Historical dataset of population level and growth rate for the Brisbane, Australia metro area from 1950 to 2025.

This dataset is available on Brisbane City Council’s open data website – data.brisbane.qld.gov.au. The site provides additional features for viewing and interacting with the data and for downloading the data in various formats.

The Brisbane Community Profiles provide detailed statistical information for Greater Brisbane and Brisbane City using information from the Australian Bureau of Statistics, Commonwealth and Queensland Government sources.

Profiles are generated using the latest demographic, social and economic data to gather information about the people who live in an area (Resident Profile) the workers and businesses that operate in the area (Workforce Profile) or how the area has changed over time (Time Series Profile).

The Data and resources section of this dataset contains further information for this dataset.

To select and view data use the link in the Data and resources section below.

This dataset is available on Brisbane City Council’s open data website – data.brisbane.qld.gov.au. The site provides additional features for viewing and interacting with the data and for downloading the data in various formats. The Brisbane Community Profiles provide detailed statistical information for Greater Brisbane and Brisbane City using information from the Australian Bureau of Statistics, Commonwealth and Queensland Government sources. Profiles are generated using the latest demographic, social and economic data to gather information about the people who live in an area (Resident Profile) the workers and businesses that operate in the area (Workforce Profile) or how the area has changed over time (Time Series Profile). The Data and resources section of this dataset contains further information for this dataset. To select and view data use the link in the Data and resources section below.

Yearly registered births – breakdown by Month

An fMRI Dataset for Appetite Neural Correlates in People Living with Motor Neuron Disease

This is a motor neuron disease (MND) imaging dataset generated by the Steyn/Ngo Lab at the University of Queensland, Australia. Imaging was conducted at the Herston Imaging Research Facility (HIRF) at Brisbane, Australia.

The raw BIDS data was created using BIDScoin 2.3.1 All provenance information and settings can be found in ./code/bidscoin For more information see: https://github.com/Donders-Institute/bidscoin

Anatomical volumes were refaced using mri_reface 0.3.3 The code can be found in ./code/reface_structural.sh

Identifiable volumes under the derivatives dataset derivatives/fmriprep-v23.1.4 were removed.

Protocol change for sub-43

For this patient we used the 20 channel coil instead of the 64 channel coil as the 64 channel coil did not fit the patients head. Due to the coil change there were a few modifications to the imaging protocol as listed below: PA multiband diffusion block changes: TE changed from 84 ms to 89 ms TR changed from 4700 ms to 5200ms Multiband diffusion AP block 1 changes: TE changed from 84 ms to 89 ms TR changed from 4700 ms to 5200ms AP multiband diffusion block 2 changes: TE changed from 84ms to 89 ms TR changed from 4700 ms to 5200 ms

DWI not available for sub-17

DWI files for sub-17 are incomplete. As such, sub-17/ses-02/dwi is not included as part of the published dataset.

Lists businesses and other locations and whether they are accessible to people with disabilities.

Dataset includes: location, suburb, region, category, sub category, rating and rating description.

This online survey was undertaken between September to November 2021 targeting people living in the Brisbane urban area. QUT Research Data Respository Dataset Resource available for download

This dataset, created in June 2013, provides an indication of areas subject to overland flow flooding inside the Brisbane City Council local government area. The overall overland flow layer consists of the 1% Annual Exceedance Probability (AEP) (100 year Average Recurrence Interval (ARI)) flood extent sourced from the Citywide Creek and Overland Flow Path mapping study (GHD, 2017).High impact area:In high impact areas, overland flow is almost certain to occur during a single lifetime (70 years). An event of this size or larger has a 5% chance of occurring in any year. The overland flow is generally unsafe for people, vehicles and buildings.Medium impact area:For the majority of medium impact areas, overland flow is very likely to occur during a single lifetime (70 years). An event of this size or larger has a 2% chance of occurring in any year. The overland flow is generally unsafe for people, vehicles and buildings, however these hazards are experienced less frequently than in high impact areas.Low impact area:For the majority of low impact areas, overland flow is likely to occur during a single lifetime (70 years). An event of this size or larger has a 1% chance of occurring in any year. The overland flow is generally safe for people, vehicles and buildings; however, certain areas can experience greater hazards.link in the Data and resources section on this page.

