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

• Main Authors: E. Alonso-González, V. Fernández-García
• Format: Article
• Language: English
• Published: Copernicus Publications 2021-05-01
• Series: Earth System Science Data
• Online Access: https://essd.copernicus.org/articles/13/1925/2021/essd-13-1925-2021.pdf

<p>To make advances in the fire discipline, as well as in the study of CO<span class="inline-formula">₂</span> 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 km<span class="inline-formula">²</span> (<span class="inline-formula"><i>n</i>=32 163</span>). Results showed that MOSEV and Landsat-8 burn severity indices are highly correlated, particularly the post-burn NBR (<span class="inline-formula"><i>R</i>=0.88</span>; <span class="inline-formula"><i>P</i><i>&lt;</i>0.001</span>), and dNBR (<span class="inline-formula"><i>R</i>=0.74</span>; <span class="inline-formula"><i>P</i><i>&lt;</i>0.001</span>) showed stronger relationships than RdNBR (<span class="inline-formula"><i>R</i>=0.42</span>; <span class="inline-formula"><i>P</i><i>&lt;</i>0.001</span>). 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 d; Landsat: 16 d). The database is structured according to the MODIS tiling system and is freely downloadable at <a href="https://doi.org/10.5281/zenodo.4265209">https://doi.org/10.5281/zenodo.4265209</a> (Alonso-González and Fernández-García, 2020).</p>