Annual Fire Scars - Landsat, QLD DES algorithm, QLD coverage
The data set is a statewide annual composite of fire scars (burnt area) derived from all available Landsat 5, 7 and 8 images acquired over the period January to December using time series change detection. Fire scars are automatically detected and mapped using dense time series of Landsat imagery acquired over the period 1987 - present. In addition, from 2013, products have undergone significant quality assessment and manual editing. The automated Landsat fire scar map products covering the period 1987-2012 were validated using a Landsat-derived data set of over 500,000 random points sampling the spatial and temporal variability. On average, over 80% of fire scars captured in Landsat imagery have been correctly mapped with less than 30% false fire rate. These error rates are significantly reduced in the edited 2013-2016 fire scar data sets, although this has not been quantified. <br>
For the 2016 annual fire scar composite, the manual editing stage incorporated Landsat and Sentinel 2A imagery (resampled to match Landsat spatial resolution), allowing for increased cloud-free ground observations, and an associated reduction in the number of missed fires (not quantified). Sentinel 2A images were primarily used to map fire scars that were otherwise undetectable in the Landsat sequence due to cloud cover/Landsat revisit time. Additionally, Landsat-7 SLC-Off imagery (affected by striping) was excluded from the 2016 annual composite. It is expected that these modifications should result in improved mapping accuracy for the 2016 period.<br>
A new fire scar detection algorithm has been developed, with a new edited product implemented in 2021.
Simple
Identification info
- Date (Creation)
- 2014-10-14
- Date (Publication)
- 2021-09-23
- Date (Revision)
- 2024-09-23
- Edition
- 1.0
Publisher
Author
Department of Environment and Science (2017-2023), Queensland Government - Collett, Lisa (Scientist (Remote Sensing))
41 Boggo Road, Dutton Park, 4102, Queensland, Australia
Dutton Park
Queensland
4102
Australia
- Website
- https://www.tern.org.au/
- Purpose
- Characterising historic patterns of burning and changing fire regimes over time (spatial extent, timing, patchiness, frequency and intensity) is important for improving our understanding and management of fire, climate, land-use and vegetation interactions. These products may assist the development of appropriate fire management practices and benefit a range of conservation and resource management objectives, as well as ongoing scientific research.
- Credit
- We at TERN acknowledge the Traditional Owners and Custodians throughout Australia, New Zealand and all nations. We honour their profound connections to land, water, biodiversity and culture and pay our respects to their Elders past, present and emerging.
- Credit
- Landsat 5 TM, Landsat 7 ETM+ and Landsat 8 OLI images were acquired from United States Geologic Survey. Copernicus Sentinel 2 data from the European Union and European Space Agency Copernicus Program.
- Status
- Completed
Point of contact
Department of Environment and Science (2017-2023), Queensland Government - van den Berg, Deanna (Principal Scientist (Remote Sensing))
41 Boggo Road, Dutton Park, 4102, Queensland, Australia
41 Boggo Road
Dutton Park
Queensland
4102
Australia
- Topic category
-
- Imagery base maps earth cover
- Environment
Extent
- Description
- Queensland
N
S
E
W
))
Temporal extent
- Time period
- 1987-01-01 2016-12-31
- Title
- Goodwin, N.R. and Collett, L.J. 2014. Development of an automated method for mapping fire history captured in Landsat TM and ETM+ time series across Queensland, Australia. Remote Sensing of Environment 148, 206-221
- Website
-
Goodwin, N.R. and Collett, L.J. 2014. Development of an automated method for mapping fire history captured in Landsat TM and ETM+ time series across Queensland, Australia. Remote Sensing of Environment 148, 206-221
Related documentation
- GCMD Science Keywords
- ANZSRC Fields of Research
- TERN Platform Vocabulary
- TERN Instrument Vocabulary
- TERN Parameter Vocabulary
- QUDT Units of Measure
- GCMD Horizontal Resolution Ranges
- GCMD Temporal Resolution Ranges
Resource constraints
- Use limitation
- The Creative Commons Attribution 4.0 International (CC BY 4.0) license allows others to copy, distribute, display, and create derivative works provided that they credit the original source and any other nominated parties. Details are provided at https://creativecommons.org/licenses/by/4.0/
- File name
- 88x31.png
- File description
- CCBy Logo from creativecommons.org
- File type
- png
- Title
- Creative Commons Attribution 4.0 International Licence
- Alternate title
- CC-BY
- Edition
- 4.0
- Access constraints
- License
- Use constraints
- Other restrictions
- Other constraints
- TERN services are provided on an “as-is” and “as available” basis. Users use any TERN services at their discretion and risk. They will be solely responsible for any damage or loss whatsoever that results from such use including use of any data obtained through TERN and any analysis performed using the TERN infrastructure. Web links to and from external, third party websites should not be construed as implying any relationships with and/or endorsement of the external site or its content by TERN.
Resource constraints
- Classification
- Unclassified
Distribution Information
Distributor
Distributor
Terrestrial Ecosystem Research Network
80 Meiers Road, Indooroopilly, Queensland, 4068, Australia
Indooroopilly
Queensland
4068
Australia
- Distribution format
-
- OnLine resource
- Download Annual Fire Scars data via HTTP
- OnLine resource
- Landscape Data Visualiser
- OnLine resource
-
QLD Annual Fire Scars Landsat
landscapes:qld_annual_fire_scars
- OnLine resource
- ro-crate-metadata.json
Data quality info
- Hierarchy level
- Dataset
- Other
- The input imagery was processed to level L1T by the USGS. Geodetic accuracy of the product depends on the image quality and the accuracy, number, and distribution of the ground control points.
