Clinical Whole Genome Sequencing Market Outlook

According to our latest research, the global market size for Clinical Whole Genome Sequencing (WGS) reached USD 1.85 billion in 2024, demonstrating robust momentum fueled by advances in genomics and precision medicine. The market is witnessing a strong compound annual growth rate (CAGR) of 13.2% from 2025 to 2033, projecting the market value to soar to USD 5.19 billion by 2033. This impressive growth trajectory is primarily driven by the increasing adoption of WGS in clinical diagnostics, the falling cost of sequencing technologies, and the expanding utility of genomic data in healthcare decision-making.

The primary growth factor propelling the Clinical Whole Genome Sequencing market is the rising prevalence of rare and genetic diseases, coupled with the increased demand for personalized medicine. Healthcare providers and researchers are leveraging WGS to identify pathogenic variants responsible for rare disorders, enabling timely and accurate diagnoses that were previously unattainable with traditional genetic testing methods. Furthermore, the integration of WGS into newborn screening programs and its growing use in reproductive health are significantly contributing to the expanding market. The ability of WGS to provide comprehensive genomic information in a single test, as opposed to targeted panels, is transforming clinical workflows and improving patient outcomes across a spectrum of diseases.

Technological advancements in sequencing platforms and bioinformatics are also major catalysts for market growth. The development of high-throughput, cost-effective sequencing instruments and the evolution of robust data analysis software have democratized access to WGS, making it feasible for clinical laboratories of varying scales. Additionally, the emergence of cloud-based genomic data management solutions has simplified the storage, sharing, and interpretation of vast genomic datasets. The continuous innovation in sequencing chemistry, accuracy, and read lengths, including the adoption of nanopore and single-molecule real-time (SMRT) sequencing, is further enhancing the clinical utility of whole genome sequencing.

Another crucial growth driver is the increasing support from governments and private organizations through funding, policy initiatives, and public-private partnerships. Numerous national genomics initiatives, such as the UKÂ’s 100,000 Genomes Project and the US All of Us Research Program, are fostering the integration of WGS into routine clinical practice. These initiatives aim to build large-scale genomic databases that facilitate disease gene discovery, pharmacogenomics, and population health management. The resulting data not only accelerates clinical research but also encourages the development of new diagnostic and therapeutic modalities, creating a positive feedback loop that sustains market expansion.

Clinical NGS Informatics plays a pivotal role in the advancement of Clinical Whole Genome Sequencing by providing the necessary computational tools and platforms for analyzing complex genomic data. As sequencing technologies generate vast amounts of data, the need for sophisticated informatics solutions becomes paramount. These solutions enable the efficient processing, storage, and interpretation of genomic information, facilitating the identification of clinically relevant variants. The integration of Clinical NGS Informatics into healthcare systems is enhancing the precision and accuracy of genomic analyses, thereby improving diagnostic outcomes and personalized treatment plans. By leveraging advanced algorithms and machine learning techniques, informatics platforms are transforming raw sequencing data into actionable insights that drive clinical decision-making and research innovations.

From a regional perspective, North America currently dominates the Clinical Whole Genome Sequencing market, attributed to its advanced healthcare infrastructure, high research and development expenditure, and the presence of key industry players. Europe follows closely, benefiting from strong government support and collaborative research networks. The Asia Pacific region is poised for the fastest growth, driven by increasing healthcare investments, rising awareness of genomics, and the rapid expansion of biotechnology sectors in countries like China, Ja

The dataset contains whole-genome sequencing data (aligned read files) in CRAM-format (lossless compression) for a total of 942 DNA samples, selected to represent a cross-section of the Swedish population. The samples originate from the Swedish Twin Registry (STR) and have been obtained from different geographical regions. For each of the 942 individuals, DNA was extracted from a blood sample and subject to whole genome sequencing (WGS). The WGS was performed using 2x150 bp paired-end chemistry on Illumina HiSeq X Ten instrumentation at the SciLifeLab National Genomics Infrastructure (NGI) in Stockholm and Uppsala. FASTQ files generated by WGS were analyzed using the nf-core pipeline Sarek, which includes pre-processing, alignment to the human GRCh38 reference genome, and germline variant calling. All participants gave their written informed consent and the TwinGene study was approved by the regional ethics committee (Regionala Etikprövningsnämnden, Stockholm, dnr 2007-644-31, dnr 2014/521-32). Access to phenotypic information can be requested from the Swedish Twin Registry (http://ki.se/en/research/the-swedish-twin-registry).

