The United States Office of the Geographer provides the Large Scale International Boundary (LSIB) dataset. It is derived from two other datasets: a LSIB line vector file and the World Vector Shorelines (WVS) from the National Geospatial-Intelligence Agency (NGA). The interior boundaries reflect U.S. government policies on boundaries, boundary disputes, and sovereignty. The exterior boundaries are derived from the WVS; however, the WVS coastline data is outdated and generally shifted from between several hundred meters to over a kilometer. Each feature is the polygonal area enclosed by interior boundaries and exterior coastlines where applicable, and many countries consist of multiple features, one per disjoint region. Each of the 180,741 features is a part of the geometry of one of the 284 countries described in this dataset.

The Digital Geologic-GIS Map of Rocky Mountain National Park and Vicinity, Colorado is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) an ESRI file geodatabase (romo_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro 3.X map file (.mapx) file (romo_geology.mapx) and individual Pro 3.X layer (.lyrx) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (romo_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (romo_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (romo_geology_metadata_faq.pdf). Please read the romo_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri.htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (romo_geology_metadata.txt or romo_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:50,000 and United States National Map Accuracy Standards features are within (horizontally) 25.4 meters or 83.3 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS Pro, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

Welcome to Apiscrapy, your ultimate destination for comprehensive location-based intelligence. As an AI-driven web scraping and automation platform, Apiscrapy excels in converting raw web data into polished, ready-to-use data APIs. With a unique capability to collect Google Address Data, Google Address API, Google Location API, Google Map, and Google Location Data with 100% accuracy, we redefine possibilities in location intelligence.

Key Features:

Unparalleled Data Variety: Apiscrapy offers a diverse range of address-related datasets, including Google Address Data and Google Location Data. Whether you seek B2B address data or detailed insights for various industries, we cover it all.

Integration with Google Address API: Seamlessly integrate our datasets with the powerful Google Address API. This collaboration ensures not just accessibility but a robust combination that amplifies the precision of your location-based insights.

Business Location Precision: Experience a new level of precision in business decision-making with our address data. Apiscrapy delivers accurate and up-to-date business locations, enhancing your strategic planning and expansion efforts.

Tailored B2B Marketing: Customize your B2B marketing strategies with precision using our detailed B2B address data. Target specific geographic areas, refine your approach, and maximize the impact of your marketing efforts.

Use Cases:

Location-Based Services: Companies use Google Address Data to provide location-based services such as navigation, local search, and location-aware advertisements.

Logistics and Transportation: Logistics companies utilize Google Address Data for route optimization, fleet management, and delivery tracking.

E-commerce: Online retailers integrate address autocomplete features powered by Google Address Data to simplify the checkout process and ensure accurate delivery addresses.

Real Estate: Real estate agents and property websites leverage Google Address Data to provide accurate property listings, neighborhood information, and proximity to amenities.

Urban Planning and Development: City planners and developers utilize Google Address Data to analyze population density, traffic patterns, and infrastructure needs for urban planning and development projects.

Market Analysis: Businesses use Google Address Data for market analysis, including identifying target demographics, analyzing competitor locations, and selecting optimal locations for new stores or offices.

Geographic Information Systems (GIS): GIS professionals use Google Address Data as a foundational layer for mapping and spatial analysis in fields such as environmental science, public health, and natural resource management.

Government Services: Government agencies utilize Google Address Data for census enumeration, voter registration, tax assessment, and planning public infrastructure projects.

Tourism and Hospitality: Travel agencies, hotels, and tourism websites incorporate Google Address Data to provide location-based recommendations, itinerary planning, and booking services for travelers.

Discover the difference with Apiscrapy – where accuracy meets diversity in address-related datasets, including Google Address Data, Google Address API, Google Location API, and more. Redefine your approach to location intelligence and make data-driven decisions with confidence. Revolutionize your business strategies today!

