associated islands, but excluding Macquarie Island. Approximately 65% of the DEM is derived from LiDAR data, with the remainder of the surface interpolated from photogrammetric contours, spot heights and mean high water level data. Outside of LiDAR areas, the data resolution is 10 m. The projection is GDA 1994 MGA Zone 55, with vertical heights relative to AHD. This dataset was produced by Mineral Resources Tasmania and the data is available to download using the ELVIS download portal. https://elevation.fsdf.org.au/

The Points of Interest (POI) web service provides the identification and location of a feature, service or activity that people may want to see, know about or visit. POI features for this service are primarily derived from features maintained within the Digital Topographic Database (DTDB). The POI feature class is maintained programmatically (automated) by sourcing spatial and aspatial attributes from other feature classes in the DTDB that contain POI features. The midpoint of a line or polygon features is used to define the POI. Points of Interest include features related to Community, Education, Recreation, Transportation, Utility, or Hydrography, Physiography and Place, and defined as a place with a prescribed name. The attribute information for an individual dataset may have been thinned or modifed to cater for the service. The service is available in a cached environment only. This dataset is compliant with the NSW FSDF and its specifications. For details information for each individual dataset contained in this web services.

NOTE: Please contact SS-SDS@finance.nsw.gov.au for advice on datasets access.

Access APINSW Physiography Category - Fuzzy Extent Point Please Note WGS 84 = GDA94 service This dataset has a spatial reference of [WGS 84 = GDA94] and can NOT be easily consumed into GDA2020 …Show full description Access APINSW Physiography Category - Fuzzy Extent Point Please Note WGS 84 = GDA94 service This dataset has a spatial reference of [WGS 84 = GDA94] and can NOT be easily consumed into GDA2020 environments. A similar service with a ‘multiCRS’ suffix is available which can support GDA2020, GDA94 and WGS84 = GDA2020 environments. In due course, and allowing time for user feedback and testing, it is intended that these original services will adopt the new multiCRS functionally. Fuzzy Extent Point is a point feature class representing the approximate centre of formally named landforms that have relatively indistinct name extent. Data in the Fuzzy Extent Point includes: Beach Like - The gently sloping shore which is washed by waves or tides, especially the parts covered by sand or pebbles. Flat Like - A named flat-like landform, which includes GNB designations: Flat, Plain, River Flat & Terrace. General Locality - A formally named general place or locality of indistinct extent not readily classified by a more specific feature classification. Headland Like - A named headland-like landform, which includes GNB designations: Head, Headland & Point (near water). Gap Like - A named gap-like landform, which includes GNB designations: Gap, Pass, Passage (inland) & Saddle. Island Like - A named Island-like landform, being an area of dry or relatively dry land surrounded by water or low wetland, adapted from the Intergovernmental Committee of Surveying and Mapping, Qualification: Includes GNB designation: Island and Islet. Landcover Like - A named landcover land surface, which includes GNB designations: Clearing, Desert, Moor & Scrub. Mountain Like - A named mountain-like landform, which includes GNB designations: Bluff, Butte, Crag, Hill, Hillock, Knob, Knolls, Monolith, Mount, Mountain, Mountain Peak, Neck, Peak, Pinnacle, Point (inland), Rock and Top. Peninsula Like - A named peninsula-like landform, which includes GNB designations: Cape, Peninsula and Spit. Plateau Like - A named plateau-like landform, which includes GNB designations: Mesa, Plateau and Tableland. Sandbar Like - A named sandbar-like landform, which includes GNB designations: Sandbank, Sandbar and Shoal. Slope Like - A named slope-like landform, which includes GNB designations: Buttress, Cliff, Escarpment, Fault, Gradient, Rock Face, Slope & Steeps. Valley Like - Named valley-like landform, which includes GNB designations: Amphitheatre, Basin, Bend, Canyon, Chasm, Crater, Cutting, Depression, Glen, Gorge, Gulf, Gullies, Hole, Ravine, Sink & Valley. Promontory Like - A named promontory-like landform. Promontory like data points are positioned within the cadastral parcel in which they are located.MetadataType Esri Feature Service Update Frequency As required Contact Details Contact us via the Spatial Services Customer Hub Relationship to Themes and Datasets Physiography Category of the Foundation Spatial Data Framework (FSDF) Accuracy The dataset maintains a positional relationship to, and alignment with, a range of themes from the NSW FSDF including, transport, imagery, positioning, water and land cover. This dataset was captured by digitising the best available cadastral mapping 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 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: WGS84 Geographic 2D WGS84 Equivalent To GDA94 Spatial Extent Full state Standards and Specifications Open Geospatial Consortium (OGC) implemented and compatible for consumption by common GIS platforms. Available as either cache or non-cache, depending on client use or requirement. 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 Middleton LiDAR dataset is high resolution digital information available as classified point cloud data or a 1 metre Digital Elevation Model (DEM) and can be downloaded on a 1 km tile basis from …Show full descriptionThe Middleton LiDAR dataset is high resolution digital information available as classified point cloud data or a 1 metre Digital Elevation Model (DEM) and can be downloaded on a 1 km tile basis from http://elevation.fsdf.org.au. The data was collected in 2017 and covers the Middleton coastal area.