AndreaBozzo/ceres-open-data-index huggingface dataset:
DBCA South West Vegetation Complex Statistics

Please note:
These reports are provided as a historic archive only and are not current. If you have an ongoing requirement to use the statistics, to meet a legislative or policy requirement, please seek advice from the relevant WA Government Department or Authority rather than contacting the Data Custodians listed under Key Information. If you use the reports, please include a caveat stating the following: (1) year of currency, (2) a statement that the statistics presented may now be out of date, and (3) the report citation.
Important update (October 2025):
The Department of Water and Environmental Regulation (DWER) have updated the remnant vegetation mapping and statistics for the Swan Coastal Plain and Region Schemes and, they are available on DataWA. Please refer to the Swan Coastal Plain and Region Schemes 2024 Remnant Vegetation Statistics available at:
https://catalogue.data.wa.gov.au/dataset/swan-coastal-plain-and-region-schemes-2024-remnant-vegetation-statistics
The Swan Coastal Plain and Region Schemes 2024 Remnant Vegetation Statistics provide status of remnant vegetation for the Swan Coastal Plain bioregion, the Metropolitan, Peel and portion of the Greater Bunbury Region Scheme areas, and local government areas within these regions.
The mapping and statistics for the South West Forest outside of the Perth and Peel Region Schemes have not been updated by DWER.
Overview of the Report
From 2016 to 2018, DBCA provided annual updates of statistics on the pre-European and current extent of the vegetation complexes of the south-west of Western Australia and are based on more detailed vegetation complex mapping than the Statewide vegetation association mapping. The statistics were used for several purposes including conservation planning, land use planning and when assessing development applications.
The statistics provided a general overview of the status of vegetation complexes, noting the limitations detailed in the README document relating to scale, remnant vegetation mapping and currency of the analysis. They were intended to be used in conjunction with other information on the biodiversity values of an area and with input and advice from people familiar with the vegetation complex and the vegetation condition of an area of interest.
For the Swan Coastal Plain and South-West Forests regions, three reports are included:
· CAR Report - provides information on the progress towards achieving a conservation reserve system that is comprehensive, adequate, and representative (CAR Reserve Analysis);
· Region Scheme Report – provides supporting statistics regarding EPA policies for Region Scheme areas;
· LGA Report – summary statistics for each LGA.
A CAR system of reserves helps conserve our biodiversity. Please contact DBCA for advice on the CAR statistics.

Tags: CAR, DBCA, DPAW, DWER, EPA, PEEL, PERTH, Pre-European, Region, Remnant, Schemes, complex, south-west, statistics, vegetation
Organization: Department of Biodiversity, Conservation and Attractions
AWAC - Acoustic Wave and Current Stations (DOT-026)

Short term acoustic wave and current data is collected using Nortek AWAC instruments. The AWAC instruments are deployed on a fixed mooring on the sea bed. The instruments are delayed mode systems where the data is stored in memory of the instrument as the data is collected. The data is retrieved from the instruments when the instruments are recovered from the water at the end of the deployment. The deployment period is determined by the battery life and memory capacity of the instrument. The raw binary data files downloaded from the instruments are post processed through specialist software to produce files of wave, current, temperature, water level and instrument status data. The post-process files are then archived without being analysed by DoT staff. 

Tags: Coastal Protection, DOT-006, coastline, marine habitat, oceans, transport
Organization: Department of Transport
GP Catchment 2023 - Modified Monash Model 2023

General Practitioner Catchment (GPC)
 
Developed by the Australian Government Department of Health and Aged Care as custom aggregations of the Australian Bureau of Statistics (ABS) Australian Statistical Geography Standard (ASGS) 2021 Statistical Area Level 1 (SA1), Statistical Area Level 2 (SA2), Statistical Area Level 3 (SA3), and Urban Centre and Locality (UCL) geographies. 
The GP catchment areas give a more accurate picture of where patients access their health services. 
 
Modified Monash Model (MMM)
 
The Modified Monash Model (MMM) is a classification system used to define the remoteness of Australian locations, ranging from MM 1 (major cities) to MM 7 (very remote areas). It combines population size and geographic remoteness to guide health workforce planning, especially in rural and remote communities. MMM is based on the Australian Statistical Geography Standard – Remoteness Areas (ASGS-RA) and is updated after each national Census conducted by the ABS.
 
