The Historical Bushfire Boundaries service represents the aggregation of jurisdictional supplied burnt areas polygons stemming from the early 1900's through to 2022 (excluding the Northern Territory). The burnt area data represents curated jurisdictional owned polygons of both bushfires and prescribed (planned) burns. To ensure the dataset adhered to the nationally approved and agreed data dictionary for fire history Geoscience Australia had to modify some of the attributes presented. The information provided within this service is reflective only of data supplied by participating authoritative agencies and may or may not represent all fire history within a state.

<div>The A1 poster incorporates 4 images of Australia taken from space by Earth observing satellites. The accompanying text briefly introduces sensors and the bands within the electromagnetic spectrum. The images include examples of both true and false colour and the diverse range of applications of satellite images such as tracking visible changes to the Earth’s surface like crop growth, bushfires, coastal changes and floods. Scientists, land and emergency managers use satellite images to analyse vegetation, surface water or human activities as well as evaluate natural&nbsp;hazards.</div>

The Historical Bushfire Boundaries service represents the aggregation of jurisdictional supplied burnt areas polygons stemming from the early 1900's through to 2022 (excluding the Northern Territory). The burnt area data represents curated jurisdictional owned polygons of both bushfires and prescribed (planned) burns. To ensure the dataset adhered to the nationally approved and agreed data dictionary for fire history Geoscience Australia had to modify some of the attributes presented. The information provided within this service is reflective only of data supplied by participating authoritative agencies and may or may not represent all fire history within a state.

This dataset presents a three hourly accumulation of bushfire boundaries throughout the 2021/22 bushfire season (1/9/2021 - 30/4/22) for all Australian jurisdictions who have the technical ability and/or appropriate licence conditions to provide this information. The accuracy and completeness of the data attributes within this webservice is reliant on each jurisdictional source and the information they elect to publish into their historical bushfire boundary data products. The update frequency of the underlying data varies across the jurisdictions and therefore data may not be present in some areas. No filtering has been performed where source data overlaps.

This atlas-style report presents a spatial demographic analysis for Victoria including measures of population vulnerability. It updates the 2016 report which relied on data from the ABS 2011 census of population and housing. This version uses information from the 2016 census along with other updated population data. Key findings include: • Fire is a natural part of the Australian landscape but its incidence and impact can be increased by the presence of people. • Measures of vulnerability are indicative. They do not predict how a particular individual will respond to a specific event. Nevertheless, research studies have shown that some characteristics are associated with an individual’s level of vulnerability before, during, or after a disaster. • Population vulnerabilities have a geographical distribution. Some communities will have a greater measure of vulnerability than others, and some locations may display multiple types of vulnerability. • The vulnerability level of a household will be determined by its weakest rather than its strongest member. KEY FINDINGS • Population characteristics change over time. Hence patterns of vulnerability can also change over time. Sometimes changing characteristics occur because people move into or out of a community. Other changes occur within a population. Children may be born, increasing the number of infants in a community, or people may age in place, causing an increse in numbers of older people. • In Melbourne’s fringe and peri-urban areas, this pattern of ageing in place is likely to cause a significant increase in numbers of older people. • Most population measures are based on where people usually live or work, yet people can be highly mobile. • People may have more than one residence. This can include: holiday homes; weekenders; or for regional populations, a townhouse in the city. • Population mobility presents particular challenges for risk assessment and emergency management. Towns may vary in population size by a factor of four or five during particular seasons of the year. • Popular visitor and holiday locations such as the Dandenong Ranges and Great Ocean Road have particularly high fire risk. Planning for fire therefore requires an understanding of both permanent and part-time populations.

<div>This dataset was produced under Stream 1 - Work Package 4 of the 2021-23 Australian Research Data Commons (ARDC) Bushfire Data Challenge Project; a collaborative partnership between the ARDC, Geoscience Australia, and the Emergency Management Spatial Information Network. The Project’s aim was to bring together a single nationally consistent and harmonised historical bushfire boundary data derived from the authoritative state and territory agencies. Geoscience Australia's role within this project was to; negotiate access to the data, collate and transform the data into the National Standard and then deliver the 'Historical Bushfire Boundaries' data through a static file and a webservice.</div><div><br></div><div>More information about the ARDC Project and Work Package 4: <br>https://ardc.edu.au/program/bushfire-data-challenges/</div><div> More information about the Fire History Data Dictionary: <br>https://www.afac.com.au/insight/doctrine/article/current/fire-history-data-dictionary</div><div><br></div><div>The Historical Bushfire Boundaries dataset represents the aggregation of jurisdictional supplied burnt areas polygons stemming from the early 1900's through to 2022 (excluding the Northern Territory). The burnt area data represents curated jurisdictional owned polygons of both bushfires and prescribed (planned) burns. To ensure the dataset adhered to the nationally approved and agreed data dictionary for fire history Geoscience Australia had to modify some of the attributes presented.</div><div><br></div><div>The information provided within this dataset is reflective only of data supplied by participating authoritative agencies and may or may not represent all fire history within a state.</div><div><br></div><div><b>Important:</b> The Northern Australia Fire Information (NAFI) data has been intentionally omitted from this dataset (refer to Lineage).</div>