This dataset is 1 of 4 included in the study titled SweGen: a whole-genome data resource of genetic variability in a cross-section of the Swedish population, http://identifiers.org/ega.study:EGAS50000000906.

Microorganisms are ubiquitous in the biosphere, playing a crucial role in both biogeochemistry of the planet and human health. However, identifying these microorganisms and defining their function are challenging. Widely used approaches in comparative metagenomics, 16S amplicon sequencing and whole genome shotgun sequencing (WGS), have provided access to DNA sequencing analysis to identify microorganisms and evaluate diversity and abundance in various environments. However, advances in parallel high-throughput DNA sequencing in the past decade have introduced major hurdles, namely standardization of methods, data storage, reproducible interoperability of results, and data sharing. The National Ecological Observatory Network (NEON), established by the National Science Foundation, enables all researchers to address queries on a regional to continental scale around a variety of environmental challenges and provide high-quality, integrated, and standardized data from field sites across the U.S. As the amount of metagenomic data continues to grow, standardized procedures that allow results across projects to be assessed and compared is becoming increasingly important in the field of metagenomics. We demonstrate the feasibility of using publicly available NEON soil metagenomic sequencing datasets in combination with open access Metagenomics Rapid Annotation using the Subsystem Technology (MG-RAST) server to illustrate advantages of WGS compared to 16S amplicon sequencing. Four WGS and four 16S amplicon sequence datasets, from surface soil samples prepared by NEON investigators, were selected for comparison, using standardized protocols collected at the same locations in Colorado between April-July 2014. The dominant bacterial phyla detected across samples agreed between sequencing methodologies. However, WGS yielded greater microbial resolution, increased accuracy, and allowed identification of more genera of bacteria, archaea, viruses, and eukaryota, and putative functional genes that would have gone undetected using 16S amplicon sequencing. NEON open data will be useful for future studies characterizing and quantifying complex ecological processes associated with changing aquatic and terrestrial ecosystems.

A crucial aspect of validating any clinical assay is the availability of well-characterized samples to assess the specificity and sensitivity of the methodology being tested. However, due to logistical constraints, the biosafety requirements of the specimen studied, or geographic diversity, many laboratories struggle to access adequate clinical specimens or isolates. Consequently, a diverse and well-characterized dataset for standardized assay validation is needed. The Wadsworth Center, the New York State Department of Health's laboratory, has been performing whole-genome sequencing (WGS) on every tuberculosis (TB) case in the state since 2016, along with comprehensive phenotypic drug susceptibility testing (DST) of all drug-resistant isolates. This work has resulted in a large collection of fully characterized clinical Mycobacterium tuberculosis complex isolates, complete with whole-genome sequencing data and paired phenotypic drug resistance profiles. To support the TB community, we have compiled a comprehensive dataset from 50 of these well-characterized isolates, sequenced using the Illumina MiSeq platform. This dataset has been curated to be inclusive of a broad range of lineage diversity, drug resistance types, and resistance-associated gene mutations. This dataset is now available to the community for method development and bioinformatics pipeline validation, serving as a valuable resource to advance research and enhance clinical WGS assays.

The dataset contains files with single nucleotide variants in VCF format for a total of 942 DNA samples, selected to represent a cross-section of the Swedish population. The samples originate from the Swedish Twin Registry (STR) and have been obtained from different geographical regions. For each of the 942 individuals, DNA was extracted from a blood sample and subject to whole genome sequencing (WGS). The WGS was performed using 2x150 bp paired-end chemistry on Illumina HiSeq X Ten instrumentation at the SciLifeLab National Genomics Infrastructure (NGI) in Stockholm and Uppsala. FASTQ files generated by WGS were analyzed using the nf-core pipeline Sarek, which includes pre-processing, alignment to the human GRCh38 reference genome, and germline variant calling. All participants gave their written informed consent and the TwinGene study was approved by the regional ethics committee (Regionala Etikprövningsnämnden, Stockholm, dnr 2007-644-31, dnr 2014/521-32). Access to phenotypic information can be requested from the Swedish Twin Registry (http://ki.se/en/research/the-swedish-twin-registry).

This dataset is 1 of 4 included in the study titled SweGen: a whole-genome data resource of genetic variability in a cross-section of the Swedish population, http://identifiers.org/ega.study:EGAS50000000906.