Estimated Resident Population (ERP)
 
The Estimated resident population is the official estimate of the Australian population, which links people to a place of usual residence within Australia. Usual residence is the address at which a person considers themselves to currently live. ERP includes all people who usually live in Australia (regardless of nationality, citizenship or legal status), with the exception of foreign diplomatic personnel and their families.

Tags: ABS, ERP, Estimated Resident Population, GPC, General Practitioner, Geographical Classification System, MMM, Modified Monash Model, Remoteness Area, population
Organization: Department of Health and Aged Care
Sea Surface Temperature Warming Rates in Australian Marine Parks according to the SSTAARS

This dataset measures the mean decadal warming rates of the sea surface temperature (SST) in 58 Australian Marine Parks (with the exception of the Heard Island and McDonald Islands Marine Park) over the past 25 years (1992 to 2016). They are derived from the Sea Surface Temperature Atlas of the Australian Regional Seas (SSTAARS). The field of “trend_d” represents the linear SST trend for March 1992 to December 2016. The unit of the warming rates is Celsius degree/per decade.
This research is supported by the National Environmental Science Program (NESP) Marine Biodiversity Hub through Project D1.

Tags: Marine Biodiversity Hub, Marine Park, National Environmental Science Program, Published_External, Remote Sensing, SST
Organization: Geoscience Australia Data
GP Catchment 2023 - Modified Monash Model 2019

General Practitioner Catchment (GPC)
 
Developed by the Australian Government Department of Health and Aged Care as custom aggregations of the Australian Bureau of Statistics (ABS) Australian Statistical Geography Standard (ASGS) 2021 Statistical Area Level 1 (SA1), Statistical Area Level 2 (SA2), Statistical Area Level 3 (SA3), and Urban Centre and Locality (UCL) geographies. 
The GP catchment areas give a more accurate picture of where patients access their health services. 
 
Modified Monash Model (MMM)
 
The Modified Monash Model (MMM) is a classification system used to define the remoteness of Australian locations, ranging from MM 1 (major cities) to MM 7 (very remote areas). It combines population size and geographic remoteness to guide health workforce planning, especially in rural and remote communities. MMM is based on the Australian Statistical Geography Standard – Remoteness Areas (ASGS-RA) and is updated after each national Census conducted by the ABS.
 
Estimated Resident Population (ERP)
 
The Estimated resident population is the official estimate of the Australian population, which links people to a place of usual residence within Australia. Usual residence is the address at which a person considers themselves to currently live. ERP includes all people who usually live in Australia (regardless of nationality, citizenship or legal status), with the exception of foreign diplomatic personnel and their families.

Tags: ABS, ERP, GPC, General Practitioner, Geographical Classification System, MMM, MMM 2019, Modified Monash Model, Remoteness Area
Organization: Department of Health and Aged Care
ASGS SA4 2021 by GP Catchments 2023

General Practitioner Catchment (GPC)
 
Developed by the Australian Government Department of Health and Aged Care as custom aggregations of the Australian Bureau of Statistics (ABS) Australian Statistical Geography Standard (ASGS) 2021 Statistical Area Level 1 (SA1), Statistical Area Level 2 (SA2), Statistical Area Level 3 (SA3), and Urban Centre and Locality (UCL) geographies. 
The GP catchment areas give a more accurate picture of where patients access their health services. 
 
Statistical Area Level 4 (SA4)
 
SA4s are the largest sub-state regions used in the Australian Statistical Geography Standard (ASGS), built from SA3s. They are designed to reflect labour markets and the functional areas of capital cities, supporting the release of regional data such as the Quarterly Labour Force Survey. There are 108 SA4s across Australia, including special codes for mobile or unlocated populations. SA4s aggregate to form Greater Capital City Statistical Areas and States/Territories.

