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Abstract This spatial product shows consistent ‘near real-time’ bushfire and prescribed burn boundaries for all jurisdictions who have the technical ability or appropriate licence conditions to provide this information. Currency Maintenance of the underlying data is the responsibility of the custodian. Geoscience Australia has automated methods of regularly checking for changes in source data. Once detected the dataset and feeds will be updated as soon as possible. NOTE: The update frequency of the underlying data from the jurisdictions varies and, in most cases, does not line up to this product’s update cycle. Date created: November 2023 Modification frequency: Every 15 Minutes Spatial Extent

West Bounding Longitude: 113° South Bounding Latitude: -44° East Bounding Longitude: 154° North Bounding Latitude: -10°

Source Information The project team initially identified a list of potential source data through jurisdictional websites and the Emergency Management LINK catalogue. These were then confirmed by each jurisdiction through the EMSINA National and EMSINA Developers networks. This Webservice contains authoritative data sourced from:

Australian Capital Territory - Emergency Service Agency (ESA) New South Wales - Rural Fire Service (RFS) Queensland - Queensland Fire and Emergency Service (QFES) South Australia - Country Fire Service (CFS)
Tasmania - Tasmania Fire Service (TFS)
Victoria – Department of Environment, Land, Water and Planning (DELWP)
Western Australia – Department of Fire and Emergency Services (DFES)

The completeness of the data within this webservice is reliant on each jurisdictional source and the information they elect to publish into their Operational Bushfire Boundary webservices. Known Limitations:

This dataset does not contain information from the Northern Territory government. This dataset contains a subset of the Queensland bushfire boundary data. The Queensland ‘Operational’ feed that is consumed within this National Database displays a the last six (6) months of incident boundaries. In order to make this dataset best represent a ‘near-real-time’ or current view of operational bushfire boundaries Geoscience Australia has filtered the Queensland data to only incorporate the last two (2) weeks data. Geoscience Australia is aware of duplicate data (features) may appear within this dataset. This duplicate data is commonly represented in the regions around state borders where it is operationally necessary for one jurisdiction to understand cross border situations. Care must be taken when summing the values to obtain a total area burnt. The data within this aggregated National product is a spatial representation of the input data received from the custodian agencies. Therefore, data quality and data completion will vary. If you wish to assess more information about specific jurisdictional data and/or data feature(s) it is strongly recommended that you contact the appropriate custodian.

The accuracy of the data attributes within this webservice is reliant on each jurisdictional source and the information they elect to publish into their Operational Bushfire Boundary webservices. Note: Geoscience Australia has, where possible, attempted to align the data to the (as of October 2023) draft National Current Incident Extent Feeds Data Dictionary. However, this has not been possible in all cases. Work to progress this alignment will be undertaken after the publication of this dataset, once this project enters a maintenance period. Catalog entry: Bushfire Boundaries – Near Real-Time Lineage Statement Version 1 and 2 (2019/20): This dataset was first built by EMSINA, Geoscience Australia, and Esri Australia staff in early January 2020 in response to the Black Summer Bushfires. The product was aimed at providing a nationally consistent dataset of bushfire boundaries. Version 1 was released publicly on 8 January 2020 through Esri AGOL software.
Version 2 of the product was released in mid-February as EMSINA and Geoscience Australia began automating the product. The release of version 2 exhibited a reformatted attributed table to accommodate these new automation scripts. The product was continuously developed by the three entities above until early May 2020 when both the scripts and data were handed over to the National Bushfire Recovery Agency. The EMSINA Group formally ended their technical involvement with this project on June 30, 2020. Version 3 (2020/21): A 2020/21 version of the National Operational Bushfire Boundaries dataset was agreed to by the Australian Government. It continued to extend upon EMSINA’s 2019/20 Version 2 product. This product was owned and managed by the Australian Government Department of Home Affairs, with Geoscience Australia identified as the technical partners responsible for development and delivery. Work on Version 3 began in August 2020 with delivery of this product occurring on 14 September 2020. Version 4 (2021/22): A 2021/22 version of the National Operational Bushfire Boundaries dataset was produced by Geoscience Australia. This product was owned and managed by Geoscience Australia, who provided both development and delivery. Work on Version 4 began in August 2021 with delivery of this product occurring on 1 September 2021. The dataset was discontinued in May 2022 because of insufficient Government funding. Version 5 (2023/25): A 2023/25 version of the National Near-Real-Time Bushfire Boundaries dataset is produced by Geoscience Australia under funding from the National Bushfire Intelligence Capability (NBIC) - CSIRO. NBIC and Geoscience Australia have also partnered with the EMSINA Group to assist with accessing and delivering this dataset. This dataset is the first time where the jurisdictional attributes are aligned to AFAC’s National Bushfire Schema.
Work on Version 5 began in August 2023 and was released in late 2023 under formal access arrangements with the States and Territories. Data Dictionary Geoscience Australia has not included attributes added automatically by spatial software processes in the table below.