Small public breeding programs have many barriers to adopting technology, particularly creating, and using genetic marker panels for genomic-based decisions in selection. Here we report the creation of a DArTag panel of 3,000 loci distributed across the tetraploid blueberry genome for use in molecular breeding and genomic prediction. The creation of this marker panel brings cost-effective and rapid genotyping capabilities to public and private breeding programs. The open access provided by this platform will allow genetic data sets generated on the marker panel to be compared and joined across projects, institutions, and countries. This genotyping resource has the power to make routine genotyping a reality for any breeder of blueberry., The blueberry 3K DArTag panel was created from whole-genome skim sequencing (WGS) of 31 cultivated blueberry accessions focused on elite North American breeding lines. A total of 600K SNPs were discovered in the WGS. A high-confidence set of 10K SNPs was then identified using the following criteria: 1) not located within 5 bp from an indel; 2) QUAL > 30; 3) minimum and maximum read depths of 20 and 1500, respectively; 4) at each heterozygous site, at least one read supporting the reference allele and two reads supporting the alternative allele; 5) no missing genotype per SNP position; 6) with a minor allele frequency greater than 0.25; 7) not located in transposable elements or within 1 Kb of chromosome termini; 8) even genomic distribution and mostly located in genic regions. The 10K SNPs were submitted for QC to DArT (Diversity Arrays Technology Pty Ltd, www.diversityarrays.com), from which, a 3K SNP set was selected. Additionally, a few experimentally validated SNPs were also forc..., , # A public mid-density genotyping platform for cultivated Blueberry

https://doi.org/10.5061/dryad.j6q573nnc

The blueberry 3K DArTag panel contains 3K marker loci evenly distributed throughout the blueberry genome. DArT generates genotyping results in several formats, among which the MADC format (missing allele discovery count) provides all the microhaplotypes (54-81 bp) discovered based on amplicons for the 3K marker loci. These microhaplotypes contain target SNPs per assay design as well as off-target SNPs, which are present in flanking amplicon sequences. BI created a microhaplotype database for the 3K blueberry marker loci.

Description of the data and file structure

This project consists of the following datasets:

1. **20200819-BI-Blueberry_10K_SNPs_forDArT_3K.txt:Â **The 3K DArTag panel probe information, which contains the target SNP coordinates, their 180 bp flanking sequences, and reference genome used for the SNP discovery
2. **b...

Data Set Description The dataset consists of whole genome (WGS) and whole exome sequencing (WES) data from 82 biobanked central nervous system (CNS) tumors and patient-matched peripheral blood-derived DNA from 79 affected pediatric patients. The data was generated as part of a study conducted by Díaz de Ståhl, T. et. al., mansucript to be sumitted. The sequence data presented in this publication contains sensitive information and cannot be openly shared. However, the authors intend to share the data for use in research projects after a medicolegal review and controlled access through FEGA Sweden, which is a national node of the Federated European Genome-phenome Archive (FEGA). FEGA Sweden will be hosted by the National Bioinformatics Infrastructure Sweden (NBIS) at SciLifeLab, and the datasets will be findable through the European Genome-phenome Archive web portal. The dataset comprises WGS from 137 samples (70 tumors and 67 blood samples) and WES from 24 samples (12 tumors and 12 blood samples) from several diagnoses, including medulloblastomas, ependymomas, glioblastomas/primitive neuroectodermal tumors/embryonal tumors, pilocytic astrocytomas, astrocytoma/glioma, atypical teratoid rhabdoid tumors, oligodendrogliomas, meningiomas, craniopharyngiomas, pineoblastoma, ganglioglioma, pituitary adenoma, choroid plexus tumor, and schwannoma. The tumor DNA was extracted from fresh frozen tissue, and patient-matched normal DNA was extracted from peripheral blood cells. The WGS and WES libraries and associated next-generation sequencing (NGS) were conducted at the Genomic Production Center, SciLifeLab, Stockholm, Sweden. The WGS libraries were prepared using the TruSeq PCR-free (126 samples) or TruSeq Nano, NeoPrep (11 samples) DNA sample preparation kits, followed by paired-end 150 bp read length sequencing on a HiSeq X (Illumina Inc.) instrument. The WES libraries were prepared using the Agilent SureSelect Human All Exon V5 (22 samples) or the Twist Human Core Exome (2 samples) DNA sample preparation kits, followed by paired-end 100 bp read length sequencing on a HiSeq 2500 (Illumina Inc.) instrument.