Tags: ABS, ASGS, GPC, GPC 2023, General Practitioner, Geographical Classification System, SA4, SA4 2021
Organization: Department of Health and Aged Care
ASGS SA3 2021 by GP Catchments 2023

General Practitioner Catchment (GPC)
 
Developed by the Australian Government Department of Health and Aged Care as custom aggregations of the Australian Bureau of Statistics (ABS) Australian Statistical Geography Standard (ASGS) 2021 Statistical Area Level 1 (SA1), Statistical Area Level 2 (SA2), Statistical Area Level 3 (SA3), and Urban Centre and Locality (UCL) geographies. 
The GP catchment areas give a more accurate picture of where patients access their health services. 
 
Statistical Area Level 3 (SA3)
 
SA3s are regional areas used in the Australian Statistical Geography Standard (ASGS). Formed by grouping SA2s with similar characteristics, they provide a standard framework for analysing ABS data at the regional level, including Census outputs. Australia has 359 SA3s, including codes for non-geographically defined populations. SA3s are used to support regional planning and policy development, and they aggregate to form SA4s.

Tags: ABS, ASGS, GPC, GPC 2023, General Practitioner, Geographical Classification System, SA3, SA3 2021
Organization: Department of Health and Aged Care
ASGS SA2 2021 by GP Catchments 2023

General Practitioner Catchment (GPC)
 
Developed by the Australian Government Department of Health and Aged Care as custom aggregations of the Australian Bureau of Statistics (ABS) Australian Statistical Geography Standard (ASGS) 2021 Statistical Area Level 1 (SA1), Statistical Area Level 2 (SA2), Statistical Area Level 3 (SA3), and Urban Centre and Locality (UCL) geographies. 
The GP catchment areas give a more accurate picture of where patients access their health services. 
 
Statistical Area Level 2 (SA2)
 
SA2s are geographic units used in the Australian Statistical Geography Standard (ASGS). Built from SA1s, they are designed to represent communities with shared social and economic interactions. There are 2,473 SA2s across Australia, including special codes for populations without fixed locations. SA2s are commonly used for publishing non-Census ABS statistics such as health and population estimates, and they form the basis for SA3s and other regional structures like Significant Urban Areas and Tourism Regions.

Tags: ABS, ASGS, GPC, GPC 2023, General Practitioner, Geographical Classification System, SA2, SA2 2021
Organization: Department of Health and Aged Care
ASGS SA1 2021 by GP Catchments 2023

General Practitioner Catchment (GPC)
 
Developed by the Australian Government Department of Health and Aged Care as custom aggregations of the Australian Bureau of Statistics (ABS) Australian Statistical Geography Standard (ASGS) 2021 Statistical Area Level 1 (SA1), Statistical Area Level 2 (SA2), Statistical Area Level 3 (SA3), and Urban Centre and Locality (UCL) geographies. 
The GP catchment areas give a more accurate picture of where patients access their health services. 
 
Statistical Area Level 1 (SA1)
 
SA1s are geographic units used in the Australian Statistical Geography Standard (ASGS), designed to provide detailed Census data. Built from Mesh Blocks, SA1s aggregate into SA2s and serve as foundational units for various statistical structures, including urban and Indigenous classifications. There are 61,845 SA1s across Australia, including special codes for populations without fixed addresses, such as those in transit or with no usual residence.

Tags: ABS, ASGS, GPC, GPC 2023, General Practitioner, Geographical Classification System, SA1, SA1 2021
Organization: Department of Health and Aged Care
Sports and recreation facilities

The City of Sydney offers a variety of sports and recreation options across its facilities. Book a court, join a sports competition, use a fitness station or go for a swim at one of the many facilities in the City of Sydney. This dataset contains the locations of sport and recreation facilities in the City of Sydney including type of sport and description of facility. View this dataset in the sports and recreation facilities app.

Tags: asset amenity, city council, culture leisure sport, fitness, health, indoors, outdoors, recreation, sports
Organization: City of Sydney
FES Industry of occupation

The floor space and employment survey collects data on all businesses, floor space uses and employment numbers for every building or property in the City of Sydney local area every 5 years. The 2022 floor space and employment survey was the fourth full survey within the current City of Sydney local area boundaries. Previous surveys were undertaken in 2007, 2012 and 2017.    The business establishment dataset contains the point location of each business establishment within a building from the 2007, 2012, 2017 and 2022 floor space and employment survey.    Each business establishment is classified using a composite city-based industry classification to report on the various industry sectors across the local area, categorised by the main function of a business. The classifications are based on an expanded version of the Australian and New Zealand Standard Industrial Classification (ANZSIC) 2006.   For more information on the floor space and employment survey, visit the City of Sydney website.

