Circumpolar boreal forest burnt area - George, C.; Gerard, F.; Balzter, H. (NERC Environmental Information Data Centre, 2010)
Burnt areas are presented with a daily date of burn at 500m resolution for the circumpolar boreal forest zone. The dataset comprises eleven tiff files, one for each year: 2001 to 2011.
The aim of this dataset is the improved understanding of spatio-temporal patterns and dynamics of boreal fire intensity and extent, the driving factors behind these variations, and the consequence for carbon fluxes for the whole boreal area.
The source data for the daily burnt area product is the 16-day MODIS Nadir BRDF-Adjusted Reflectance (N-BAR) MCD43A4 product on the standard Sinusoidal projection. The burnt areas are identified by thresholding a differencing method, with the resulting fire-scars dated using MODIS thermal anomalies (MOD14A1). The results are annual TIFF images at 500m resolution with the pixel values being the first day of burn for that year. The product was validated using temporal assemblages of ETM images randomly located throughout the whole Boreal zone and analysed on a date and per pixel basis. The result was a Kappa co-efficient of 0.54. This algorithms used to map the burnt areas were developed by members of the CEH Wallingford Earth Observation group.
The source data for the daily burnt area product is the 16-day MODIS Nadir BRDF-Adjusted Reflectance (N-BAR) MCD43A4 product on the standard Sinusoidal projection. The burnt areas are identified by thresholding a differencing method, with the resulting fire-scars dated using MODIS thermal anomalies (MOD14A1). The results are annual TIFF images at 500m resolution with the pixel values being the first day of burn for that year. The product was validated using temporal assemblages of ETM images randomly located throughout the whole Boreal zone and analysed on a date and per pixel basis. The result was a Kappa co-efficient of 0.54.
Keywords: Russia; Siberia; Canada; Alaska; Land cover; Climate and climate change; Natural resource management; earth observation; forest; fire; remote sensing; climate change