Terms for access Access to the pediatric cancer dataset will only be granted to authorized research projects who meet specific ethical and legal criteria and have a clear need for the data. These criteria include adherence to ethical guidelines, such as an ethical permit and obedience to the General Data Protection Regulation (GDPR) It also includes the submission of a research proposal outlining their objectives, methods, and commitment to upholding the highest ethical and legal standards. The protected pediatric dataset is exclusively available for research projects that require access to pediatric data sets and cannot be achieved using adult data. These projects aim to deepen our understanding of the causes and mechanisms of pediatric cancer, identify new therapeutic targets, and develop more effective treatments for affected children. Our goal is to facilitate meaningful research that contributes to better outcomes for pediatric cancer patients in the future.

Access APINSW Transport Theme - Transport Facility Line Please Note WGS 84 = GDA94 serviceThis 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.Transport Facility …Show full description Access APINSW Transport Theme - Transport Facility Line Please Note WGS 84 = GDA94 serviceThis 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.Transport Facility Point is point feature class defining a facility related to transport. Data in the Transport Facility Point include: · Parking Area - an area set aside for the parking of motor vehicles or aircraft · Marina - an area provided with berthing and shore facilities (including toilets, water and rubbish disposal) particularly for yachts and other pleasure craft · Railway Station - a place where passengers are exchanged between vehicles or between transport modes · Helipad - a place for helicopters to land and take-off, like runway is to airport · Roadside Rest Area - a formal area adjacent to the road enabling motorists to take fatigue breaks · Roadside Emergency Telephone - a dedicated telephone adjacent to a road that provides public access to emergency services · Airport - an airport is a listed, public or private known landing strip · Bus Interchange - a connection or terminal point for long distance bus travellers or other major transport interchange · Heavy Vehicle Check Station - a facility to ensure that heavy vehicles meet safety and roadworthiness standards and that their drivers are complying with road transport laws. MetadataType Esri Feature Service Update Frequency As required Contact Details Contact us via the Spatial Services Customer Hub Relationship to Themes and Datasets Transport Theme of the Foundation Spatial Data Framework (FSDF) Accuracy The 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. 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

Next-Generation Sequencing Services Market Outlook

According to our latest research, the global Next-Generation Sequencing (NGS) Services market size reached USD 7.8 billion in 2024, demonstrating robust momentum driven by technological advancements and the expanding application landscape. The market is projected to attain a value of USD 32.1 billion by 2033, progressing at a remarkable CAGR of 17.2% during the forecast period. This dynamic growth is fueled by increasing demand for high-throughput sequencing in clinical diagnostics, drug discovery, and agricultural research, as well as the falling costs of sequencing technologies and widespread adoption across healthcare and research sectors.

A primary growth factor for the Next-Generation Sequencing Services market is the accelerated integration of NGS into clinical diagnostics. As precision medicine and personalized healthcare gain traction, clinicians are increasingly leveraging NGS for comprehensive genomic profiling, hereditary disease screening, and cancer diagnostics. The ability of NGS to deliver rapid, accurate, and scalable results makes it invaluable for identifying genetic mutations, guiding targeted therapies, and improving patient outcomes. This clinical adoption is further supported by regulatory approvals for NGS-based diagnostic tests and the expansion of reimbursement policies, which collectively lower barriers for healthcare providers and patients to access advanced sequencing services.

Another significant driver of market growth is the surge in pharmaceutical and biotechnology research activities that rely on NGS for drug discovery and development. The technology’s capacity to analyze vast genomic datasets enables researchers to uncover novel drug targets, understand disease mechanisms, and accelerate biomarker identification. Pharmaceutical companies are increasingly outsourcing sequencing services to specialized providers, optimizing resource allocation and focusing on core competencies. This trend is complemented by the emergence of companion diagnostics and the growing emphasis on translational research, both of which underscore the critical role of NGS in modern drug pipelines and therapeutic innovation.

The agricultural and animal research sectors are also contributing to the expansion of the Next-Generation Sequencing Services market. With the global population rising and food security becoming paramount, NGS is being harnessed to enhance crop yields, improve livestock breeding, and monitor pathogen outbreaks. Sequencing technologies allow for the identification of beneficial genetic traits, resistance markers, and microbiome profiles, driving advancements in precision agriculture. The integration of NGS in these sectors not only optimizes productivity and sustainability but also addresses challenges posed by climate change and evolving consumer demands for safer, more nutritious food products.

From a regional perspective, North America remains the largest market for NGS services, accounting for a substantial share of global revenues in 2024, followed closely by Europe and the Asia Pacific. The dominance of North America is attributed to the presence of leading sequencing service providers, robust healthcare infrastructure, and active government funding for genomics research. However, Asia Pacific is emerging as the fastest-growing region, propelled by increasing investments in healthcare, expanding research initiatives, and the rising prevalence of genetic disorders. Latin America and Middle East & Africa are also witnessing steady growth, albeit from a lower base, as awareness and accessibility to advanced sequencing technologies improve.