Tags: City of Sydney, FES, Land Use Planning, business, economy and business, floorspace
Organization: City of Sydney
Flora and Fauna Report. For Lot 42 DP55549. Elvenwood. 1213 Bells Line of Road, Kurrajong Heights. (Aug. 2001).

Flora and Fauna Report. For Lot 42 DP55549. Elvenwood. 1213 Bells Line of Road, Kurrajong Heights. (Aug. 2001).

Tags: FIS
Organization: NSW Department of Climate Change, Energy, the Environment and Water
Local Development Performance Monitoring 2009-10

The LDPM data provides an outline of the performance of the NSW planning system and information on local and regional development determined by councils, private certifiers and joint regional planning panels.
Councils provide the Department with information on each DA and Section 96 modification application (S96) determined by council, and on CDC's determined by council or private certifiers. This is supplemented by information from joint regional planning panels. However, the majority of the data continues to come from councils.
The department issued councils with a template for data and explanatory material including data definitions. Councils generally extract their information from DA tracking databases or, for smaller country councils, DA registers.
Data analysis was undertaken by the Department using standard calculations (for a detailed explanation, refer to the "Data Quality Statement" tab of the Summary Data attached as a resource to this data set ).

Tags: Councils, HUMAN-ENVIRONMENT-Housing, HUMAN-ENVIRONMENT-Planning, LDPM, Local Development Performance Monitoring, Monitoring, Performance
Organization: NSW Department of Planning, Housing and Infrastructure
NSW Blue Carbon Compatibility under 2017 Landuse

Human activities in coastal landscapes also exert both direct and indirect pressures on blue carbon (McLeod et al., 2011). Rogers et al. (2019) accounted for this pressure using land-use mapping, with the premise being that natural landscapes are more compatible with storage, preservation, and generation of blue carbon, whilst intensive land-use activities are less compatible. They proposed that this approach partly accounts for socio-economic factors that influence blue carbon. In this study, 2017 land-use mapping was reclassified based on perceived present-day compatibility with blue carbon to generate a blue carbon compatibility (BCC) raster dataset.
McLeod, E., Chmura, G.L., Bouillon, S., Salm, R., Björk, M., Duarte, C.M., Lovelock, C.E., Schlesinger, W.H., and Silliman, B.R. (2011). A blueprint for blue carbon: toward an improved understanding of the role of vegetated coastal habitats in sequestering CO2. Frontiers in Ecology and the Environment 9, 552-560.
Rogers, K., Macreadie, P.I., Kelleway, J.J., and Saintilan, N. (2019b). Blue carbon in coastal landscapes: a spatial framework for assessment of stocks and additionality. Sustainability Science 14, 453-467.

Tags: Blue Carbon, Estuary, landuse, mangroves, saltmarsh
Organization: Department of Primary Industries and Regional Development (DPIRD)
Local Development Performance Monitoring 2014-15

The LDPM data provides an outline of the performance of the NSW planning system and information on local and regional development determined by councils, private certifiers and joint regional planning panels.
Councils provide the Department with information on each DA and Section 96 modification application (S96) determined by council, and on CDC's determined by council or private certifiers. This is supplemented by information from joint regional planning panels. However, the majority of the data continues to come from councils.
The department issued councils with a template for data and explanatory material including data definitions. Councils generally extract their information from DA tracking databases or, for smaller country councils, DA registers.
Data analysis was undertaken by the Department using standard calculations (for a detailed explanation, refer to the "Data Quality Statement" tab of the Summary Data attached as a resource to this data set ).