Attribute Name Description

fire_id ID attached to fire (e.g. incident ID, Event ID, Burn ID).

fire_name Incident name. If available.

fire_type Binary variable to describe whether a fire was a bushfire or prescribed burn.

ignition_date The date of the ignition of a fire event. Date and time are local time zone from the State where the fire is located and stored as a string.

capt_date The date of the incident boundary was captured or updated. Date and time are local time zone from the Jurisdiction where the fire is located and stored as a string.

capt_method Categorical variable to describe the source of data used for defining the spatial extent of the fire.

area_ha Burnt area in Hectares. Currently calculated field so that all areas calculations are done in the same map projection. Jurisdiction supply area in appropriate projection to match state incident reporting system.

perim_km ) Burnt perimeter in Kilometres. Calculated field so that all areas calculations are done in the same map projection. Jurisdiction preference is that supplied perimeter calculations are used for consistency with jurisdictional reporting.

state State custodian of the data. NOTE: Currently some states use and have in their feeds cross border data

agency Agency that is responsible for the incident

date_retrieved The date and time that Geoscience Australia retrieved this data from the jurisdictions, stored as UTC. Please note when viewed in ArcGIS Online, the date is converted from UTC to your local time.

Contact Geoscience Australia, clientservices@ga.gov.au

Data acquisitionOccurrence data for bee species were downloaded from ALA60 using ALA4R version 1.8.064 in R version 3.6.265.Floral visitation data were obtained from ALA60, Museums Victoria, the Western Australian Museum66,67, and publications (Tables S1 and S2). Floral visitation records were checked for errors and synonymies using the Australian Plant Name Index68. Life-history traits for bee species were sourced, in most cases, from the most recent taxonomic descriptions, or other publications (Tables S1 and S2). A one-hectare resolution Major Vegetation Subgroup (MVS) map was sourced from Geoscience Australia’s National Mapping Division (NMD)61. Fire frequency data from 1988 to 2016 were downloaded from the Department of Environment and Energy (DEE)69, 2019–20 wildfire occurrence data (National Indicative Aggregated Fire Extent Dataset — NIAFED — version 20200623) were sourced from the Department of Agriculture, Water and the Environment (DAWE)36, and 2019–20 wildfire intensity data (Google Earth Engine Burnt Area Map — GEEBAM) were sourced from the Department of Planning, Industry and Environment (DPIE)62. All raster data sources were matched in resolution to the one-hectare MVS map. These GIS data sources may vary in spatial uncertainty or resolution and their caveats can be found at their respective locations online.Data filtering and analysesOccurrence data from ALA were filtered to include only reliable (“preserved specimens”, “machine observations” — e.g., malaise traps, — and data from published datasets) and “present” (compared to “absent”) records. Records without geographic locations or that did not align with base maps were excluded from GIS analyses. Species were then filtered for minimum sample size (n = 30) and minimum number of unique localities (n = 5). However, if there were 15 or more unique localities and a sample size of less than 30, the species was included.The MVS map was reprojected to a world geodetic system (WGS 1984, EPSG:4326) and clipped to the 2019–20 wildfire map in QGIS version 3.1270. The NIAFED and GEEBAM maps were aligned and matched to the resolution of the MVS map using the package raster version 3.0-1271 in R version 3.6.265. Major vegetation subgroups61, 2019–20 wildfire status36, and fire frequency69 were extracted for each ALA record using raster. The proportion of each MVS burnt was calculated by clipping MVS maps with the 2019–20 burn map in ArcMap Version 10.6.172. All map files used in our analyses are available at (html location to be confirmed upon acceptance) for use with our R script.We complemented species distributional data (ALA60 point data) with spatial information on their associated habitat (MVS61), to avoid reliance on the limited data for some species. To determine the potential distribution of each species we buffered the latitudinal and longitudinal extents of the raster datasets (MVS, fire frequency, NIAFED, and GEEBAM) by 20% in each direction. For geographically-restricted species with latitudinal or longitudinal ranges less than one degree (~111 km), we buffered their extent by one degree in each direction along that axis or axes. These values were chosen as conservative estimates of species distributional extents, but we recognize that this treatment may over-inflate the distribution of some species with highly-localized ranges. These data are broken into four files:Map_data — hosts all of the map files used in the analysesBee-plant_point_data — hosts the ALA download data, combined bee dataset, and the life history and plant data spreadsheetWard_comparison_data — hosts some of the data used for the Ward co-analysis using our methodAll_other_R_data — hosts many of the runfiles from our main analysis