Service Type Analysis

The service type segment of the Next-Generation Sequencing Services market encompasses whole genome sequencing, targeted sequencing, exome sequencing, RNA sequencing, and other specialized offerings. Whole genome sequencing (WGS) continues to gain traction as it provides the most comprehensive insight into an individual’s genetic makeup, enabling the identification of both common and rare genetic variants. The decreasing cost per genome, coupled with improvements in sequencing accuracy and speed, has made WGS increasingly accessible for both research and clinical applications. This segment is particularly favored for large-scale population studies and rare disease research, where deep genomic insights are critical for discovery and diagnosis.<

Access API Administrative Boundaries Theme - Parish 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 Administrative Boundaries Theme - Mines Subsidence DistrictContent TypeHosted Feature LayerDescriptionNSW Parish is a dataset within the Administrative Boundaries Theme of the FSDF. It contains 7,459 administrative areas (Parishes) formed by the division of 141 counties. Counties and parishes are administrative divisions of the state and are not separately disposable land parcels. County and Parish are historical layers and the information contained on these layers was gathered from Parish and County maps which are now held at State Records (digital versions can be accessed through the Historical Lands Records Viewer). However, they can be updated (if necessary) after a title inspection.Parishes are divided into separately land parcels called “portions”, these being the common basic units of land disposed of by the Crown (sold), held in occupation (leased) or reserved for public purposes. Other basic units are section and allotments in Towns and Villages. The dataset contains county and parish names. Any changes that occur to the dataset should have a reference in the authority of reference feature class in the lot and property data sets.Features are positioned in topological alignment within the extents of the land and property polygons for each county and are held in alignment, including changes resulting cadastral maintenance and upgrades. NSW Parish is a subset of NSW County.This dataset contains an historical land administration boundary. The original Parish definition is static, however, data will move with changes to the Land Parcel and Property theme.Initial Publication Date05/02/2020Data 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:4326WGS84 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

🇦🇺 Australia English Export Data Access API NSW Features of Interest Category - Place 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 functionality. Metadata Portal Metadata InformationContent TitleNSW Features of Interest Category - Place PointContent TypeHosted Feature LayerDescriptionPlace point is a point feature class within the Features of interest Category. There is no overall accuracy reported in the database, however accuracy of the individual feature instances of each feature class can be found in the database tables.The currency of the feature instances in this dataset can be found in “feature reliability date” or “attribute reliability date” attributes. All feature instances in this class are attributed with a planimetric accuracy value. It is expected that the 90% of well-defined points with the same planimetric accuracy are within 0.5mm of that map scale. Depending on the capture source, capture method, digital update and control point upgrade, every feature instance reported has a positional accuracy within the range of 1m - 100m.Place Points included in the layer include:City - A centre of population, commerce and culture with all essential services; a town of significant size and importance, generally accorded the legal right to call itself a city under, either, the Local Government Act, the Crown Lands Act or other instruments. This point feature dataset is part of Spatial Services Defined Administrative Data Sets. City data points are positioned within the cadastral parcel in which they are located.Locality - A bounded area within the landscape that has a rural character. Locality data points are positioned within the cadastral parcel in which they are located.Region - A region is a relatively large tract of land distinguished by certain common characteristics, natural or cultural. Natural unifying features could include same drainage basin, similar landforms, or climatic conditions, a special flora or fauna, or the like. This point feature dataset is part of Spatial Services Defined Administrative Data Sets. Region data points are positioned within the cadastral parcel in which they are located.Rural Place - A place, site or precinct in a rural landscape, generally of small extent, the name of which is in current use. This point feature dataset is part of Spatial Services Defined Administrative Data Sets. Rural place data points are positioned within the cadastral parcel in which they are located.Suburb - A gazetted boundary of a suburb or locality area as defined by the Geographical Names Board of NSW. This point feature dataset is part of Spatial Services Defined Administrative Data Sets. Suburb data points are positioned within the cadastral parcel in which they are located.Town - A commercial nucleus offering a wide range of services and a large number of shops, often several of the same type. Depending on size, the residential area can be relatively compact or (in addition) dispersed in clusters on the periphery. This point feature dataset is part of Spatial Services Defined Administrative Data Sets. Town data points are positioned within the cadastral parcel in which they are located.Urban Place - A place, site or precinct in an urban landscape, the name of which is in current use, but the limits of which have not been defined under the address locality program. This point feature dataset is part of Spatial Services Defined Administrative Data Sets. Urban place data points are positioned within the cadastral parcel in which they are located.Village - A cohesive populated place in a rural landscape, which may provide a limited range of services to the local area. Residential subdivisions are in urban lot sizes. This point feature dataset is part of Spatial Services Defined Administrative Data Sets. Village data points are positioned within the cadastral parcel in which they are located.Initial Publication Date06/02/02020Data 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 Features of Interest Category.AccuracyThe 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 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 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 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