Tags: Councils, HUMAN-ENVIRONMENT-Housing, HUMAN-ENVIRONMENT-Planning, LDPM, Local Development Performance Monitoring, Monitoring, Performance
Organization: NSW Department of Planning, Housing and Infrastructure
Genetic management of threatened koala populations: Using genotyping-by-sequencing to define meaningful conservation goals

Genetic management is a critical component of threatened species conservation. Understanding spatial patterns of genetic diversity is essential for evaluating the resilience of fragmented populations to accelerating anthropogenic threats. Nowhere is this more relevant than on the Australian continent, which is experiencing an ongoing loss of biodiversity that exceeds any other developed nation. However, while threatened species management is generally the purview of state governments, intensive data collection at this scale is often neglected, despite arguably being the most useful for guiding ongoing conservation efforts. Using a proprietary genome complexity reduction-based method, we generated a data set of high-quality Single Nucleotide Polymorphisms (SNPs) to investigate spatial patterns and indices of genetic diversity in the koala (Phascolarctos cinereus), a highly specialised folivorous marsupial that is experiencing rapid and widespread population declines across much of its former range. Genotyping of 314 individual koalas sourced from across the state of New South Wales was performed using the Diversity Arrays Technology platform (DArTseq™) with funding provided by the NSW Government under the New South Wales Koala Strategy (Grant Agreement No. KR_2019_01). 
Our findings demonstrate that current management divisions across the state of NSW do not fully represent the distribution of genetic diversity among extant koala populations, and that care must be taken to ensure that translocation paradigms based on these frameworks do not inadvertently restrict gene flow between populations and regions that were historically interconnected. We also recommend that koala populations should be prioritised for conservation action based on the scale and severity of the threatening processes that they are currently faced with, rather than placing too much emphasis on their perceived value (e.g., as reservoirs of potentially adaptive alleles), as our data indicate that existing genetic variation in koalas is primarily partitioned amongst individual animals. As such, the extirpation of koalas from any part of their range represents a potentially critical reduction of genetic diversity for this iconic Australian species.

Tags: Phylogeography, conservation genomics, threatened species management, wildlife monitoring
Organization: Australian Museum
The 2012 floor space and employment survey employment zone data

This dataset contains employment, internal floor area and businesses by employment zone collected in the 2012 floor space and employment survey.    The 2012 survey was the second full survey within the current City of Sydney local area boundaries. The previous survey were undertaken in 2007. View this dataset in our employment in the city app.  For more information about the floor space and employment survey, visit the City of Sydney website.

Tags: 2012, FES, Land Use Planning, businesses, economy and business, employment, employment zone, environmental, floor space and employment survey, internal floor area
Organization: City of Sydney
Employment in the City

The 2022 floor space and employment survey was the fourth full survey within the current City of Sydney local area boundaries. Previous surveys were undertaken in 2007, 2012 and 2017.   For more information about the floor space and employment survey, visit the City of Sydney website.

Tags: Blocks, Employment, FES, FES2007, FES2012, FES2017, FES2022, Land Use Planning, city council, economy and business
Organization: City of Sydney
Parks

Our parks and open spaces provide for the diverse recreational needs of our communities. There are over 400 parks of various sizes, from pocket parks to extensive regional parklands.   This dataset contains the location of parks in the City of Sydney including park name, type and playground feature.   For more information on parks, visit the City of Sydney website.

Tags: asset amenity, community, culture leisure sport, environmental, fitness, gardens, outdoor, parks, recreation, services facilities, walking
Organization: City of Sydney
River Condition Index

Access APIFor Data Download pls contact DPIEMetadata Portal Metadata InformationContent TitleRiver Condition IndexContent TypeHosted Feature LayerDescriptionRiver Condition IndexInitial Publication Date28/08/2024Data Currency28/08/2024Data Update FrequencyAPIContent SourceAPIFile TypeWeb Feature ServiceAttributionData Theme, Classification or Relationship to other DatasetsAccuracySpatial Reference System (dataset)GDA94Spatial Reference System (web service)OtherWGS84 Equivalent ToGDA94Spatial ExtentContent LineageData ClassificationUnclassifiedData Access PolicyOpenData QualityTerms and ConditionsCreative CommonStandard and SpecificationData CustodianNSW Department of Climate Change Energy, Environment and WaterPoint of ContactNSW Department of Climate Change Energy, Environment and WaterData AggregatorData DistributorAdditional Supporting InformationTRIM Number

Tags: Water
Organization: Spatial Services (DCS)