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https://doi.org/10.5194/essd-2020-341
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-2020-341
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  19 Nov 2020

19 Nov 2020

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This preprint is currently under review for the journal ESSD.

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

Esteban Alonso-González1 and Víctor Fernández-García2 Esteban Alonso-González and Víctor Fernández-García
  • 1Instituto Pirenaico de Ecología, Spanish Research Council (IPE-CSIC), Zaragoza, 50059, Spain
  • 2Ecology, Department of Biodiversity and Environmental Management, University of León, León, 20971, Spain

Abstract. To advance 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 since 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 6,904 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 < 0.001). dNBR (R = 0.74; P < 0.001) showed stronger relationships than RdNBR (R = 0.42; P < 0.001). Differences between MOSEV and Landsat-8 indices are attributable to variability in reflectance values and to the different temporal resolution of both satellites (MODIS: 1–2 days, Landsat-: 16 days). The database is structured according to the MODIS tiling system and is freely downloadable in https://doi.org/10.5281/zenodo.4265209 (Alonso-González and Fernández-García, 2020).

Esteban Alonso-González and Víctor Fernández-García

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Esteban Alonso-González and Víctor Fernández-García

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MOSEV: a global burn severity database from MODIS (2000-2020) Esteban Alonso-González and Víctor Fernández-García https://doi.org/10.5281/zenodo.4265209

Esteban Alonso-González and Víctor Fernández-García

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Short summary
We present the first global burn severity database (MOSEV database), which is based on Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance and burned area products. The database inludes monthly scenes with the dNBR, RdNBR and post-burn NBR spectral indices at 500 m spatial resolution since November 2000. Moreover, in this work we show that there is a close relationship between the burn severity metrics included in MOSEV and the same ones obtained from Landsat-8.
We present the first global burn severity database (MOSEV database), which is based on Moderate...
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