Due to a system issue, this data is not displayed here. To access the data, please use the ArcGIS Hub Datasets link in the Data and resources section on this page.

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.

This dataset is available on Brisbane City Council’s open data website – data.brisbane.qld.gov.au. The site provides additional features for viewing and interacting with the data and for downloading the data in various formats. This dataset contains information about Brisbane City Council's Free Native Plants Program. Council offers free native plants to: Residential properties, including houses, units and townhouses. Owners, tenants, and public housing and Defence Housing residents can apply. Lessees on Council leased land and official citizenship ceremonies within the Brisbane Local Government area to plant on their properties. Brisbane City Council offers a variety of native plant species for residential properties and entities that are suitable for all garden types and sizes. The native species provided through the program are designed to help grow our city's urban forest and support local wildlife. Further information is available on the Brisbane City Council website. The Data and resources section of this dataset contains further information for this dataset.

Official and Alternative Addresses within the Brisbane City Council Local Government Area.

Contains property information including: Address, Ward, Property Description and Coordinates.

The Data and resources section of this dataset contains further information for this dataset.

This dataset is available on Brisbane City Council’s open data website – data.brisbane.qld.gov.au. The site provides additional features for viewing and interacting with the data and for downloading the data in various formats. This dataset, created in June 2013, provides an indication of the likelihood of a flood occurring from one or more sources: creek, river, and storm tide inside the Brisbane City Council local government area. This layer contributes to the overall Flood Awareness Mapping for Brisbane City Council. Brisbane City Council has developed the Flood Awareness Maps and adopted the terms ‘high’, ‘medium’, ‘low’ and ‘very low’ likelihood areas to help residents and businesses better understand the likelihood of a flood affecting their property. The Flood Awareness Maps are an awareness tool and the maps do not provide information about the depth or speed of flood water. Information on potential flood levels for a property can be found in the FloodWise Property Report online. The Flood Awareness Maps are an awareness tool to provide an indication of the likelihood of a flood occurring from one or more sources: creek, river, overland flow and storm tide. The maps do not provide information about the depth or speed of flood water. Use the FloodWise Property Report for information about flood levels specific to your property. Many properties within the high and medium flood likelihood were affected by flooding in the 1974 and 2011 Brisbane River floods. Residents in the low and very low flood likelihood areas should still be aware of their risk of flooding and understand how they, as well as others in the area, may be affected. High likelihood area Flooding is almost certain to occur in a high likelihood area. Residents and businesses are strongly advised to learn about the flood likelihood for their property so they can be prepared to help minimise the impact on their home, business and family. Medium likelihood area Flooding is likely to occur in a medium likelihood area. Residents and businesses are advised to learn about the flood likelihood for their property so they can be prepared to help minimise the impact on their home, business and family. Low likelihood area Low flood likelihood areas may experience flooding in a rare flood event. Residents and businesses should consider how flooding may affect their local area, suburb or community. Flooding is unlikely in a low flood likelihood area but it may still occur. Very low likelihood area Very low likelihood areas are unlikely to flood except in a very rare or extreme flood event. Residents and businesses should consider how flooding may affect their local suburb, area or community. Flooding is very unlikely in a very low flood likelihood area, but may still occur. Brisbane City Council is working hard to reduce the impact of flooding but we all have a responsibility to understand our flood risk and be better prepared to minimise the impact of flooding on our homes, property and businesses. For further information please refer to Council's website.

This dataset provides advice and restrictions on the methods available to dispose of common waste items by Brisbane City Council residents.

Descriptions for the disposal options listed below are available in the Attachments and Dataset schema sections of this dataset.

Disposal options:

Council Drop Off Points/Public Drop Off Points

Household Hazardous Waste

Kerbside Green Waste

Kerbside Large Item Collection

Kerbside Recycle

Kerbside Waste

Must follow proper procedure

Other

Public Drop Off Points

Resource Recovery Centre

The Attachments and Dataset schema sections of this dataset contain further information for this dataset.

This dataset is available on Brisbane City Council’s open data website – data.brisbane.qld.gov.au. The site provides additional features for viewing and interacting with the data and for downloading the data in various formats.

This dataset, created in June 2013, provides an indication of areas subject to overland flow flooding inside the Brisbane City Council local government area.