The National Indicative Aggregated Fire Extent Dataset has been developed rapidly to support the immediate needs of the Department of Climate Change, Energy, the Environment and Water (DCCEEW, previously DAWE) in:quantifying the potential impacts of the 2019/20 bushfires on wildlife, plants and ecological communities; and,identifying appropriate response and recovery actions.The intent was to derive a reliable, agreed, fit for purpose and repeatable national dataset of burnt areas across Australia for the 2019/20 bushfire season.The NIAFED was first published on 13 February 2020 and was updated several times during 2020 to reflect updates to fire extent datasets from state and territory agencies. Most changes across these versions, after February (end of summer), reflect refinements on previous extent mapping, rather than new burnt areas. Fire analyses and decision making within the department after June 2020 has been based on the GEEBAM dataset. The GEEBAM dataset reports on fire severity within the NIAFED v20200225 extent envelope and includes some areas determined to be unburnt within NIAFED areas.NOTE: previous versions of this dataset are available on request to geospatial@dcceew.gov.auThe dataset takes the national Emergency Management Spatial Information Network Australia (EMSINA) data service, which is the official fire extent currently used by the Commonwealth and adds supplementary data from other sources to form a cumulative national view of fire extent. This EMSINA data service shows the current active fire incidents, and the Department map shows the total fire extent from 1 July 2019 to the 22 June 2020.EMSINA have been instrumental in providing advice on access to data and where to make contact in the early stages of developing the National Indicative Aggregated Fire Extent Dataset.This dataset is released on behalf of the Commonwealth Government and endorsed by the National Burnt Area Dataset Working Group, convened by the National Bushfire Recovery Agency.Known Issues:The dataset has a number of known issues, both in its conceptual design and in the quality of its inputs. These are outlined below and should be taken into account in interpreting the data and developing any derived analyses.The list of known issues below is not comprehensive: it is anticipated that further issues will be identified in the future, and the Department welcomes feedback on this. We will seek as far as possible to continuously improve the dataset in future versions.In addition, the 2019/20 bushfire season is ongoing and it can be expected that the fire extent will increase.Future versions of the dataset will therefore document and distinguish between changes arising from methodological improvement, as distinct from changes to the actual fire extent.The dataset draws data together from multiple different sources, including from state and territory agencies responsible for emergency and natural resource management, and from the Northern Australian Fire Information website. The variety of mapping methods means that conceptually the dataset lacks national coherency. The limitations associated with the input datasets are carried through to this dataset. Users are advised to refer to the input datasets’ documentation to better understand limitations.The dataset is intentionally precautionary and the rulesets for its creation elect to accept the risk of overstating the size of particular burnt areas. If and when there are overlapping polygons for an area, the internal boundaries have been dissolved.The dataset shows only the outline of burnt areas and lacks information on fire severity in these areas, which may often include areas within them that are completely unburnt. For the intended purpose this may limit the usability of the data, particularly informing on local environmental impacts and response. This issue will be given priority, either for future versions of the dataset or for development of a separate, but related, fire severity product.This continental dataset includes large burnt areas, particularly in northern Australia, which can be considered part of the natural landscape dynamics. For the intended purpose of informing on fire of potential environmental impact, some interpretation and filtering may be required. There are a variety of ways to do this, including by limiting the analysis to southern Australia, as was done for recent Wildlife and Threatened Species Bushfire Recovery Expert Panel’s preliminary analysis of 13 January 2020. For that preliminary analysis area, boundaries from the Interim Biogeographic Regionalisation of Australia version 7 were used by the Department to delineate an area of southern Australia encompassing the emergency bushfire areas of the southern summer. The Department will work in consultation with the expert panel and other relevant bodies in the future on alternative approaches to defining, spatially or otherwise, fire of potential environmental impact.The dataset cannot be used to reliably recreate what the national burnt area extent was at a given date prior to the date of release. Reasons for this include that information on the date/time on individual fires may or may not have been provided in the input datasets, and then lost as part of the dissolve process discussed in issue 2 above.With fires still burning extents are not yet refined.Fire extents are downloaded daily, and datasets are aggregated. This results in an overlap of polygon extents and raises the issue that refined extents are disregarded at this early stage.The Northern Australian Fire Information (NAFI) dataset is only current to 19 June 2020.

[Superseded] This dataset is a single layer from [Superseded] City Plan 2014 – v16.00–2019 collection. Not all layers were updated in this amendment, for more information on past Adopted City Plan amendments. This feature class is shown on the Bushfire overlay map (map reference: OM-002.3).This feature class includes the following sub-categories:(a) High hazard area sub-category;(b) Medium …Show full description[Superseded] This dataset is a single layer from [Superseded] City Plan 2014 – v16.00–2019 collection. Not all layers were updated in this amendment, for more information on past Adopted City Plan amendments. This feature class is shown on the Bushfire overlay map (map reference: OM-002.3).This feature class includes the following sub-categories:(a) High hazard area sub-category;(b) Medium hazard area sub-category;(c) High hazard buffer area sub-category;(d) Medium hazard buffer area sub-category.(e) Potential impact sub-category;(f) Very high potential bushfire intensity sub-category;(g) High potential bushfire intensity sub-category;(h) Medium potential bushfire intensity sub-category;(i) Potential impact buffer sub-category.For information about the overlay and how it is applied, please refer to the Brisbane City Plan 2014 document.This dataset utilises Brisbane City Council's Open Spatial Data website to provide additional features for viewing and downloading the data.The first resource is in HTML format. The GO TO button will launch our Open Spatial Data website and this will let you preview the data and enable additional download options. The resources labelled GeoJSON, KML and SHP will give you a download of the entire dataset. The ESRI REST resource connects to metadata for the layer while the CSV resource will download attribute data in a table. For more information on the new features and other tips and tricks please read our Blog.