Modelling of the risk posed by the impacts of extreme weather events requires knowledge of the vulnerability, or performance, of building assets. Furthermore, to assess the benefits of mitigation an ability to quantitatively model the change in vulnerability associated with mitigation actions is required. In Australia past efforts at establishing vulnerability relationships between building damage and severe wind have centred on empirical techniques, using data from damage surveys or insurance losses, and heuristic techniques. Neither of these methods permits the change in vulnerability afforded by mitigation work to be quantitatively modelled. The Bushfire and Natural Hazards CRC project “Improving the Resilience of Existing Housing to Severe Wind Events” is developing a software tool, Vulnerability and Adaption to Wind Simulation (VAWS), to provide a quantitative vulnerability model for Australian house types. It is based on the premise that overall building damage is strongly related to the failure of key connections. The software uses a Monte Carlo approach whereby numerous realisations of a single generic house type are subjected to an increasing gust wind speed and the loss at each wind speed is calculated. Each realisation of the house varies from others as many key building parameters, such as connection strength, are sampled from probability distributions. For each instance, at each wind speed, the number and type of failed connections are related to damage states and extents of damage which permits the repair cost to be calculated. The repair cost is adjusted for the repair of debris impact damage and water ingress damage. The modelling of mitigation is easily accomplished by rerunning a house modelled with the probability distribution of an upgraded connection’s strength substituted. The software tool provides quantitative measures of reduced vulnerability that can be used in assessing the incremental effectiveness of a range of mitigation strategies in economic terms. Abstract submitted to/presented at AMOS-ICSHMO 2018 (https://www.ametsoc.org/index.cfm/ams/meetings-events/ams-meetings/amos-icshmo-2018/)

This report was prepared by Geoscience Australia for the Bushfire CRC. It is intended that this report be used as part of the background material for the reports prepared for the Royal Commission into the Victorian Bushfires 2009. This report contains a demographic analysis of some of the areas directly affected by the bushfires. The areas included in this report (with alternative fire names in brackets) are: Churchill (Churchill - Jeeralang) Bunyip (Bunyip SP - Bunyip Ridge Trk) Bendigo (Mainden Gully/Eaglehawk - Bracewell St) Kilmore (Kilmore East - Murrindindi Complex South) Murrindindi/Yea (Kilmore East - Murrindindi Complex North) Beechworth Horsham Narre Warren

<div>The National Bushfire Historical Extents Dataset (version 3.0) represents the aggregation of jurisdictional supplied burnt areas polygons (except Northern Territory) that date from the late 1800's through to 2024. The burnt areas represent curated jurisdictional owned polygons of both bushfires and prescribed (planned) burns.</div><div><br></div><div>This dataset was produced under Work Stream 1C - Activity 3 of the National Bushfire Intelligence Capability; a collaborative partnership between the Australian Climate Services, CSIRO (NBIC), Geoscience Australia (GA), and the Emergency Management Spatial Information Network (EMSINA). Under agreement this Project (Activity 3) will release a nationally consistent, harmonised and standardised historical bushfire extent dataset derived from the authoritative state and territory agencies. </div><div><br></div><div>The information released within this dataset is reflective of the data supplied by participating authoritative agencies. It may, or may not, represent all fire history within that jurisdiction.</div><div><br></div><div>Apart from small updates to this dataset up until 30 June 2025 there are <strong>no plans</strong> for another major update to this Product. </div>

The Historical Bushfire Boundaries service represents the aggregation of jurisdictional supplied burnt areas polygons stemming from the early 1900's through to 2022 (excluding the Northern Territory). The burnt area data represents curated jurisdictional owned polygons of both bushfires and prescribed (planned) burns. To ensure the dataset adhered to the nationally approved and agreed data dictionary for fire history Geoscience Australia had to modify some of the attributes presented. The information provided within this service is reflective only of data supplied by participating authoritative agencies and may or may not represent all fire history within a state