The overall overland flow layer consists of the 1% Annual Exceedance Probability (AEP) (100 year Average Recurrence Interval (ARI)) flood extent sourced from the Citywide Creek and Overland Flow Path mapping study (GHD, 2017\).

High impact area:

In high impact areas, overland flow is almost certain to occur during a single lifetime (70 years). An event of this size or larger has a 5% chance of occurring in any year. The overland flow is generally unsafe for people, vehicles and buildings.

Medium impact area:

For the majority of medium impact areas, overland flow is very likely to occur during a single lifetime (70 years). An event of this size or larger has a 2% chance of occurring in any year. The overland flow is generally unsafe for people, vehicles and buildings, however these hazards are experienced less frequently than in high impact areas.

Low impact area:

For the majority of low impact areas, overland flow is likely to occur during a single lifetime (70 years). An event of this size or larger has a 1% chance of occurring in any year. The overland flow is generally safe for people, vehicles and buildings; however, certain areas can experience greater hazards.

link in the Data and resources section on this page.

Due to a system issue, this data is not displayed here. To access the data, please use the ArcGIS Hub Datasets link in the Data and resources section on this page.

Births that occurred by hospital name. Birth events of 5 or more per hospital location are displayed

Real time data of traffic volume and occupancy of lanes at Brisbane City Council signalised intersections and approaches.

Not all signalised traffic intersections within Brisbane are operated by Brisbane City Council. This dataset contains only the Brisbane City Council operated signalised traffic intersection data.

To gain maximum benefit from this dataset you will have to use it in conjunction with another dataset Traffic Management — Intersection locations — reference.

The Data and resources section of this dataset contains further information for this dataset.

This dataset is available on Brisbane City Council’s open data website – data.brisbane.qld.gov.au. The site provides additional features for viewing and interacting with the data and for downloading the data in various formats.

Brisbane City Council has partnered with a number of community gardens around Brisbane to help residents turn food scraps into nutrients for soil.Food waste is a big part of avoidable waste that goes into Brisbane’s general household bins. Composting helps to reduce the amount of food waste we send to landfill, while also reducing the harmful greenhouse gases that are released. It’s also an easy way to experience where our food comes from and shows how valuable our food scraps can be in the cultivation and harvesting cycle.Brisbane’s Community composting hub program encourages residents living near a hub to regularly contribute their food scraps. With support from Council and community volunteer caretakers, residents can learn about the benefits of composting and other ways to reduce the amount of food waste they create.More information on compost and food waste recycling can be found on the Brisbane City Council website.

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/ North Stradbroke Island NRS is located 6.6 nm north east of North Stradbroke Island at a depth of 60 m over sandy substrate. It is 30 km southeast of the major city of Brisbane, Queensland (population 2.099 million), at the opening to large, shallow, Moreton Bay. The site is impacted by the southerly flowing EAC and its eddies, which may cause periodic nutrient enrichment through upwelling. This latitude is the biogeographic boundary for many tropical and subtropical species. The water column is well mixed between May-August and stratified for the remainder of the year and salinity may at times be affected by floodwaters from the nearby Brisbane River outflow.

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: North Stradbroke Island National Reference Station (NRS), Queensland, 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_nsi Please see https://www.australianmicrobiome.com/protocols/acknowledgements/ for citation examples and links to the data policy.

This dataset contains information on Brisbane City Council's Talk to a Planner sessions. These sessions help residents, business owners and community groups learn more about Brisbane City Plan 2014 (City Plan) and how it relates to their building and construction plans. It includes locations, dates and times.

Brisbane City Council's events data containing dates, costs, booking requirements, venue and location for Council's Talk to a Planner sessions.

The dataset was created using data from an external service called Trumba. The data is a transformed extract created using the Trumba Calendar API XML feed, that is limited to the next 1,000 events. The transformed extract is converted to a CSV file and uploaded into this dataset daily.

To access and view the data using the Source API (Trumba), use the information below and your preferred link in the Data and Resources section. The Source API is available for this dataset in:

Trumba Calendar - API - XML feed is limited to the next 1,000 events

The Data and resources section of this dataset contains further information for this dataset.