DCHC MPO boundary revised boundary that was approved and adopted on November 2012. Triangle Regional Model (TRM), for transportation modeling purposes. Version 5, 2010 base year. Data dictionary available at https://sites.google.com/a/ncsu.edu/dchc-mpo/home The NC State County Boundary GIS data set is to provide location information for the North Carolina State and County Boundary lines with best available information to facilityat planing siting, impact analysis in the 100 counties of NC. Sources for information are NC Division of Transportation, United States Geological Survey and actual field surveys conducted by North Carolina and South Carolina Licensed Surveyors that have been approved and recoded in their respective counties. This file shows some of the boundaries of counties which have a completed boundary survey but the majority of lines have not been surveyed. Also some boundaries cannot be surveyed in cases where boundaries are coincident with river centers. Most of the lines currently are from the DOT county maps which originally come from USGS but might have been updated by the county parcel maps.

NZ Parcel Boundaries Wireframe provides a map of land, road and other parcel boundaries, and is especially useful for displaying property boundaries.
This map service is for visualisation purposes only and is not intended for download. You can download the full parcels data from the NZ Parcels dataset.
This map service provides a dark outline and transparent fill, making it perfect for overlaying on our basemaps or any map service you choose.
Data for this map service is sourced from the NZ Parcels dataset which is updated weekly with authoritative data direct from LINZ’s Survey and Title system. Refer to the NZ Parcel layer for detailed metadata.
To simplify the visualisation of this data, the map service filters the data from the NZ Parcels layer to display parcels with a status of 'current' only.
This map service has been designed to be integrated into GIS, web and mobile applications via LINZ’s WMTS and XYZ tile services. View the Services tab to access these services.
See the LINZ website for service specifications and help using WMTS and XYZ tile services and more information about this service.

The Digital Geologic-GIS Map of Niobrara National Scenic River and Vicinity, Nebraska is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) an ESRI file geodatabase (niob_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (niob_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (niob_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (niob_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (niob_geology_metadata_faq.pdf). Please read the niob_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri.htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (niob_geology_metadata.txt or niob_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:100,000 and United States National Map Accuracy Standards features are within (horizontally) 50.8 meters or 166.7 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS Pro, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

The Digital Geologic-GIS Map of Ocmulgee Mounds National Historical Park and Vicinity, Georgia is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (ocmu_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (ocmu_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (ocmu_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (ocmu_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (ocmu_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (ocmu_geology_metadata_faq.pdf). Please read the ocmu_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Georgia Department of Natural Resources and U. S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (ocmu_geology_metadata.txt or ocmu_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:181,000 and United States National Map Accuracy Standards features are within (horizontally) 91.9 meters or 301.7 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The boundaries for counties and equivalent entities are as of January 1, 2017, primarily as reported through the Census Bureau's Boundary and Annexation Survey (BAS).

This layer contains detailed outlines of Maryland counties. The Maryland land county boundaries were built using political county boundaries and the National Hydrology Data (NHD). Land boundaries are a key geographic featue in our mapping process.This is a MD iMAP hosted service. Find more information at https://imap.maryland.gov.Last Updated: UnknownFeature Service Link:https://geodata.md.gov/imap/rest/services/Boundaries/MD_PhysicalBoundaries/FeatureServer/0

This service displays a complete state-wide digital land use map of Queensland. It is based on the Queensland Land use Mapping Program (QLUMP) data product produced by the Queensland Government. The service presents the most recent mapping of land use features for Queensland. The service is cached to the standard Google / Bing Maps scale levels from 1:591,657,551 to 1:9,028.

KML file of boundary for the city of Chicago. To view or use these files, special GIS software, such as Google Earth, is required.