Export Data Access APIAdministrative Boundaries Theme - NSW NPWS ReservePlease 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 Administrative Boundaries Theme - National Park and Wildlife Services ReserveContent TypeHosted Feature LayerDescriptionNSW NPWS Reserve is a dataset within the NSW Administrative Boundaries Theme (FSDF).The dataset contains National Park, Nature Reserve, Historic Site, Regional Park, Karst Conservation Reserve, Aboriginal Area, and State Conservation Area. It identifies under the terms of the National Parks and Wildlife Act, 1974, certain areas of NSW that have been reserved.Office of Environment and Heritage (OEH) is responsible for this dataset. Any changes that occur to the dataset should have a reference in the authority of reference feature class in the Administrative boundary theme.Features are typically positioned in alignment within the extents of the Land Parcel and Property theme changes impact this dataset and maintained from information sourced from Office of Environment and Heritage and NSW Government Gazette notices.Initial Publication Date05/05/2020Data 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.au© State of New South Wales (Department of Climate Change, Energy, the Environment and Water)Data 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:4326WGS84 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 CustodianDepartment of Climate Change, Energy, the Environment and Water - Environment and HeritagePhone: 1300 361 967Email: info@environment.nsw.gov.auPoint 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

Access APINSW Features of Interest Category - Place Area 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 Features of Interest Category - Place Area 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. Place Area is a polygon feature class defining a named place. Themes included in the Place Area include: Region - A region is a relatively large tract of land distinguished by certain common characteristics, natural or cultural. Natural unifying features could include same drainage basin, similar landforms, or climatic conditions, a special flora or fauna, or the like. This polygon feature dataset is part of Spatial Services Defined Administrative Data Sets. Where possible, polygon geometries of the region dataset align to Spatial Services Defined Administrative Data Sets. Locality - A bounded area within the landscape that has a rural character. This polygon feature dataset is part of Spatial Services Defined Administrative Data Sets. Where possible, polygon geometries of the locality dataset align to Spatial Services Defined Administrative Data Sets. City - A centre of population, commerce and culture with all essential services; a town of significant size and importance, generally accorded the legal right to call itself a city under, either, the Local Government Act, the Crown Lands Act or other instruments. This polygon feature dataset is part of Spatial Services Defined Administrative Data Sets. Where possible, polygon geometries of the city dataset align to Spatial Services Defined Administrative Data Sets. Village - A cohesive populated place in a rural landscape, which may provide a limited range of services to the local area. Residential subdivisions are in urban lot sizes. This polygon feature dataset is part of Spatial Services Defined Administrative Data Sets. Where possible, polygon geometries of the village dataset align to Spatial Services Defined Administrative Data Sets Town - A commercial nucleus offering a wide range of services and a large number of shops, often several of the same type. Depending on size, the residential area can be relatively compact or (in addition) dispersed in clusters on the periphery. This polygon feature dataset is Spatial Services Defined Administrative Data Sets. Where possible, polygon geometries of the town dataset align to the Spatial Services Defined Administrative Data Sets. Suburb - A gazetted boundary of a suburb or locality area as defined by the Geographical Names Board of NSW. This polygon feature dataset is part of Spatial Services Defined Administrative Data Sets. Where possible, polygon geometries of the suburb dataset align to Spatial Services Defined Administrative Data Sets. Urban Place - A place, site or precinct in an urban landscape, the name of which is in current use, but the limits of which have not been defined under the address locality program. This polygon feature dataset is part of Spatial Services Defined Administrative Data Sets. Where possible, polygon geometries of the urban place dataset align to Spatial Services Defined Administrative Data Sets. Rural Place - A place, site or precinct in a rural landscape, generally of small extent, the name of which is in current use. This polygon feature dataset is part of Spatial Services Defined Administrative Data Sets. Where possible, polygon geometries of the rural place dataset align to Spatial Services Defined Administrative Data Sets. MetadataType Esri Feature 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