This extract includes projects funded through the Local Economic Recovery Fund, as seen on the bushfire-affected LGAs interactive map.

Context: Sound taxonomy is the cornerstone of biodiversity conservation. Without a fundamental understanding of species delimitations, as well as their distributions and ecological requirements, our ability to conserve them is drastically impeded. Cryptic species – two or more distinct species currently classified as a single species – present a significant challenge to biodiversity conservation. How do we assess the conservation status and address potential drivers of extinction if we are unaware of a species’ existence? Here, we present a case where the reclassification of a species formerly considered widespread and secure – the sugar glider (Petaurus breviceps) – has dramatically increased our understanding of the potential impacts of the catastrophic 2019–20 Australian megafires to this species. Methods: We modelled and mapped the distribution of the former and reclassified sugar glider (Petaurus breviceps). We then compared the proportional overlap of fire severity classes between the former and reclassified distribution, and intersect habitat suitability and fire severity to help identify areas of important habitat following the 2019–20 fires. Key Results: Taxonomic revision means that the distribution of this iconic species appears to have been reduced to 8% of its formerly accepted range. Whereas the 2019–20 Australian megafires overlapped with 8% of the formerly accepted range, they overlapped with 33% of the proposed range of the redefined Petaurus breviceps. Conclusions: Our study serves as a sombre example of the substantial risk of underestimating impacts of mega-disturbance on cryptic species, and hence the urgent need for cataloguing Earth’s biodiversity in the age of megafire.,Methods Occurrence data Occurrence records of P. breviceps were collected from the Atlas of Living Australia (https://www.ala.org.au) and were subject to a filtering process. Because sugar gliders were introduced to Tasmania (Campbell et al. 2018), we excluded all Tasmanian records. We then removed dubious records by clipping all records to either the former P. breviceps range (based on IUCN maps; IUCN 2020) or the proposed reclassified P. breviceps range (Cremona et al. 2021) to create two sets of occurrence data (i.e., one each for the former and reclassified P. breviceps). It is worth noting, however, that the reclassified distribution of P. breviceps proposed by Cremona et al. (2021) is an estimate based on genetic and morphological data. Although evidence currently suggests that the Great Dividing Range acts as the western edge of the distribution of P. breviceps (Cremona et al. 2021), we cannot be certain of this. However, for the purposes of this study we have assumed it to be so. In both datasets, records were removed if: (i) they were missing date information or were collected before the year 2000; or (ii) they had high locational uncertainty (e.g., vague or inaccurate locations). Records within any 1 × 1 km grid cell were collapsed into a single record. The final filtered data base consisted of 7777 presence records within the formerly considered geographic range, and 5089 within the reclassified range (see Figure S1). Geographic range estimation We mapped the extent of occurrence (EOO) of the former and reclassified P. breviceps using the occurrence datasets. Extent of occurrence is defined as the area enclosed by the shortest possible boundary containing all sites in which a species is known to be present (IUCN 2021). We calculated EOO as α‐hulls (a generalisation of convex polygons that allow for breaks in species ranges), using the ‘alphahull’ package in R version 3.6.2 (R Core Team 2021), specifying a α value of two (IUCN 2021). We regarded EOO as preferable to area of occupancy (AOO) because maps of the latter showed clear spatial bias indicated by high densities of records surrounding major capital cities. Species distribution modelling Using the maxent algorithm, we developed species distribution models (SDMs) based on the two occurrence datasets outlined above (Phillips et al. 2006). We selected SDM environmental layers based on their likely importance to P. breviceps habitat suitability. All environmental layers were resampled to 1 × 1 km resolution prior to being included in models. A set of 10,000 background points were included within the SDM to compare densities in environmental values occupied by P. breviceps with those of the surrounding unoccupied environment. We addressed sample bias within the study area with a ‘target group’ background sampling approach (Phillips et al. 2009) (see Figure S1). We defined the target group as arboreal mammal species occurring within the study area, including P. breviceps. Sampling intensity for target group species was mapped by converting species presence records of the target group to a kernel density map using the kde2d function of the ‘MASS’ package (Venables and Ripley 2002) set with the default kernel bandwidth. Model performance was measured as area under the curve (AUC) of the receiver operating characteristic (ROC) plot, and the contribution of environmental variables to the response variable was measured as permutation importance (Phillips 2005). Fire overlap We overlapped the former and reclassified P. breviceps EOO with 2019–20 bushfire severity maps from the Google Earth Engine Burnt Area Mapping (GEEBAM; DIPE 2020). GEEBAM classifies the cells within the fire boundary as one of five fire severity classes: no data (cleared land, water etc.); unburnt (unburnt and lightly burnt); low and moderately burnt (some or moderate change post-fire); high severity (vegetation mostly scorched); and very high severity (vegetation clearly consumed). When calculating fire overlap, we considered only fires occurring within the Department of Agriculture, Water and Environment’s (2020) ‘preliminary area for environmental analysis’ (following Legge et al. 2020). This area encompasses bioregions that were deemed to have experienced anomalously substantial fire activity during the 2019–20 bushfire season. Overlap measures were calculated using QGIS version 3.14.1 (QGIS Development Team 2021). We created a fire severity × habitat quality matrix to help identify the spatial intersection between fire severity and habitat quality for the reclassified P. breviceps. First, we classified the continuous output of relative habitat quality derived from the SDM into four discrete classes: low quality (relative likelihood of occurrence 0–0.25); low–medium quality (relative likelihood of occurrence 0.25–0.50); medium–high quality (relative likelihood of occurrence 0.5–0.75); and high quality (relative likelihood of occurrence 0.75–1). We then combined the reclassified SDM with the GEEBAM fire severity layer to derive a layer with 16 unique combinations of all combinations of habitat quality and fire severity and mapped this across the range of P. breviceps.,

