Brief description
This product provides locations of areas affected by fire including the approximate day of burning. Inputs are daily day time observations from MODIS sensors on Terra and Aqua. Observations are atmospherically corrected and the resulting time series is investigated for sudden changes in reflectance, persistent over multiple days. Variations in observation and illumination geometry are taken into account through application of a kernel driven Bidirectional Reflectance Distribution Function (BRDF) model.Notes
Supplemental InformationPixel value indicates the number of days since reference date 1970-01-01 Datasets are monthly, annual and composited from 2002.
Lineage
The algorithm uses daily MODIS Terra and Aqua day time observations. Observations are atmospherically corrected and the resulting time series is investigated for sudden changes in reflectance, persistent over multiple days. Variations in observation and illumination geometry are taken into account through application of a kernel driven BRDF model.
Notes
CreditWe 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.
The product consists of monthly rasters of the approximate julian day of burning within the month. Seasonality and bioregional effects are taken into account in the analysis of daily reflectance changes in the satellite data (Maier, 2010). The data can be used to estimate both area of burns (contiguous burn pixels) and time of burns (approximate day a pixel burns). Annual and all-data composites of the monthly files are also provided.
Data Quality Assessment Scope
local :
dataset
This product is validated to Stage 2. Product accuracy is estimated over a significant set of locations and time periods by comparison with reference in situ or other suitable reference data. Spatial and temporal consistency of the product and with similar products has been evaluated over representative locations and time periods (Maier, 2010).
Data Quality Assessment Result
local :
Quality Result
Northern Australia: overall accuracy 95.2%, commission error 3.7%, omission error 6.2%. Rainfall events in sparsely vegetated areas cause commission errors. Low intensity, patchy understorey fires under dense canopies are not detected. Small fires affecting a small fraction of a sensor pixel (250 m x 250 m) are not detected.
Created: 2018-09-30
Issued: 2022-02-21
Modified: 2026-03-23
Data time period: 2002-08-01 to 2017-02-28
text: Australia
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- URI : geonetwork.tern.org.au/geonetwork/srv/eng/catalog.search#/metadata/5e262fd7-261f-4c5d-81e7-fff2c6d54d32
- global : 5e262fd7-261f-4c5d-81e7-fff2c6d54d32