Export Data Access API NSW Features of Interest Category - Utility Water Supply Canal 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 functionality. Metadata Portal Metadata InformationContent TitleNSW Features of Interest Category - Utility Water Supply CanalContent TypeHosted Feature LayerDescriptionA utility water supply canal is an artificial watercourse to convey water. This line feature dataset is part of Spatial Services Defined Administrative Data Sets.Where possible, line geometries of the utility water supply canal dataset align to Spatial Services Defined Administrative Data Sets. The features in this dataset are part of Spatial Services Defined Administrative Data Sets and can be displayed with other Defined Administrative Data in their correct relative position.Initial Publication Date06/02/02020Data 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 Features of Interest Category.AccuracyThe 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 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 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 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

Export Data Access API NSW Features of Interest Category - Health FacilitiesPlease 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 functionality. Metadata Portal Metadata InformationContent TitleNSW Features of Interest Category - Health FacilitiesContent TypeHosted Feature LayerDescriptionThe NSW Features of Interest Category – Health 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 - Health Category service include:Ambulance - An ambulance station is a structure or other area set aside for storage of ambulance vehicles and medical equipment. This point feature dataset is part of the Features of Interest Category Database.Children’s Hospital - A hospital specifically for the care of children.General Hospital - An institution in which the sick or injured persons are given medical or surgical treatment.Psychiatric Hospital - A hospital for the care and treatment of patients affected with acute or chronic mental illness.These point feature datasets are part of the Features of Interest Category data and all the Health-related data centroids 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.Initial Publication Date25/02/2021Data 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 Features of Interest Category.AccuracyThe 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 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 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 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

Export Data Access API NSW Features of Interest Category - Emergency Service Facilities Please NoteWGS 84 service aligned to GDA94This dataset has a 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 Features of Interest - Emergency Service FacilitiesContent TypeHosted Feature LayerDescriptionThe Features of Interest – Emergency Services is a point feature dataset that represents the location of Emergency Services - related datasets such as Police, Fire and SES Stations which is crucial to delivery of Emergency Services to NSW. The Features of Interest category Emergency 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 - Emergency Services include: Fire Station – Urban (Fire and Rescue NSW) - The facility in which firefighting vehicles and equipment are stationed or intended to be stationed to serve urban communities. This point feature dataset is part of the Features of interest Category. Fire station (located in an urban area) data points are positioned within the cadastral parcel in which they are located. Fire Station - Bush (NSW Rural Fire Service) - The facility in which firefighting vehicles and equipment are stationed or intended to be stationed to serve rural communities. This point feature dataset is part of the Features of interest Category. Fire station (located in bushland) data points are positioned within the cadastral parcel in which they are located. Police Station - An office of the local police force, which may or may not have associated lock-up. This point feature dataset is part of the Features of interest Category. Police stations data points are positioned within the cadastral parcel in which they are located. State Emergency Service (SES) - A facility for the operations of the State Emergency Services (SES). This point feature dataset is part of the Features of interest Category. SES facility data points are positioned within the cadastral parcel in which they are located. These point feature datasets are part of the Features of Interest Category data and all the Emergency Services -related data centroids 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.Initial Publication Date25/02/2021Data 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 Features of Interest Category.AccuracyThe 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 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 ClassificationUnclassified Data Access PolicyOpenData QualityFor additional information, please contact us via the Spatial Services Customer Hub Terms 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

Export Data Access API NSW 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 functionality. Metadata Portal Metadata Information Content TitleNSW Features of Interest Category - Justice FacilitiesContent TypeHosted Feature LayerDescriptionThe 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.Initial Publication Date25/02/2021Data 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 Features of Interest Category.AccuracyThe 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 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 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 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 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

Recommended citation

Galizia, L. F., Curt, T., Barbero, R., and Rodrigues, M.: Assessing the accuracy of remotely sensed fire datasets across the southwestern Mediterranean Basin, Nat. Hazards Earth Syst. Sci., 21, 73–86, https://doi.org/10.5194/nhess-21-73-2021, 2021.

Use of the dataset and full description

Before using the dataset, please read this document and the article describing the methodology.

Abstract

This harmonized database (GBD) was constructed from multiple regional/national fire agencies datasets including fire records from Portugal, Spain, France, and Sardinia in Italy. We extracted, for each agency dataset, the following information: day of ignition, fire size, and location of the fire. To ensure consistency across regions, we provide here the overlapping record period among the datasets, i.e., 2005–2015. Small fires (<1ha) were discarded to ensure the coherence of the analysis since these were not reported systematically by AG. We aggregated datasets onto a 0.25° grid (≈ 25 km) and at a monthly scale, setting a common ground across the Southwestern Mediterranean basin. The harmonized GBD database contains 95,561 fire records, including only events that required a firefighting response (i.e., disregarding agricultural and prescribed fires).