This map describes Australian fuel type classes and their estimated extents using the Bushfire Fuel Classification (BFC) framework of Hollis et al. (2015) and Cruz et al. (2018). The BFC is a hierarchical, structure-based classification system for fuel complexes, enabling distinct fuel extents and characterisations to be mapped directly onto fire behaviour models. The map has been generated using nationally consistent, open-source datasets, predominantly derived from remotely sensed data, to quantitatively characterise vegetation life forms, height and foliage cover. The automated production of this map allows for rapid versioning as data inputs are enhanced. This version of the BFC fuel types map integrates multiple spatial and temporal resolution datasets, ranging from 10 to 500 metres. For a detailed methodology, refer to Joshi et al. (2025). Lineage: Fuel types have been created by combining height and foliage cover data using a rule-based method according to the BFC framework of Hollis et al. (2015) and Cruz et al. (2018). Cover data were taken from the woody and grass foliage cover data derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery averaged from 2000 to 2021, as described by Donohue and Renzullo (2025). Vegetation height and cover profile data came from Scarth et al. (2019) and Lang et al. (2023), which incorporate observations from multiple optical and radar satellite-based sensors. Plantation data were included from the National Plantation Inventory (NPI) (ABARES, 2022). Croplands, Horticulture, and Wetlands were included from the Australian Land Use Mapping (ALUM) (ABARES, 2021). Sedgelands are from the National Vegetation Information System (NVIS) (DCCEEW, 2020). Spinifex is derived from multiple MODIS products; detail method is given in Joshi et al. (2025). Built-up is from the polygon footprints provided by Australian Housing Data Analytics Platform (AHDAP, 2022). Bare ground and Water are extracted from the MODIS time-series from 2000-2021, as given in Guerschman et al. (2018) and Donohue et al. (2022) respectively.

Important Disclaimer: CSIRO advises that the information contained in this dataset comprises general statements and information based on scientific research. The user is advised and needs to be aware that such information may be incomplete or unable to be used in any specific situation. No reliance or actions must therefore be made on that information without seeking prior expert professional, scientific and technical advice. To the extent permitted by law, CSIRO (including its employees and consultants) excludes all liability to any person for any consequences, including but not limited to all losses, damages, costs, expenses and any other compensation, arising directly or indirectly from using this publication (in part or in whole) and any information or material contained in it.

