DEA Burnt Area Characteristic Layers (Sentinel 2 Near Real-Time, Provisional)

Brief description

Background Bushfires pose a serious and increasing threat to Australia. The detection and mapping of burns has many applications to support management of areas impacted by fire. The identification of bushfire burn using Earth Observation is often manual, can come with a significant time delay, and only available at a relatively small scale. This product offers provisional and preliminary change detection using same day satellite data to automatically and rapidly identify burn characteristics. Knowledge about the potential location and extent of fire helps to understand community and ecosystem impacts, enables directed relief and recovery support, and informs planning of mitigation burning for future fire seasons. What this product offers DEA Provisional Burnt Area Characteristic Layers contribute to the understanding of the distribution and frequency of fire in the Australian continent by measuring change in vegetation cover and soil characteristics that may be indicative of fire activity in the landscape. This product contains three layers that each describe change in a specific remote sensing index. Change in each index is measured between a baseline reference image and the most recent observation of Australia from the Sentinel 2 satellite constellation.  The indexes contained in each dataset describe change in a characteristic of the Earth’s surface that may be the result of a burn. The characteristic described are green vegetation cover and the reflective properties of bare soil and of burnt materials. These layers can be used to detect areas that may have been recently burnt, as fire will change the presence of these characteristics in the satellite data. These layers should be used with other information sources to determine if the change is the result of fire or other processes.

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Maintenance and Update Frequency: asNeeded

Statement: The DEA Burnt Area Characteristic Layers is a change detection product derived from two data sources: DEA Sentinel 2 Barest Earth (based on method of Roberts, et al. 2019). The daily Sentinel-2 (A and B combined) Near Real-Time provisional satellite data. The Sentinel-2 (A and B combined) Near Real-Time data is masked for cloud, shadows and other image artefacts using the Sentinel-2 fmask pixel quality layer to help provide as clear a set of observations as possible for change detection. The following indexes are calculated from both the DEA Sentinel 2 Barest Earth and the Sentinel-2 Near Real-Time data: Bare Soil Index (BSI) Normalized Difference Vegetation Index (NDVI) Normalized Burn Ratio (NBR) The change layers for each index are then calculated in the following way for each index: Change(index) = Barest Earth(index) - Near Real-Time(index)

Notes

Purpose
Applications: - As a preliminary use-case to show the potential of near real-time change detection - As a screening tool to identify the potential location of new burnt areas - As a screening tool to identify the potential size of burnt areas - To visually identify potential changes of known burnt areas between two time periods