Publications

Garcia-Lazaro, JR; Moreno-Ruiz, JA; Riano, D; Arbelo, M (2018). Estimation of Burned Area in the Northeastern Siberian Boreal Forest from a Long-Term Data Record (LTDR) 1982-2015 Time Series. REMOTE SENSING, 10(6), 940.

Abstract
A Bayesian classifier mapped the Burned Area (BA) in the Northeastern Siberian boreal forest (70 degrees N 120 degrees E-60 degrees N 170 degrees E) from 1982 to 2015. The algorithm selected the 0.05 degrees (similar to 5 km) Long-Term Data Record (LTDR) version 3 and 4 data sets to generate 10-day BA composites. Landsat-TM scenes of the entire study site in 2002, 2010, and 2011 assessed the spatial accuracy of this LTDR-BA product, in comparison to Moderate-Resolution Imaging Spectroradiometer (MODIS) MCD45A1 and MCD64A1 BA products. The LTDR-BA algorithm proves a reliable source to quantify BA in this part of Siberia, where comprehensive BA remote sensing products since the 1980s are lacking. Once grouped by year and decade, this study explored the trends in fire activity. The LTDR-BA estimates contained a high interannual variability with a maximum of 2.42 million ha in 2002, an average of 0.78 million ha/year, and a standard deviation of 0.61 million ha. Going from 6.36 in the 1980s to 10.21 million ha BA in the 2010s, there was a positive linear BA trend of approximately 1.28 million ha/decade during these last four decades in the Northeastern Siberian boreal forest.

DOI:
10.3390/rs10060940

ISSN:
2072-4292