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 and 06 November 2017.

Bushfire prone areas(BPA) of Victoria review 11, gazetted 2018-05-16 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 (Regulation 810 of the Building Interim Regulations 2017).

Refer to the following web links for information... https://www.planning.vic.gov.au/bushfire-protection/building-in-bushfire-prone-areas http://services.land.vic.gov.au/landchannel/html/help/BushfireProneAreas.htm

Interactive Map. http://services.land.vic.gov.au/landchannel/jsp/map/BushfireProneMapsIntro.jsp

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 and 4 Apr 2019, 24 March 2020, 7 September 2020, 1 Feburary 2021, 6 July 2021.

Bushfire prone areas (BPA) of Victoria review 18, gazetted 06/07/2021. 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 2.5.0 - Generalize Tool with a 50m tolerance

Abstract 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. 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. 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. Apart from small updates to this dataset up until 30 June 2025 there are no plans for another major update to this Product. Currency Date modified: November 2024 Next modification date: June 2025 Data Extent Spatial extent North: -9° South: -44° East: 154° West: 112° Temporal extent 30 December 1899 to 29 August 2024 Source information Catalog entry: Bushfire Boundaries – Historical Lineage Statement Date created: 24 October 2024 Version 3 of this dataset extends upon the previous versions of this dataset built and released under the Australia Research Data Commons Project in early 2023 and National Bushfire Intelligence Capability in October 2023. This dataset represents an updated aggregation of each jurisdiction (except the Northern Territo ry) fire history data to include information from the 2023-24 bushfire season. Sources of State and Territory Data are: - Australian Capital Territory Parks and Conservation - New South Wales Parks and Wildlife Service - New South Wales Rural Fire Service - Queensland Parks and Wildlife Service - South Australia Department of Environment, Water and Natural Resources - Tasmania Department of Natural Resources and Environment - Victorian Department of Energy, Environment and Climate Action - Western Australia Department of Biodiversity, Conservation and Attractions

Please note that some of the above are responsible for the collection and distribution of multiple Agencies data. These agencies are identified at the attribute level.

Northern Territory Data: The Northern Territory Government continue to progress in the development of their Bushfire Extent capabilities. Work is well underway with the relevant agency’s to be able to incorporate NT Government approved Historical Bushfire Extent data in the near future. Product standardisation: The data provided by each jurisdiction is standardised and harmonised. This process maps the existing state/territory attributes to the National Data Schema that was agreed to and endorsed by the participating state agencies and the Australian Fire and Emergency Services Authorities Council. The Digital Atlas of Australia data team published an optimised Bushfire Historic Extents dataset designed to perform efficiently in either a desktop application or a web service. Data dictionary All layers

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.

capture_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.

extinguish_date The date a fire is declared safe (contained and under control). If available.

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

Fire Type definitions

Data Source Category Description

Bushfire Unplanned vegetation fire. A generic term which includes grass fires, forest fires and scrub fires both with and without a suppression objective. Also known as wildfire, accident, arson, lightning.

Prescribed Burn The controlled application of fire under specified environmental conditions to a predetermined area and at the time, intensity, and rate of spread required to attain planned resource management objectives. Also known as planned burning, fuel reduction, traditional owner, ecological, hazard reduction

Unknown Fire type is undetermined.

Ignition Cause definitions

Data Source Category Description

Accidental Fires that are not the result of a deliberate (intentional) act.

Natural Fires that ignite without human intervention.

Incendiary Fires result from deliberate acts, intentional actions, or circumstances for the fire to occur in areas where it should not have occurred.

Undetermined Fires that have not yet been investigated, under investigation or fires that have been investigated and the cause is not proven to an acceptable level of certainty.

Capture Method definitions

Data Source Category Description

Aerial photography Derived from Aerial photography including manual interpretation as well as partially automated and fully automated methods.

Linescanner Mapped against airborne sensor systems.

Ground intelligence Mud map from ground observation.

Ground intelligence GPS Fire boundary derived from ground (e.g. GPS tracker, Avenza).