Digitized from USGS 1:24,000-scale Digital Raster Graphics (scanned topographic maps) by the West Virginia Department of Environmental Protection. First published January 2002, updated with Census 2000 attribute data and re-published March 2005. Scale: 1:24000. Attribute Information includes Federal Information Processing Standards (FIPS) codes and 2000 Census data.Coordinate System: NAD_1983_UTM_Zone_17N

After 2022-01-25, Sentinel-2 scenes with PROCESSING_BASELINE '04.00' or above have their DN (value) range shifted by 1000. The HARMONIZED collection shifts data in newer scenes to be in the same range as in older scenes. Sentinel-2 is a wide-swath, high-resolution, multi-spectral imaging mission supporting Copernicus Land Monitoring studies, including the …

This dataset was created by the Transportation Planning and Programming (TPP) Division of the Texas Department of Transportation (TxDOT) for planning and asset inventory purposes, as well as for visualization and general mapping. County boundaries were digitized by TxDOT using USGS quad maps, and converted to line features using the Feature to Line tool. This dataset depicts a generalized coastline.Date valid as of: February 2015Publish Date: February 2015Update Frequency: StaticSecurity Level: Public

The Forever Wild layer delineates the location of ecologically important natural resources within NYC Parks property.

Map: https://data.cityofnewyork.us/dataset/Forever-Wild-Map/br7w-st33

Data Dictionary and User Guide: https://docs.google.com/spreadsheets/d/1BGfs3SaRlh0p2itOIimg1OQMvfkVuT0NQE6xDitZDQM/edit?usp=sharing

Summary: A comprehensive NSW Land Tenure layer has been developed, integrating the latest and most reliable datasets sourced from various governmental authorities and departments. To the best of our knowledge, this layer offers detailed mapping of recent updates and changes in land tenure across the state. It includes information on land allocations, ownership transformations, and management updates, providing an up-to-date and accurate representation of land tenure in New South Wales. Description: The statewide Land Tenure layer is a comprehensive dataset created by incorporating spatial and aspatial data from various state and commonwealth government departments, organisations and authorities, including the Forestry Corporation of NSW; NSW Department of Primary Industries and Regional Development; NSW Spatial Services; Department of Climate Change, Energy, the Environment and Water (Environment and Heritage); The Australian Department of Agriculture, Fisheries and Forestry (ABARES: SOFR23 & SOFR18); the NSW SEED data portal; and National Park. The wall-to-wall spatial feature class demonstrates how land in NSW is being managed or owned. It can also be employed to monitor changes in land management or ownership transfer over time. The process of acquiring datasets for updating the tenure layer and creating the statewide layer began in January 2024 and continued until August 2024. The collected datasets were amalgamated, and gaps were filled. This combined layer has then been manually assessed and visually compared against various datasets to ensure its completeness and accuracy. Esri basemaps such as Imagery, Imagery Hybrid, OpenStreetMap, and Google Earth maps were also used for visual assessment. Furtheremore, expert knowledge from government professionals, and land history web search were considered to address potential inaccuracies and unreliability in datasets from various sources. The land tenure data consists of seven Tenure classes each class covering various tenure types as below: - Tenure Class: presents tenure classification of the dataset as Crownland-Leasehold; Crownland-Other; Indigenous Owned; National Park; Private; State Forest; Unresolved Tenure. Tenure Type of each tenure class are as follow: Crownland-Leasehold: Crown Timberland Lease; LEASE (SOFR2023); Leasehold Crown Land; Western Lands Lease; Crownland-Other: Crown Road; Crown Waterway; Either Crown Waterway, Road or other; OCL (SOFR2023); Other crownland; Public Road; Reserved Crown Timber Land; Timber Reserve; Vacant And Reserved Crown Land; Vacant Crown Land; Reserve for Public Buildings (Forestry); Indigenous Owned: Aboriginal Area; National Park: Conservation Reserve; Fire trail within national parks; Historic Sites; National Park; Nature Reserve; NCR (SOFR2023); Regional Park; State Conservation Area; Private: Hardwood Joint Venture; PRIV (SOFR2023); Private; Hardwood Plantations; Private Property; Private Softwood Plantation; Profit á Prendre; Softwood Joint Venture; State Forest: FCNSW Ownership; MUF (SOFR2023); State Forest: State Forest OEH Managed Flora Reserve; Unresolved Tenure: null (-2); ND (SOFR2023). - Shape_Area: Area of each Tenure class in square meter. Caveats: - In general, data from diverse sources retains different levels of accuracy, reliability and coverage, therefore, a thorough visual assessment has been carried out to overcome the issue. Having said that, there still could be potential minor errors which could have been missed due to the large extent of the dataset. - Note that Roads, Waterways and general public areas across the Greater Sydney and Wollongong have not been properly mapped in this version. This will be updated in the next update. Data and Resources

