Abstract
Abstract. Quantitative information on the error properties of global satellite-derived burned area (BA) products is essential for evaluating the quality of these products, e.g. against modelled BA estimates. We estimate theoretical uncertainties for three widely used global satellite-derived BA products using a multiplicative triple collocation error model. The approach provides spatially unique uncertainties at 1∘ for the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 burned area product (MCD64), the MODIS Collection 5.1 (MCD45) product, and the European Space Agency (ESA) Climate Change Initiative Fire product version 5.0 (FireCCI50) for 2001–2013. The uncertainties on mean global burned area for three products are 3.76±0.15×106 km2 for MCD64, 3.70±0.17×106 km2 for FireCCI50, and 3.31±0.18×106 km2 for MCD45. These correspond to relative uncertainties of 4 %–5.5 % and also indicate previous uncertainty estimates to be underestimated. Relative uncertainties are 8 %–10 % in Africa and Australia, for example, and larger in regions with less annual burned area. The method provides uncertainties that are likely to be more consistent with modelling and data analysis studies due to their spatially explicit properties. These properties are also intended to allow spatially explicit validation of current burned area products.
Highlights
Several global satellite-derived burned area (BA) products have been generated for the past two decades
Given that we may expect the performance of each product to vary with the local fire behaviour, we considered the uncertainty estimates with regard to the International GeosphereBiosphere Programme (IGBP) land cover type classification provided in the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 land cover product (MCD12Q1.006) (Friedl et al, 2010)
We find that the reported uncertainties are considerably smaller than those provided by the triple collocation (TC) error model as well as the uncertainty estimates provided by GFED4
Summary
Several global satellite-derived burned area (BA) products have been generated for the past two decades. These products, generated from coarse spatial resolution (250–1000 m) satellite imagery, have provided vital information to firerelated disciplines (Mouillot et al, 2014) They have provided new information on global pyrogeography and changes in fire occurrence (Archibald et al, 2013; Andela et al, 2017), been used to calibrate and validate fire models within dynamic global vegetation models (DGVMs) (Thonicke et al, 2001; Hantson et al, 2016), as well as to drive “bottomup” estimates of fire emissions (Seiler and Crutzen, 2008; van der Werf et al, 2017). Large differences between product estimates have been highlighted in tropical regions, boreal Eurasia, and sub-Saharan Africa (Giglio et al, 2010; Humber et al, 2018) These divergences have been interpreted to be driven by differences in the observing properties of the satellites used to create products, as well as the mapping algorithms used within each product. A key determinant on the accuracy of burned area de-
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