The Australian Google Earth Engine Burnt Area Map (AUS GEEBAM) is a rapid, national approach to fire severity mapping. It has been developed rapidly to support the immediate needs of the Department of Climate Change, Energy, the Environment and Water (DAWE) in:a) quantifying the potential impacts of the 2019/20 bushfires on wildlife, plants and ecological communities, andb) identifying appropriate response and recovery actions.AUS GEEBAM Fire Severity uses Sentinel 2A satellite imagery from before and after fire to estimate the severity of burn within each 40m grid cell. Fire severity is defined as a metric of the loss or change in organic matter caused by fire.The extent of the 2019/2020 fires was derived from the National Indicative Aggregated Fire Extent Dataset (NIAFED). NIAFED was sourced from the national Emergency Management Spatial Information Network Australia (EMSINA) data service, which is the official fire extent currently used by the Commonwealth and adds supplementary data from other sources to form a cumulative national view of fire extent.AUS GEEBAM relies on a vegetation index (Relativised Normalized Burnt Ratio, RNBR) that is calculated for burnt areas and adjacent unburnt areas, before and after the fire season. The result is a map of four fire severity classes that represent how severely vegetation was burnt during the 2019/2020 fires.To determine a reference unburnt condition, the NIAFED extent was buffered by 2km. For each NVIS broad vegetation type, in each IBRA bioregion a reference unburnt RNBR class was determined. That value was available to calculate a standardised offset or a reference unburnt value.Each IBRA bioregion was systematically assessed to correct for obvious errors. For example, the Very High severity class could be adjusted down by one RNBR Value for a fire where its extent extended into an area of lower severity. Conversely, there were areas of shrublands that had clearly burnt at Very High severity where all of the biomass is likely to have been consumed but low pre-fire biomass had given it a lower RNBR Value.Each pixel of AUS GEEBAM contains the raw RNBR Value, the RNBR Class and the GEEBAM Value. This allows an end user to observe which values have been adjusted during the calibration away from the default global RNBR Value and allows for some transparency in the process.GEEBAMValueGEEBAM ClassDescription1No dataNo data indicates areas outside NIAFED or NVIS categories that do not represent native vegetation (e.g. cleared land, water)2UnburntLittle or no change observed between pre-fire and post-fire imagery.3Low and ModerateSome change or moderate change detected when compared to reference unburnt areas outside the NIAFED extent.4HighVegetation is mostly scorched.5Very highVegetation is clearly consumed.Known Issues:The dataset has a number of known issues, both in its conceptual design and in the quality of its inputs. These are outlined below and should be taken into account when interpreting the data and developing any derived analyses.The list of known issues below is not comprehensive, it is anticipated that further issues will be identified, and the Department welcomes feedback on this. We will seek as far as possible to continuously improve the dataset in future versions.AUS GEEBAM classes are not based on field data and no confidence interval or report on accuracy has been provided.The number of severity classes has been reduced by combining low and moderate severity fires. Single index thresholds are known to feature poor delineation of low fire severity classes.AUS GEEBAM classes are calibrated systematically for each bioregion using visual interpretation of Sentinel 2 false colour composites. The limitations associated with the NIAFED are carried through to this dataset. Users are advised to refer to the NIAFED documentation to better understand limitations.This continental dataset includes large burnt areas, particularly in northern Australia, which can be considered part of the natural landscape dynamics. For the intended purpose of informing on the potential impact of fire on the environmental, some interpretation and filtering may be required. The NIAFED dataset used as the extent layer for AUS GEEBAM Fire Severity is current as of 24 February 2020. More recent versions were available at the time of creation, however, these would have introduced burnt areas from a second fire season in Northern Australia where fire patterns differ greatly to that of southern Australia.NOTE: Report methodology and supporting material is available on request to geospatial@dcceew.gov.auTo download this data go to AUS GEEBAM download file

This vector dataset presents the extent of areas in European countries directly affected by wildfires (period 2000-2017). This dataset can be used as one of the indications where the danger of wildfires may persist or increase in the future under the changing climate. The dataset is one of the output of the “European Forest Fire Information System-EFFIS” (http://effis.jrc.ec.europa.eu) provided by the Joint Research Centre (JRC). The dataset is also part of the EEA indicator "Forest fires": https://www.eea.europa.eu/data-and-maps/indicators/forest-fire-danger-2/assessment.

This dataset details the proportion of the geographic range of 26,062 Australian plant species burnt in the 2019-2020 megafire; threatened listing status on state and Commonwealth threatened species legislation; species endemic status in each state/territory according to the Australian Plant Census; and risk ranking for exposure to high fire frequency (short intervals between fires) and cumulative impacts of fire (populations dominated by immature individuals). Further details are provided in the users should consult and cite the associated paper:

Gallagher, R.V., Allen, S., MacKenzie, B.D.E., Yates, C.D., Gosper C.R, Keith, D.A., 29 Merow, C., White, M., Wenk, E., Maitner, B.S., He, K., Adams, V.M. & Auld, T.D. (2021) High fire frequency and the impact of the 2019-2020 megafires on Australian plant diversity. Diversity & Distributions.

Usage Notes Species names were listed as accepted in the Australian Plant Census as of July 2020. Range data was sourced from three lines of evidence: (1) cleaned occurrence data (latitude-longitude point locations) associated with digitised herbarium specimens accessed from the Australasian Virtual Herbarium (https://avh.ala.org.au/) via the Atlas of Living Australia Application Programming Interface (https://api.ala.org.au/) in July 2020; (2) range mapping built from Poisson Point Process models, range bagging and area of occurrence (AOO) calculations; and (3) maps for Species of National Environmental Significance (SNES) for species listed on the Commonwealth Environment Protection and Biodiversity Conservation Act 1999 (EPBC Act) available from the SPRAT database (http://www.environment.gov.au/cgi-bin/sprat/public/sprat.pl). Details of the building of range models are available in the paper associated with this dataset.

The spatial extent of the 2019-2020 fires was quantified using the National Indicative Aggregated Fire Extent Dataset (NIAFED; https://data.gov.au/dataset/ds-environment-9ACDCB09-0364-4FE8-9459-2A56C792C743/details?q=). Geographic ranges were intersected with the NIAFED dataset and proportion of burnt range is reported in the columns: "Proportion of range map burnt", "Proportion of SNES range map burnt (EPBC Act species only) ", and "Proportion of point locations burnt".

