From DataNSW
JSON RDF ISO19115-3 XML

Historical Fire Extent and Severity Mapping (FESM) - Statewide 2007-08

Created 05/05/2025

Updated 05/05/2025

JSON RDF ISO19115-3 XML

Fire severity is a metric of the loss of biomass caused by fire. In collaboration with the NSW Rural Fire Service, the department's 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 statewide historical severity mapping of fires >100ha for the 2007-08 fire year, which is based on Landsat satellite imagery (30m pixels). From 2016/17 to the current fire year is covered in the statewide FESM data, which is based on Sentinel 2 satellite imagery (10m pixels).

Files and APIs

Tags

Additional Info

Field Value
Title Historical Fire Extent and Severity Mapping (FESM) - Statewide 2007-08
Language English
Licence Creative Commons Attribution 3.0 Australia
Landing Page https://devweb.dga.links.com.au/data/dataset/4547e92b-f69b-42ba-9461-465585d2f482
Remote Last Updated 21/02/2025
Contact Point
New South Wales Datasets
test@email.loc
Reference Period 01/07/2006 - 30/06/2007
Geospatial Coverage { "type": "Polygon", "coordinates": [ [ [ 141, -37.7 ], [ 141, -28 ], [ 154, -28 ], [ 154, -37.7 ], [ 141, -37.7 ] ] ]}
Data Portal data.gov.au

Data Source

This dataset was originally found on data.gov.au "Historical Fire Extent and Severity Mapping (FESM) - Statewide 2007-08". Please visit the source to access the original metadata of the dataset:
https://devweb.dga.links.com.au/data/dataset/historical-fire-extent-and-severity-mapping-fesm-statewide-200708

Original dataset
Dataset copies

No duplicate datasets found.