Natural selection for territoriality is theorized to occur under conditions favouring intra-sexual phenotypic variation in physiology, morphology and behaviour. In this context, certain suites of behavioural traits associated with territoriality are expected to consistently covary among individuals (sometimes referred to as ‘behavioural syndromes’) within sexes. Agonism (conflict-associated behaviours that may or may not be associated with physical aggression) and movement – for example, ranging, or relocation within or across seasons - are two behavioural components that are associated with territoriality, and may be expected to covary in this context. Territorial males are expected to employ agonistic behaviours to actively establish and defend areas and resources, and show more stability in their location across the landscape. However, the interaction between agonism and movement especially for wild reptiles, has rarely been tested. We investigated whether agonistic and movement behaviour correlate at the individual level both within one year and across multiple years, in a wild population of Australian eastern water dragons, Intellagama lesueurii. Although both types of behaviours exhibited among-individual repeatability over year and multi-year scales, we found no evidence of an agonistic-movement behavioural syndrome. These findings indicate that agonistic and movement behaviours are likely independent traits, and thus territoriality may not drive shared selective pressures for both. It is possible that other social behaviours and strategies are in place to maintain structure in this wild population. Methods Behavioural survey data (Agonism) We utilised data taken as part of a longitudinal study (2010-2020) conducted at Roma Street Parklands, Brisbane, Australia (-27.462315, 153.019052). Between August – May each year, behavioural surveys were recorded three days per week, twice each day (07:30 – 10:30 and 13:00 – 16:00), with the survey route capturing approximately 85% of the water dragon population (Strickland et al. 2014). For every individual encountered, a profile photograph was taken using a Canon EOS 600 digital camera, their GPS coordinates recorded using a GARMIN eTREX10 handheld device, and any agonistic behaviour being exhibited was recorded. Water dragons perform a number of discrete visual and physical behaviours that are considered agonistic or aggressive towards conspecifics. We noted whether, during the survey, the focal individual demonstrated any of the following: head bob, arm wave, tail slap, chasing or fighting. We did not include fighting data for our subsequent analyses, since directionality could not be inferred (i.e. if another individual had begun a fight and the focal individual was acting in defence, rather than demonstrating agonistic behaviour). All other behaviours were pooled, such that an encounter would have recorded an agonistic behaviour, or not (i.e. a binary response variable). Individual ID of each dragon was determined subsequently, thus these observations were done blind to ID. Individual sex was determined based on known sexual dimorphic characteristics: males present a red ventral colouration which the females lack, and are larger in size than females (Cuervo and Shine 2007). Individuals could then be identified via their photographs in the I3S Manta software using the unique scale patterning around their ear (Gardiner et al. 2014). In addition, once or twice each year a morphological catch took place where we measured individual snout-to-vent length (SVL) from the tip of the snout to the posterior edge of the anal scale, as a measure of body size (Littleford-Colquhoun et al. 2017). All work was done with the approval of the University of the Sunshine Coast Animal Ethics Committee. Over the 10-year period we collected 68,452 observations of water dragons with 1,414 unique individuals identified. The data used for these analyses only included adult males that had body size measurements, and therefore consisted of 17,207 observations made for 303 individuals. Distance measurements (Movement) We converted GPS points of each individual sighting into x-y coordinates using the adehabitatHR package (Calenge 2006) in the R statistical environment (Team 2010). We then calculated two types of distance measures: successive and displacement. Successive distance was defined as the number of meters between each successive sighting (with time between each) for an individual, and gives an idea of relative location of a territory, and whether the territory centroid shifted directionally over time. Displacement was the number of meters between an individual’s first adult sighting and each subsequent sighting (Fig. 1). Successive distance tends to reveal more about an individual’s daily activity or patrolling (i.e. tendency to always be found in the same place) whereas displacement reflects territory shifts (or the lack of territory) within a season – something that may occur to submissive, younger or transient males. Both traits, however, may be positively correlated with territory size. In order to determine individual site fidelity between seasons, we calculated the centroid of each home range using the kernel utilisation distribution for each adult male (minimum 20 sightings) at the 95% home range class (Strickland et al. 2017). Following methods from Gardiner et al (2014), we applied a smoothing parameter of seven meters optimised for this species. We then took the centroid coordinates from the projected polygons for each individual per year and measured the distance the centroid had moved between years. This would reveal whether individuals remained in the same area across years or whether they moved their home range site. Site fidelity was then log-transformed, while other movement behaviours were scaled (mean=0; sd=1) in order to improve model convergence.