Report
Result
- Statement
- The USGS aims to provide image-to-image registration with an accuracy of 12m. Refer to the L8 Data Users Handbook for more detail. For 1987-2012 automated fire scar products, the average fire scar omission error was measured at 15%.
Resource lineage
- Statement
- Applied outlier identification algorithm to timeseries of geometrically and radiometrically corrected Landsat and Sentinel 2 imagery, as described in https://doi.org/10.1016/j.rse.2014.03.021
- Hierarchy level
- Dataset
Process step
- Description
- Algorithm Summary: Raster pixel values correspond to the month of detection (often different from the date of active fire). A pixel is mapped as burnt if there has been a significant change in reflectance relative to the time series due to the effects of fire e.g. presence of charcoal or ash, removal of foliage, scorch. Pixel values:0: no fire scar was detected during this period;1-12: month (of Landsat acquisition) when fire scar was first detected;254: crop/water masked - no fire scar detection conducted. For the 2014-2016 products, crop and water masking was applied during processing and these areas are not attributed as 254;255: no data value.Note: fire scars may persist and continue to be detected for several months in the image time sequence. The earliest month of detection within the compositing year is recorded.Data sets are 8 Bit GeoTiff with LZW compression and tiling (BigTIFF).<br /> See https://doi.org/10.1016/j.rse.2014.03.021
Process step
- Description
- Algorithm Accuracy: Landsat does not provide a complete record of fire history for this period. This is mostly due to the sensor revisit time of 8-16 days which may be further limited by cloud and cloud shadow obstruction and striping in the imagery. Annual composites from 2003 onwards are affected by data loss due to systematic striping in the Landsat-7 ETM+ imagery. This is due to the failure of the instrument's Scan Line Corrector (SLC). This is increasingly apparent in imagery acquired in the period 2010-2013, prior to the launch of Landsat-8, as image transmission from the Landsat-5 TM (unaffected by striping) was limited and finally ceased in November 2011 due to sensor malfunction. This has resulted in striping and fragmentation in the fire scar maps derived from SLC-Off imagery.
Process step
- Description
- Omissions: In the 1987-2012 automated fire scar products, the average fire scar omission error for the State was measured at 15%. The omission error does not include fire scars missed due to Landsat data loss e.g. SLC-Off striping, or gaps in the Landsat record e.g. due to cloud or revisit time. This has not been quantified due to the lack of a validation data set which is independent from the sensor being used (Landsat). In addition, omission errors are likely to be higher for fire scar composites containing Landsat-7 SLC-Off striping and for wet season periods (Nov-February) in tropical and coastal regions where cloud cover may obscure the view of the surface for months at a time. A fire scar signal may not be evident in the image sequence for long time periods, particularly in savanna regions in North Queensland. Ash/char can be blown or washed away over short periods of time (~weeks) and the fire scar is often rapidly masked by green-flush and vegetation resprouting in subsequent images.
Process step
- Description
- Omissions: Additionally, fires may be captured in the Landsat imagery but missed or under-mapped by the classifier for the following reasons: the fire may be too small or patchy to detect; cool grass/understorey fires may be obscured by the unburnt tree canopy; or the fire may be misclassified as non-fire related change or cloud shadow. An assumption that burnt areas decline in reflectance over time may not always be true and missed fire scars have been noted (e.g. spinifex grasses). The additional step of manual editing applied to the 2013-2016 fire scar data sets should reduce the number of missed fires (due to misclassification) to well below the measured omission rate of 15%, although the edited mapping has not been validated. For 2016, the incorporation of Sentinel 2A into the Landsat image sequence at the manual editing stage has allowed for increased cloud-free ground observations, improved interpretation, and mapping of fire scars which might otherwise be missed in the Landsat sequence.
Process step
- Description
- False Fires: In the 1987-2012 automated fire scar products, the average rate of false fires across Queensland was measured at 30%. This is likely to be less in some regions and more in others. False fires are far more common in image dates affected by SLC-Off striping as the data is fragmented and less reliable. False fires or over-mapping of fire scars may result from the presence of cloud shadows, areas of high land-use change (e.g. cropping), black soils, and inundation e.g. tidal flats, wetlands, ephemeral lakes and channels. These features often spectrally and temporally resemble fire scars. The additional step of manual editing applied to the 2013-2016 fire scar data sets should reduce the number of false fires to well below the measured rate of 30%, although the edited mapping has not been validated.
Reference System Information
- Reference system identifier
- EPSG/EPSG:4326
- Reference system type
- Geodetic Geographic 2D
Metadata
- Metadata identifier
-
urn:uuid/461074b3-5272-4e4e-886f-df26bd2426ad
- Title
- TERN GeoNetwork UUID
- Language
- English
- Character encoding
- UTF8
Point of contact
Type of resource
- Resource scope
- Dataset
- Metadata linkage
-
https://geonetwork.tern.org.au/geonetwork/srv/eng/catalog.search#/metadata/461074b3-5272-4e4e-886f-df26bd2426ad
Point-of-truth metadata URL
- Date info (Creation)
- 2014-10-14T00:00:00
- Date info (Revision)
- 2024-09-23T00:00:00
Metadata standard
- Title
- ISO 19115-1:2014/AMD 1:2018 Geographic information - Metadata - Fundamentals
- Edition
- 1
Metadata standard
- Title
- ISO/TS 19115-3:2016
- Edition
- 1.0
Metadata standard
- Title
- ISO/TS 19157-2:2016
- Edition
- 1.0
- Title
- Terrestrial Ecosystem Research Network (TERN) Metadata Profile of ISO 19115-3:2016 and ISO 19157-2:2016
- Date (published)
- 2021
- Edition
- 1.0
Identifier
Overviews
Spatial extent
N
S
E
W
Provided by
Associated resources
Not available