MOSEV: a global burn severity database from MODIS (2000–2020)

To make advances in the fire discipline, as well as in the study of CO2 emissions, it is of great interest to develop a global database with estimators of the degree of biomass consumed by fire, which is defined as burn severity. In this work we present the first global burn severity database (MOSEV...

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Bibliographic Details
Published in:Earth system science data 2021-05, Vol.13 (5), p.1925-1938
Main Authors: Alonso-González, Esteban, Fernández-García, Víctor
Format: Article
Language:English
Subjects:
Biomass
Biomass burning
Burning
Coefficients
Correlation coefficient
Correlation coefficients
Earth resources technology satellites
Ecosystems
Fires
Landsat
Landsat satellites
Mathematical analysis
MODIS
Reflectance
Remote sensing
Resolution
Satellites
Spectroradiometers
Temporal resolution
Tiling
Time series
Trends
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Summary:To make advances in the fire discipline, as well as in the study of CO2 emissions, it is of great interest to develop a global database with estimators of the degree of biomass consumed by fire, which is defined as burn severity. In this work we present the first global burn severity database (MOSEV database), which is based on Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance and burned area (BA) products from November 2000 to near real time. To build the database we combined Terra MOD09A1 and Aqua MYD09A1 surface reflectance products to obtain dense time series of the normalized burn ratio (NBR) spectral index, and we used the MCD64A1 product to identify BA and the date of burning. Then, we calculated for each burned pixel the difference of the NBR (dNBR) and its relativized version (RdNBR), as well as the post-burn NBR, which are the most commonly used burn severity spectral indices. The database also includes the pre-burn NBR used for calculations, the date of the pre- and post-burn NBR, and the date of burning. Moreover, in this work we have compared the burn severity metrics included in MOSEV (dNBR, RdNBR and post-burn NBR) with the same ones obtained from Landsat-8 scenes which have an original resolution of 30 m. We calculated the Pearson's correlation coefficients and the significance of the relationships using 13 pairs of Landsat scenes randomly distributed across the globe, with a total BA of 6904 km2 (n=32 163). Results showed that MOSEV and Landsat-8 burn severity indices are highly correlated, particularly the post-burn NBR (R=0.88; P
ISSN:1866-3516
1866-3508
1866-3516
DOI:10.5194/essd-13-1925-2021