Exposure to high fire frequency and the cumulative fire risk rankings were created by intersecting ranges with fire history data for the last 5 years (non-woody species), 15 years (woody species) and 50 years (rainforest trees) and trait data on fire response. Species level data on growth form and fire response traits (resprouter, obligate seeder) were sourced from the AusTraits database (https://www.biorxiv.org/content/10.1101/2021.01.04.425314v1).

The annual spatial extent of fires between September-March between 1969-2018 was quantified by combining data from remote sensing and state agency fire history databases. Remotely sensed data on fire extent in each season between 2003 and 2016 was accessed from the Global Fire Atlas https://www.globalfiredata.org/fireatlas.html and – using the same methods – fire extent data was created for the 2017 and 2018 seasons using imagery from the MODIS product (MCD64A1). Alternate data on annual fire history were accessed under license from environment agency databases in three Australian states – New South Wales (NSW National Parks and Wildlife Service Fire History – Wildfire and Prescribed Burns dataset https://data.nsw.gov.au/data/dataset/1f694774-49d5-47b8-8dd0-77ca8376eb04), Western Australia (Western Australian Department of Biodiversity, Conservation and Attractions Fire History dataset (1969-2020)), and Victoria (Victorian Department of Environment, Land, Water and Planning Fire History dataset). Methods for assigning species ranks are provided in Gallagher (2020) https://www.environment.gov.au/system/files/pages/289205b6-83c5-480c-9a7d-3fdf3cde2f68/files/final-national-prioritisation-australian-plants-affected-2019-2020-bushfire-season.pdf

All correspondence about the dataset should be directed to rachael.gallagher@mq.edu.au. Additional data about fire impacts and threat interactions, as well as code for anlayses, are also available.

Debris flows are extremely damaging and dangerous post-fire hazards that can cause significant short- and long-term impacts to rivers and aquatic ecosystems, water quality, and infrastructure. However, they are relatively poorly documented in NSW. High-resolution aerial imagery highlights significant debris flow activity in parts of NSW severely impacted by the 2019/20 Black Summer bushfires, specifically the Tuross, Tumut and Lake Burragorang catchments which were mapped in detail. This inventory of debris flow occurrences was used to train and validate a predictive logistic regression model using key predictor variables slope, fire severity, aridity, geology and soil erodibility. The model outputs can inform assessments of future potential hazards to threatened aquatic species, remote infrastructure such as roads and properties, and drinking water reservoirs and associated infrastructure.

For more information, please read the accompanying report, ‘Post-fire debris flows in NSW: Susceptibility modelling and implications for management’, or check out this link: https://www.environment.nsw.gov.au/topics/water/estuaries/estuaries-research/bushfire-affected-waterways

Debris flows are extremely damaging and dangerous post-fire hazards that can cause significant short- and long-term impacts to rivers and aquatic ecosystems, water quality, and infrastructure. However, they are relatively poorly documented in NSW. High-resolution aerial imagery highlights significant debris flow activity in parts of NSW severely impacted by the 2019/20 Black Summer bushfires, specifically the Tuross, Tumut and Lake Burragorang catchments which were mapped in detail. This inventory of debris flow occurrences was used to train and validate a predictive logistic regression model using key predictor variables slope, fire severity, aridity, geology and soil erodibility. The model outputs can inform assessments of future potential hazards to threatened aquatic species, remote infrastructure such as roads and properties, and drinking water reservoirs and associated infrastructure. For more information, please read the accompanying report, ‘Post-fire debris flows in NSW: Susceptibility modelling and implications for management’, or check out this link: https://www.environment.nsw.gov.au/topics/water/estuaries/estuaries-research/bushfire-affected-waterways

The SBMP requires regional fire management plans (RFMPs) to provide a link between the strategy of this plan and the more detailed bushfire operational plans (BOPs). RFMPs will be updated to cover the entire ACT to reflect boundaries based on bushfire risk and geography. RFMPs detail the five-year program (2014–19) of work for fuel reduction, access and infrastructure in the ACT. RFMPs for 2019–24 will be prepared during the life of the SBMP. The ACT Emergency Services Commissioner (the Commissioner) is responsible for approval of RFMPs. They will be reviewed as required to reflect significant changes. These may include unplanned bushfires, which may provide strategic advantages or changes to the location or extent of assets – for example, the development of new estates. IMPORTANT NOTICE The ACT Government is providing this bushfire management map for information purposes only. This data is derived from the best available vegetation. The ACT Government cannot and does not guarantee the accuracy and completeness of any data and information contained on this site as, among other reasons, there may have been changes to land use and vegetation since the map was produced. The ACT Government disclaims liability to any person who acts in reliance on the information provided on this site or contained within the reports or plans on it whether that liability is in negligence or on any other legal basis. Persons who would otherwise seek to rely on the data and information contained on this site should make their own inquiries and seek their own expert advice. [1] BPA is already declared over the Rural Areas of the ACT for the purposes of AS 3959 assessment

Creative Commons License Creative Common By Attribution 4.0 (Australian Capital Territory), Please read Data Terms and Conditions statement before data use.

