Chart and table of population level and growth rate for the Perth, Australia metro area from 1950 to 2025.

Population: Resident: Estimated: Annual: Western Australia: Greater Perth data was reported at 2,039,041.000 Person in 2017. This records an increase from the previous number of 2,019,263.000 Person for 2016. Population: Resident: Estimated: Annual: Western Australia: Greater Perth data is updated yearly, averaging 1,863,214.500 Person from Jun 2006 (Median) to 2017, with 12 observations. The data reached an all-time high of 2,039,041.000 Person in 2017 and a record low of 1,576,912.000 Person in 2006. Population: Resident: Estimated: Annual: Western Australia: Greater Perth data remains active status in CEIC and is reported by Australian Bureau of Statistics. The data is categorized under Global Database’s Australia – Table AU.G002: Estimated Resident Population.

As of June 2023, in the state of Western Australia in Australia, about 7.7 percent of the population was between 35 and 39 years old. In comparison, just 1.9 percent of the population was over the age of 85.

澳大利亚 Population: Resident: Estimated: Annual: Western Australia: Greater Perth在2017达2,039,041.000 人口，相较于2016的2,019,263.000 人口有所增长。澳大利亚 Population: Resident: Estimated: Annual: Western Australia: Greater Perth数据按每年更新，2006至2017期间平均值为1,863,214.500 人口，共12份观测结果。该数据的历史最高值出现于2017，达2,039,041.000 人口，而历史最低值则出现于2006，为1,576,912.000 人口。CEIC提供的澳大利亚 Population: Resident: Estimated: Annual: Western Australia: Greater Perth数据处于定期更新的状态，数据来源于Australian Bureau of Statistics，数据归类于Global Database的澳大利亚 – Table AU.G002: Estimated Resident Population。

As of October 2024, approximately 7,600 Japanese residents were registered in Perth. In the same year, Australia was one of the countries with the highest number of Japanese residents worldwide.

Original provider: Dr Belinda Cannell, Murdoch University

Dataset credits: Data provider Murdoch University - Biological Sciences and Biotechnology Originating data center Satellite Tracking and Analysis Tool (STAT) Project partner Murdoch University
University of NSW Project sponsor or sponsor description This project has been funded under the Australian Research Council Linkage Project Scheme. Funds have also been contributed by Department of Environment and Conservation,
Fremantle Ports, Department of Defence, Tiwest and the Winifred Violet Scott Trust fund.

Abstract: Little Penguins from Penguin and Garden islands in Perth, Western Australia, are tracked to determine the areas in which they travel and feed throughout the breeding season. Once the areas they regularly use are determined, the threats the penguins are exposed to, and their likelihood of occurrence, can be elucidated. This forms part of a broader project to determine the population viability analysis of the Little Penguins in the Perth metropolitan region.

With 109.9 men per one hundred women in the city, the greater Darwin area in Australia has the highest sex ratio. This is in stark contrast to the demographics of the other major cities in Australia which have more women than men. This is consistent with the fact that more than two thirds of all women between 25 and 64 participating in the workforce.Despite this fact, there is still some disparity between men and women in high level position as women are multiple times more likely to be sexually assaulted while men are much more likely to be victims of murder.The perpetrators of crimes are also much more likely to be men as there are

The workforce dataset contains monthly workforce sizes from July 2005 to June 2018 in the eight Australian capital cities with estimated stratification by indoor and outdoor workers. It is included in both csv and rda format. It includes variables for:

Year Month GCCSA (Greater Capital City Statistical Area, which is used to define capital cities) Date (using the first day of the month) fulltime: Fulltime workers parttime: Parttime workers n. Overall workers outorin. Estimated indoor or outdoor status

This data are derived from the Australian Bureau of Statistics (ABS) Labour Force, Australia, Detailed, LM1 dataset: LM1 - Labour force status by age, greater capital city and rest of state (ASGS), marital status and sex, February 1978 onwards (pivot table). Occupational data from the 2006, 2011 and 2016 Census of Population and Housing (ABS Census TableBuilder Basic data) were used to stratify this dataset into indoor and outdoor classifications as per the "Indooroutdoor classification.xlsx" file. For the Census data, GCCSA for the place of work was used, not the place of usual residence.

Occupations were defined by the Australian and New Zealand Standard Classification of Occupations (ANZSCO). Each 6-digit ANZSCO occupation (the lowest level classification) was manually cross-matched with their corresponding occupation(s) from the Canadian National Occupation System (NOC). ANZSCO and NOC share a similar structure, because they are both derived from the International Standard Classification of Occupations. NOC occupations listed with an “L3 location” (include main duties with outdoor work for at least part of the working day) were classified as outdoors, including occupations with multiple locations. Occupations without a listing of "L3 location" were classified as indoors (no outdoor work). 6-digit ANZSCO occupations were then aggregated to 4-digit unit groups to match the ABS Census TableBuilder Basic data. These data were further aggregated into indoor and outdoor workers. The 4-digit ANZSCO unit groups’ indoor and outdoor classifications are listed in "Indooroutdoor classification.xlsx."