While the Waimakariri District Council has taken all reasonable care in providing correct information, all information should be considered as being illustrative and indicative only. Your use of this information is entirely at your own risk. You should independently verify the accuracy of any information before taking any action in reliance upon it.Read full disclaimer here.Abstract:This layer is derived from current primary parcels, as per the NZ Parcels layer on the LINZ Data Service, joined to data on matching current/future properties in WDC’S rating database.Note, this dataset includes a boundary for the primary property address only (as identified in WDC’s rating database) and does not include a boundary for all addresses that may exist on a property.Other information:Addresses:The address datasets contain street number, street name and suburb for physical addresses in Waimakariri.There can be multiple addresses on a property and an example of these are granny flats, farm cottages etc.Click here to view Address Boundary LayerClick here to view Address Point LayerUpdate Frequency:DailyPoint of Contact:Waimakariri District CouncilLineage:Data has been compiled from a number of sources and its accuracy may vary (e.g. Field Verification, Deposited Plans, AsBuilt plans and forms, sketches, aerial photo, Google Street View). There may be delays before data is updated to reflect changes in an area.

CanVec contains more than 60 topographic features classes organized into 8 themes: Transport Features, Administrative Features, Hydro Features, Land Features, Manmade Features, Elevation Features, Resource Management Features and Toponymic Features. This multiscale product originates from the best available geospatial data sources covering Canadian territory. It offers quality topographic information in vector format complying with international geomatics standards. CanVec can be used in Web Map Services (WMS) and geographic information systems (GIS) applications and used to produce thematic maps. Because of its many attributes, CanVec allows for extensive spatial analysis. Related Products: Constructions and Land Use in Canada - CanVec Series - Manmade Features Lakes, Rivers and Glaciers in Canada - CanVec Series - Hydrographic Features Administrative Boundaries in Canada - CanVec Series - Administrative Features Mines, Energy and Communication Networks in Canada - CanVec Series - Resources Management Features Wooded Areas, Saturated Soils and Landscape in Canada - CanVec Series - Land Features Transport Networks in Canada - CanVec Series - Transport Features Elevation in Canada - CanVec Series - Elevation Features Map Labels - CanVec Series - Toponymic Features

Abstract

This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.

This dataset gives the extents of South Australian pastoral lease stations and other properties within the pastoral region of SA. The extents of the properties shown are based on the areas being managed by the leasees and boundaries are defined by fence lines rather than legal lease boundaries. Fences and legal lease boundaries are frequently divergent.

Purpose

This dataset will show the extents of South Australian pastoral lease stations within the pastoral region of SA.

Dataset History

Assessment/Inspection officers visit each station and drive around the property using a mobile device with GPS capability for field data entry including tracking and waypoints of features. The station owner/manager also contribute new information. Maps are often used to explain complex fencing changes. The GIS officer is responsible for adding the changes collected in the field into the database using ESRI ArcGIS software. Imagery and GoogleEarth are often used to verify data collected however often this is based on 2007 or older imagery.Linework is based on data captured from a variety of sources, some of which are not known.

Dataset Citation

SA Department of Environment, Water and Natural Resources (2015) Pastoral Stations - ARC. Bioregional Assessment Source Dataset. Viewed 26 May 2016, http://data.bioregionalassessments.gov.au/dataset/22ce4795-d3a9-432a-89a7-8fe53391d50d.