The SBMP requires regional fire management plans (RFMPs) to provide a link between the strategy of this plan and the more detailed bushfire operational plans (BOPs). RFMPs will be updated to cover the entire ACT to reflect boundaries based on bushfire risk and geography. RFMPs detail the five-year program (2014–19) of work for fuel reduction, access and infrastructure in the ACT. RFMPs for 2019–24 will be prepared during the life of the SBMP. The ACT Emergency Services Commissioner (the Commissioner) is responsible for approval of RFMPs. They will be reviewed as required to reflect significant changes. These may include unplanned bushfires, which may provide strategic advantages or changes to the location or extent of assets – for example, the development of new estates. IMPORTANT NOTICE The ACT Government is providing this bushfire management map for information purposes only. This data is derived from the best available vegetation. The ACT Government cannot and does not guarantee the accuracy and completeness of any data and information contained on this site as, among other reasons, there may have been changes to land use and vegetation since the map was produced. The ACT Government disclaims liability to any person who acts in reliance on the information provided on this site or contained within the reports or plans on it whether that liability is in negligence or on any other legal basis. Persons who would otherwise seek to rely on the data and information contained on this site should make their own inquiries and seek their own expert advice. [1] BPA is already declared over the Rural Areas of the ACT for the purposes of AS 3959 assessment

Creative Commons License Creative Common By Attribution 4.0 (Australian Capital Territory), Please read Data Terms and Conditions statement before data use.

Generalised version at 1:100:000 scale with the LGA boundaries dissolved of the BUSHFIRE_PRONE_AREA dataset. Polygon features identify designated Bushfire Prone Areas where specific bushfire building construction requirements apply. The municipal areas of Melbourne, Yarra, Maribyrnong, Moonee Valley, Darebin, Boroondara, Stonnington, Glen Eira, Moreland, Port Phillip and Bayside do not have any designated bushfire prone areas. The original boundaries were gazetted on 7 Sep 2011. Changes to the boundaries have been gazetted on 25 Oct 2012, 8 Oct 2013, 30 Dec 2013, 3 June 2014, 22 Oct 2014, 19 August 2015, 21 April 2016, 18 October 2016, 02 June 2017, 06 November 2017, 16 May 2018, 16 Oct 2018, 4 Apr 2019, 10 Sep 2019, 24 March 2020, 7 September 2020, 25 January 2021, 6 July 2021, 18 March 2022, 17 August 2022, 20 April 2023, 15 December 2023, 10 September 2024

Bushfire prone areas (BPA) of Victoria review 23, gazetted 10/09/2024. The BPA map depicts locations where new buildings, alterations and/or additions must meet the ‘bushfire prone area’ requirements of the National Construction Code and a minimum Bushfire Attack Level (BAL) 12.5 construction standard (Section 192A Building Act 1993 – Bushfire Prone Areas determination, and construction requirements of the Building Regulations 2018). This data set has been simplified using ArcGIS Pro 3.0.0 - Generalize Tool with a 50m tolerance.

Satellite image map of the forest fire situation near Lübtheen Mecklenburg-Vorpommern based on a picture of the optical satellite Sentinel-2 from 01 July 2019, 10:20 UTC.

Aerial map of the forest fire situation near Lübtheen Mecklenburg-Vorpommern based on optical aerial photographs taken on 2 July 2019 between 16:50 and 17:20 UTC.

Polygon features identify designated Bushfire Prone Areas where specific bushfire building construction requirements apply. The municipal areas of Melbourne, Yarra, Maribyrnong, Moonee Valley, Darebin, Boroondara, Stonnington, Glen Eira, Moreland, Port Phillip and Bayside do not have any designated bushfire prone areas. The original boundaries were gazetted on 7 Sep 2011. Changes to the boundaries have been gazetted on 25 Oct 2012, 8 Oct 2013, 30 Dec 2013, 3 June 2014, 22 Oct 2014, 19 August 2015, 21 April 2016, 18 October 2016, 02 June 2017, 06 November 2017, 16 May 2018, 16 Oct 2018, 4 Apr 2019, 10 Sep 2019, 24 March 2020, 7 September 2020, 25 January 2021, 6 July 2021, 18 March 2022, 17 August 2022, 20 April 2023, 15 December 2023, 10 September 2024 Bushfire prone areas (BPA) of Victoria review 23, gazetted 10/09/2024. The BPA map depicts locations where new buildings, alterations and/or additions must meet the ‘bushfire prone area’ requirements of the National Construction Code and a minimum Bushfire Attack Level (BAL) 12.5 construction standard (Section 192A Building Act 1993 – Bushfire Prone Areas determination, and construction requirements of the Building Regulations 2018). Refer to the following web links for information and Interactive Map. https://www.planning.vic.gov.au/bushfire-protection/building-in-bushfire-prone-areas

Content

VIIRS daily reflectance data for Red, NIR and MIR bands + VIIRS active fires on a 0.01x0.01º geographical grid for the period of 2019-09-01 to 2020-02-17 in the format used as input for BA-Net (https://github.com/mnpinto/banet) to map and date burned pixels.