ANZSCO occupations associated with both indoor and outdoor listings were classified based on the more common listing, with indoors being selected in the event of a tie. The cross-matching of ANZSCO and NOC occupation was checked against two previous cross-matches used in published Australian studies utilising older ANZSCO and NOC versions. One of these cross-matches, the original cross-match, was validated with a strong correlation between ANZSCO and NOC for outdoor work (Smith, Peter M. Comparing Imputed Occupational Exposure Classifications With Self-reported Occupational Hazards Among Australian Workers. 2013).

To stratify the ABS Labour Force detailed data by indoors or outdoors, workers from the ABS Census 2006, 2011 and 2016 data were first classified as indoors or outdoors. To extend the indoor and outdoor classification proportions from 2005 to 2018, the population counts were (1) stratified by workplace GCCSA (standardised to the 2016 metrics), (2) logit-transformed and then interpolated using cubic splines and extrapolated linearly for each month, and (3) back-transformed to the normal population scale. For the 2006 Census, workplace location was reported by Statistical Local Area and then converted to GCCSA. This interpolation method was also used to estimate the 1-monthly worker count for Darwin relative to the rest of Northern Territory (ABS worker 1-monthly counts are reported only for Northern Territory collectively).

ABS data are owned by the Commonwealth Government under a CC BY 4.0 license. The attached datasets are derived and aggregated from ABS data.

Text file (GenAlEx format) containing allele scoring for 28 microsatellite loci for 78 individual dolphins sampled in the metropolitan waters of Perth, Western Australia.Format of the dataset with detailed information:- 1st column: sample ID- 2nd column: (Pop) community allocated to the sample (based on socio-spatial structure, GR- Gage Roads; SCR - Swan Canning Riverpark; OA - Owen Anchorage; and CS - Cockburn Sound, Chabanne et al. 2017)- 3rd and 4th columns: sample location - longitude and latitude in decimal degree- 5th column: allocated haplotype (Genbank Accession numbers: Hap1- MW221830; Hap2 - MW221831; Hap3 - MW221832; Hap4 - MW221833; and Hap5 - MW221834)- 6th to end: alleles scoring, two columns per locus, missing allele is scored as '0'.

Effective population size (Ne) of seven populations of Notechis scutatus occidentalis around Perth, Western Australia.

This report is a major risk assessment project based on metropolitan Perth, the capital city of Western Australia. Completed in June 2005, the report is the final publication in Geoscience Australia's Cities Project. Approximately 72% of Western Australia's population of around 1.3 million live in the Perth metropolitan area. Significant areas of Perth are situated along the banks of the flood prone Swan River and close to Australia's most active earthquake zone. There are several limestone belts to the north and south of Perth where karst systems have been discovered and the city's coastline suffers from coastal erosion as a result of high winds and fierce storms.

The study aimed at estimating the impact on the Perth community of several sudden-onset natural hazards. The natural hazards considered are both meteorological and terrestrial in origin. The hazards investigated most comprehensively are riverine floods in the Swan and Canning Rivers, severe winds in metropolitan Perth, and earthquakes in the Perth region. Some socioeconomic factors affecting the capacity of the citizens of Perth to recover from natural disaster events have been analysed and the WA data compared with data from other Australian states. Additionally, new estimates of earthquake hazard have been made in a zone of radius around 200km from Perth, extending east into the central Wheatbelt. The susceptibility of the southwest WA coastline to sea level rise from climate change has also been investigated. A commentary on the tsunami risk to WA coastline communities is also included.

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This dataset is the June 2022 release of Geoscape Planning for a single SA2 area (Perth City) with SA2 code (51041). Buildings is a spatial dataset which represents Australia's built environment derived from remotely sensed imagery and aggregated data sources. The Buildings dataset has relationships with the G-NAF, Cadastre, Property and Administrative Boundaries products produced by Geoscape Australia. Users should note that these related Geoscape products are not part of Buildings. For more information regarding Geoscape Buildings, please refer to the Data Product Description and the June 2022 Release Notes. Please note: As per the licence for this data, the coverage area accessed by you can not be greater than a single Level 2 Statistical Area (SA2) as defined by the Australian Bureau of Statistics. If you require additional data beyond a single SA2 for your research, please request a quote from AURIN. Buildings is a digital dataset representing buildings across Australia. Data quality and potential capture timelines will vary across Australia based on two categories, each category has been developed based on a number of factors including the probability of the occurrence of natural events (e.g. flooding), population distribution and industrial/commercial activities. Areas with a population greater than 200, or with significant industrial/commercial activity in a visual assessment have been defined as 'Urban' and all other regions have been defined as 'Rural'. This dataset has been restricted to the Perth City SA2 by AURIN.