Files included in the dataset

The repository comprises two files. The aggregated fire events come in a csv file while the study domain comes in a shapefile file.

AG_fires.csv: Harmonized fire agencies (GBD) datasets aggregated at spatio-temporal scales. Coordinate reference system in WGS 84 (EPSG:4326).

“ID”: Fire event ID.

“X”: X coordinate (Longitude) of the center of each grid.

“Y”: Y coordinate (Latitude) of the center of each grid.

“Date”: Date of fire event in Year-month.

“NF”: Total number of fire events in the grid.

“BA”: Total burned area (ha) in the grid.

Study_domain.zip: Spatial extent of the study domain in ESRI Shapefile. Coordinate reference system in WGS 84 (EPSG:4326).

Agencies data sources

All regional/national datasets are open access except EGIF (Spain) that is available upon request.

DECIF: http://www2.icnf.pt/portal/florestas/dfci/inc/estat-sgif

EGIF: https://www.mapa.gob.es/va/desarrollo-rural/estadisticas/Incendios_default.aspx

Prométhée: https://www.promethee.com/

Regione Sardegna: http://webgis2.regione.sardegna.it/download/

Acknowledgments

The ground-based data used in this work have been collected several from regional/national fire agencies. In France, the original fire data was collected from the official database (Prométhée) for forest fires in the French Mediterranean area. The Centre for National Information on Forest Fires (CCINIF), agency responsible for coordinating general forest fires statistics in Spain (EGIF) within the Ministry for the Ecological Transition and demographic challenge provided the original fire data at the country level. In Portugal, the original fire data was collected from the Special Forest Fire Fighting Agency (DECIF, Dispositivo Especial de Combate a Incêndios Florestais) a publicly available fire database in the country level. In Sardinia, the original fire data was extracted from the Regione Sardegna Geoportale the official mapping agency of the Autonomous Region of Sardinia in Italy, which provides datasets at the regional level.

EMAG2v3: the Earth Magnetic Anomaly Grid (2 arc-minute resolution), version 3 is compiled from satellite, ship, and airborne magnetic measurements. Magnetic anomalies result from geologic features enhancing or depressing the local magnetic field. These maps increase knowledge of subsurface structure and composition of the Earth's crust. Global magnetic anomaly grids are used for resource exploration, navigation where GPS is unavailable (submarine, directional drilling, etc.), and for studying the evolution of the lithosphere.The 2017 release of the EMAG2v3 utilizes updated precompiled grids and a revised process for accurately incorporating the long-wavelength anomalies, as modeled by the satellite-based MF7 lithospheric field model. It is an update from the previous EMAG2v3 released by NCEI in 2016. EMAG2v3 further differs from the previous EMAG2 (version 2), which relied on an ocean age model to interpolate anomalies into non-existent data areas and on the earlier MF6 model. EMAG2v3 relies solely on the data available. As a result, EMAG2v3 better represents the complexity of these anomalies in oceanic regions and accurately reflects areas where no data has been collected. The current version reports anomalies in two ways:A consistent altitude of 4 km (referred to as Upward Continued)Anomaly altitude at Sea LevelThis tile layer displays a color relief image of the EMAG2v3 (Upward Continued) rendered with a "hillshade" effect to simulate a 3D surface. A coastline is also provided for reference. The magnetic anomaly values in nanotesla (nT) are displayed using the color ramp below:The EMAG2 dataset illustrates Earth evolution (plate tectonics and crustal interaction with the deep mantle). Distinct patterns and magnetic signatures are attributed to the formation (seafloor spreading) and destruction (subduction zones) of oceanic crust, and the formation of continental crust by accretion of various terranes to cratonic areas and large scale volcanism (both on continents and oceans).Magnetization is weaker at the equator and stronger at high latitudes, reflecting the strength of the ambient geomagnetic field, which induces magnetization in rocksStripes of alternating magnetization in the oceans are due to sea floor spreading and the alternating polarity of the geomagnetic fieldVery old crust (North American Shield, Baltic Shield, Siberian Craton) have strongest magnetization, seen as dark shades of purple and blueThere are four related ArcGIS services providing access to EMAG2v3:Color shaded relief image (tiled, Web Mercator projection)Color shaded relief image (tiled, WGS84 geographic)Multi-layer map serviceImage service (provides data values)