Bush Fire Prone Land is mapped within a local government area, which becomes the trigger for planning for bush fire protection. Bush Fire Prone Land mapping is intended to designate areas of the State that are considered to be higher bush fire risk for development control purposes. Not being designated bush fire prone is not a guarantee that losses from bush fires will not occur. The NSW Bush Fire Prone Land dataset is a map prepared in accordance with the Guide for Bush Fire Prone Land Mapping (BFPL Mapping Guide) and certified by the Commissioner of NSW RFS under purposes of Section 10.3 of the Environmental Planning and Assessment Act 1979 No 203. Over time there has been various releases of the BFPL Mapping Guide, in which the categories and types of vegetation included in the BFPL map have changed. The version of the guide under which, each polygon or LGA was certified is contained in the data. BFPL is an area of land that can support a bush fire or is likely to be subject to bush fire attack, as designated on a bush fire prone land map. The definition of bushfire vegetation categories under guideline version 5b: * Vegetation Category 1 consists of: > Areas of forest, woodlands, heaths (tall and short), forested wetlands and timber plantations. * Vegetation Category 2 consists of: >Rainforests. >Lower risk vegetation parcels. These vegetation parcels represent a lower bush fire risk to surrounding development and consist of: - Remnant vegetation; - Land with ongoing land management practices that actively reduces bush fire risk. * Vegetation Category 3 consists of: > Grasslands, freshwater wetlands, semi-arid woodlands, alpine complex and arid shrublands. * Buffers are created based on the bushfire vegetation, with buffering distance being 100 metres for vegetation category 1 and 30 metres for vegetation category 2 and 3. Vegetation excluded from the bushfire vegetation categories include isolated areas of vegetation less than one hectare, managed lands and some agricultural lands. Please refer to BFPL Mapping Guide for a full list of exclusions. The legislative context of this dataset is as follows: On 1 August 2002, the Rural Fires and Environmental Assessment Legislation Amendment Act 2002 (Amendment Act) came into effect. The Act amended both the Environmental Planning and Assessment Act 1979 and the Rural Fire Services Act 1997 to ensure that people, property and the environment are more fully protected against the dangers that may arise from bushfires. Councils are required to map bushfire prone land within their local government area, which becomes the trigger for the consideration of bushfire protection measures when developing land. BFPL Mapping Guidelines are available from www.rfs.nsw.gov.au

Please see Google Earth Engine Burnt Area Factsheet Data and Resources

FireTools Cloud is a web-based GIS processing environment developed by the NSW Bushfire Risk Management Research Hub, a NSW focused research partnership between the NSW Department of Planning, Industry and Environment, the University of Wollongong, Western Sydney University, the University of NSW, the University of Tasmania, the University of Melbourne and the NSW Rural Fire Service. It is designed to replicate and replace the functionality of the FireTools II ArcGIS processing plugin to assist in fire management planning. Users upload a datapack containing the GIS files used to run a standard FireTools II analysis, configure the layers and fields that define the analysis, and submit the analysis for processing. After processing is complete, users can download a results pack containing GIS files with analysis results. Selected results are distributed for use as described below. Results are true and correct only for the reserves within the NPWS Southern Ranges Branch. Fire history outside the reserves is incomplete so results should not be relied upon. Layers in this data package: Heritage threshold status: Input vegetation classified into LongUnburnt, WithinThreshold, Vulnerable, TooFrequentlyBurnt, Unknown and NoFireRegime (raster and vector). This layer is used to monitor the status of vegetation across the study area with respect to its biodiversity-related impacts of fire.

The Integrated Water Quality and Environmental Monitoring Dataset before, during and after the 2019/2020 Bushfires is a comprehensive repository of data compiled from multiple sources, including the MER (Monitoring, Evaluating, Reporting) program and other relevant sources. This dataset encompasses various types of information essential for assessing the impact of the 2019/2020 bushfires on water quality in selected ICOLLs (Intermittently Closed and Open Lakes and Lagoons) and river estuaries. It incorporates historical water quality data collected during the bushfires and post-bushfire period through the MER program, rainfall data from nearby BOM (Australian Bureau of Meteorology) weather stations, logger data deployed at selected estuaries during or shortly after the bushfire season, dates of fire impact on the monitored systems, and surface and depth water quality monitoring data from smart buoys deployed across various estuaries.\r \r Components:\r \r 1.\tEstuary and fire impact data\r Information detailing the systems incorporated in this data set and the dates when these systems were affected by the 2019/2020 bushfires.\r \r 2.\tMER Program Data (Lakes, Rivers):\r Historical water quality data collected during the 2019/2020 bushfires and subsequent periods as part of the MER program. Includes parameters such as pH levels, turbidity, salinity, chlorophyll-a concentrations, dissolved oxygen concentrations and nutrient concentrations. The MER dataset was collected as part of the NSW Government Monitoring, evaluating and reporting on estuaries program. The reported data has met the required QA/QC standards associated with this program. For further information: https://www.environment.nsw.gov.au/topics/water/estuaries/monitoring-and-reporting-estuaries\r \r 3.\tRainfall Data: Precipitation data obtained from BOM weather stations located near the monitored estuaries.\r \r 4.\tLogger data: Data recorded by loggers deployed at selected estuaries including Lake Conjola, Meroo Lake, Termeil Lake, Wonboyn Lake, and Tuross River during or immediately following the 2019/2020 bushfire season . Includes measurements of environmental parameters such as water temperature, dissolved oxygen and salinity. Compiled from published data available here: https://datasets.seed.nsw.gov.au/dataset/bushfire-impact-water-quality\r \r 5.\tSmart Buoy Monitoring Data: Surface and depth water quality monitoring data collected from smart buoys deployed in various estuaries (Wonboyn Lake, Wallaga Lake, Lake Conjola, and Durras Lake). This data provides continuous or periodic measurements of water quality parameters, offering insights into spatial and temporal variations in water quality after the bushfire period in the longer-term.