Sea noise collected over 2003 to 2017 from the Perth Canyon, Western Australia was analysed for variation in the South Eastern Indian Ocean pygmy blue whale song structure. The primary song-types were: P3, a three unit phrase (I, II and III) repeated with an inter-song interval (ISI) of 170–194 s; P2, a phrase consisting of only units II & III repeated every 84–96 s; and P1 with a phrase consisting of only unit II repeated every 45–49 s. The different ISI values were approximate multiples of each other within a season. When comparing data from each season, across seasons, the ISI value for each song increased significantly through time (all fits had p < 0.001), at 0.30 s/Year (95%CI 0.217–0.383), 0.8 s/Year (95%CI 0.655–1.025) and 1.73 s/Year (95%CI 1.264–2.196) for the

The Australian Marine Microbial Biodiversity Initiative (AMMBI) provides methodologically standardized, continental scale, temporal phylogenetic amplicon sequencing data describing Bacteria, Archaea and microbial Eukarya assemblages. Sequence data is linked to extensive physical, biological and chemical oceanographic contextual information. Samples are collected monthly to seasonally from multiple depths at seven National Reference Stations (NRS) sites: Darwin Harbour (Northern Territory), Yongala (Queensland), North Stradbroke Island (Queensland), Port Hacking (New South Wales), Maria Island (Tasmania), Kangaroo Island (South Australia), Rottnest Island (Western Australia). The Integrated Marine Observing System (IMOS) NRS network is described at http://imos.org.au/facilities/nationalmooringnetwork/nrs/ Rottnest Island NRS is located 18 nm offshore and 2.5 nm from Rottnest Island, at a depth of 50 m over sand but surrounded by low relief limestone reef which is predominately covered with macro-algae, mainly Ecklonia spp, on the Western Australia coast, near Perth (population 1.83 million). This is the only NRS situated on the Indian Ocean coastline. This station is heavily impacted by the Leuwin Current (LC), which delivers warm but less saline waters southward. The LC is strongly affected by ENSO and IOD events. The prevailing winds and current direction leads to coastal suppression of upwelling along the Western Australian coast throughout most of the year, and consequently sea surface temperatures of up to 4–5?°C warmer than upwelling systems at similar latitudes elsewhere on the globe2. There is an historical oceanographic dataset from this site (with intermittent gaps in certain parameters) dating back to 1951.

Site details from Brown, M. V. et al. Continental scale monitoring of marine microbiota by the Australian Marine Microbial Biodiversity Initiative. Sci. Data 5:180130 doi: 10.1038/sdata.2018.130 (2018). Site location: Rottnest Island National Reference Station (NRS), Western Australia, Australia Note on data download/processing: Data downloaded from Australian Microbiome Initiative via Bioplatforms Australia Data Portal on 17 June 2022. The search filter applied to download data from Bioplatforms Australia Data portal are stored in the Darwin Core property (identificationRemarks). Taxonomy is assigned according to the taxonomic database (SILVA 138) and method (Sklearn) which is stored in the Darwin Core Extension DNA derived data property (otu_db). Prefix were removed from the taxonomic names as shown in the example (e.g. d_Bacteria to Bacteria). Scientific name is assigned to the valid name available from the highest taxonomic rank. This collection is published as Darwin Core Occurrence, so the event level measurements need to be replicated for every occurrence. Instead of data replication, the event level eMoF data are made available separately at https://www.marine.csiro.au/data/services/obisau/emof_export.cfm?ipt_resource=bioplatforms_mm_nrs_rot

The data were collected to test hypotheses that microplastic concentrations in stormwater drains would be able to be predicted from: (1) the proportions of different land uses in stormwater catchments; (2) catchment population and land area; (3) rainfall preceding sample collection. The data show that microplastic fibres were the most common morphology across all drains, followed by fragments. Most microplastics detected were in the 100-530 µm size range, with lower proportions ≤ 25 µm or > 530 µm. The most common colour was black, followed by red, blue, and green with other colours < 5% of total particle counts. There was no statistically significant variation in microplastic concentrations between or within stormwater catchments. Linear mixed-effects models showed significant positive effects of catchment area, catchment population, and the proportion of industrial land, natural land and public open space on microplastic concentrations. The proportion of residential land had a significant negative effect on microplastic concentrations. The proportion of agricultural land in each catchment, and preceding rainfall, had no effect on microplastic concentrations. The majority of data are presented as a single comma-separated value file with 144 rows representing 3 replicates of 4 size fractions from 12 sampling sites. Samples have unique names and are categorised by Size (4 categories), Drain (6 categories) and Site (12 categories, 2 per Drain). Quantitative data relating to microplastics measurement include: sample volume; raw counts of total microplastics and microplastics separated into fragment, fibre, film, and microbead categories; concentrations of total microplastics and microplastics separated into fragment, fibre, film, and microbead categories; blank corrections (fibres only); corrected raw counts and concentrations of fibres; corrected raw counts and concentrations of total microplastics. Catchment demographic and land use data are: catchment area and population; proportions of land use in residential, industrial, services, agricultural, natural, and public open space categories. Rainfall for the 7 days prior to sample collection is also recorded. A separate comma-separated value file summarises the microplastic colour data, and an image shows aerial photograph maps of each site.

ISI-spacing for the P1, P2 and P3 songs each year (ISI-curve analysis).

Proportions of P1, P2 and P3 song-types given by ISI-curve analysis.