Air intelligence Mud map from air observation.

Air intelligence GPS Fire boundary derived from air (e.g. helicopter, spotter).

Himawari Derived from geostationary satellite Himawari and includes manual interpretation as well as partially automated and fully automated methods (spatial accuracy ± 2 kilometres).

NOAA AVHRR Derived from Low Resolution - NOAA AVHRR satellite including manual interpretation, partially automated and fully automated methods (spatial accuracy ± 1 kilometres).

MODIS Derived from Low Resolution - MODIS satellite imagery including manual interpretation as well as partially automated and fully automated methods (spatial accuracy ± 250 metres).

VIIRS Derived from Low Resolution - VIIRS satellite imagery including manual interpretation as well as partially automated and fully automated methods (spatial accuracy ± 375 metres).

Landsat Derived from Medium Resolution - Landsat satellite imagery including manual interpretation as well as partially automated and fully automated methods (spatial accuracy ± 30 metres).

Sentinel Derived from Medium Resolution - Sentinel satellite imagery including manual interpretation as well as partially automated and fully automated methods (spatial accuracy ± 10 - 20 metres).

Multiple Derived from multiple sources e.g. combination of ground intel and linescanner. For detailed information contact agency or state responsible.

Unknown Data Source is unknown.

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

Fire severity classification of bushfires (wildfires) impacting ~1.5 million hectares of predominantly forested public land in eastern and north-eastern Victoria (and ~300,000 ha of southern NSW), between November 2019 and March 2020. Fire severity mapping was derived using machine learning classification (Random forests) of eight Spectral Indices (SI) from pre and post fire Sentinel 2 satellite imagery. The fire severity classification model was trained using high resolution (<35 cm) post-fire near-infrared aerial imagery from 12 bushfires which occurred during the 2018/2019 fire season across areas of Central and Eastern Victoria. A detailed description of the classification methodology can be found in Collins et al. (2018). The classification covers woody vegetation landcover types (including native and non-native forest, woodland and shrubland). The primary purpose of this data to provide rapid and comprehensive landscape-scale spatial information about bushfire severity to inform initial risk assessments on the public land in the actual and potential impact zone. This assists with the transition from response to emergency stabilisation and initial recovery in accordance with the Code of Practice for Bushfire Management on Public Land (2012). Fire severity classes are i) Canopy burnt (Class 6)- CB (> 20% canopy foliage consumed); ii) High canopy scorch (5) - HCS (>80% of canopy foliage is scorched); Medium canopy scorch (4) - MCS (Canopy is a mosaic of both unburnt and scorched foliage, 20 - 80%); iii) Low canopy scorch (3) - LCS (Canopy foliage is largely unaffected (<20% scorched), but the understorey has been burnt); iv) Unburnt (2) - UB (Canopy and understorey foliage are largely (>90%) unburnt). Additional classes: v) No Data (0) (e.g. due to obscuration by cloud, cloud-shadow and/or smoke and haze) and vi) Non-woody vegetation (unclassified) (1). An independent cross-validation of the classification model was used to estimate global and per-class model accuracy. Overall accuracy is estimated to be 85% (0.81 Kappa), with producer per-class accuracy ranging from 97% (CB), 91% (HCS), 88% (UB), 75% (LCS) and 61% (MCS). A ground-based validation of the classification has not been undertaken. Data is provided on the basis that users undertake responsibility for assessing the relevance and accuracy of its content. The Department of Environment, Land, Water and Planning, on behalf of the Victorian Government, makes no representations, either expressed or implied, as to the suitability of this data for any particular purpose. We do not accept any liability to any person: - for the information, data or advice (or the use of such information, data or advice) which is provided or incorporated into it by reference - for any interference with or damage to a user's computer, software or data occurring in connection with or relating to this data or its use Related research can be found in L. Collins, P. Griffioen, G. Newell, A. Mellor (2018), The utility of Random Forests for wildfire severity mapping, Remote Sensing of Environment, 216, 374-384