NSW government schools by Rural Fire Service bushfire category. Includes school codes which can be used to link to other datasets. Data provided for the NSW GovHack, 2017. \r \r Data Notes:\r \r * Category 1 = heavy bush or forest\r * Category 2 = light bush or scrub\r * Category 3 = no bush, grass-covered land\r * Buffer = no bush, but within 50 meters of category 1 or 2 bush\r \r References: \r \r * https://www.rfs.nsw.gov.au/plan-and-prepare/building-in-a-bush-fire-area/additional-information (see: What do the colours mean on the map?)\r * https://datasets.seed.nsw.gov.au/dataset/d6f2d89f-3cdc-4da0-add2-f2da74bc0bfc/metaexport/html (see: abstract)\r \r \r Data Source:\r \r * Asset Management System (AMS), School Infrastructure NSW.

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.

This dataset provides input to the Palerang LGA Bush Fire Prone Land Map, which comprises this Bush Fire Vegetation map plus buffers created in accordance with the Guideline for Bushfire Prone Land Mapping Version 3 - 28 June 2006, NSW Rural Fire Service. Umwelt Pty Ltd (Umwelt) was engaged by Palerang Local Government Area (LGA) to prepare a vegetation and threatened species model for the Palerang Shire. This included amalgamating existing vegetation maps and converting these to the current ‘Biometric vegetation type’ classification. VIS_ID 4209 Map footprint supplied only. Contact Palerang Council for access to the vegetation map. Data and Resources

Fire severity is a metric of the loss of biomass caused by fire. In collaboration with the NSW Rural Fire Service, DPE Remote Sensing & Regulatory Mapping team has developed a semi-automated approach to mapping fire extent and severity through a machine learning framework based on satellite imagery. The method uses standardised classes to allow comparison of different fires across the landscape. The FESM severity classes include: unburnt, low severity (burnt understory, unburnt canopy), moderate severity (partial canopy scorch), high severity (complete canopy scorch, partial canopy consumption), extreme (full canopy consumption). Here we provide historical severity mapping for the Blue Mountains region from 1989/90 to 2015/16, which is based on Landsat satellite imagery. From 2016/17 to the current fire year, this region is covered in the statewide FESM data, which is based on Sentinel 2 satellite imagery.

FireHistory is a feature class that holds final fire boundaries for every year for which there is data. Within the feature class are two subtypes Wildfire (FireType 1) and Prescribed Burn (FireType 2). The polygons are mutually exclusive within each year and they often extend outside NPWS Estate. Fire history is captured by all regions within NPWS. At times data captured by the Rural Fire Service (RFS) and Forestry Corporation NSW are imported into this GDB also. The data are now stored centrally in ArcSDE. Enhance Bushfire Management Program (EBMP) Technical Officers collate, update and amend branch data using versions from ArcSDE.

This dataset contains a standardised assessment of the Overall Fuel Hazard at a location and point in time.

This dataset is an ensemble, or group of simulations of a fire-related climate index, from the 10 models generated by the NSW and Australian Regional Climate Modelling (NARCliM) Project. The dataset has been dynamically downscaled to a 4 km grid cell resolution and covers south-eastern Australia, including five capital cities. To learn more about the NSW Climate Data Portal, please visit https://www.climatechange.environment.nsw.gov.au/climate-data-portal.

PLEASE NOTE:

_ GEEBAM is an interim product and there is no ground truthing or assessment of accuracy. Fire Extent and Severity Mapping (FESM) data should be used for accurate information on fire severity and loss of biomass in relation to bushfires._

The intention of this dataset was to provide a rapid assessment of fire impact.

In collaboration with the University of NSW, the NSW Department of Planning Infrastructure and Environment (DPIE) Remote Sensing and Landscape Science team has developed a rapid mapping approach to find out where wildfires in NSW have affected vegetation. We call it the Google Earth Engine Burnt Area Map (GEEBAM) and it relies on Sentinel 2 satellite imagery. The product output is a TIFF image with a resolution of 15m. Burnt Area Classes:

1. Little change observed between pre and post fire

2. Canopy unburnt - A green canopy within the fire ground that may act as refugia for native fauna, may be affected by fire

3. Canopy partially affected - A mix of burnt and unburnt canopy vegetation

4. Canopy fully affected -The canopy and understorey are most likely burnt

Using GEEBAM at a local scale requires visual interpretation with reference to satellite imagery. This will ensure the best results for each fire or vegetation class.

Important Note: GEEBAM is an interim product and there is no ground truthing or assessment of accuracy. It is updated fortnightly.

Please see Google Earth Engine Burnt Area Factsheet