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ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2025, V. 22, No. 3, pp. 9-30

Validation of national and global satellite-derived burned area products in Russia

A.M. Matveev 1 , S.A. Bartalev 1 , V.A. Egorov 1 , I.A. Saigin 1 , F.V. Stytsenko 1 , S.S. Shinkarenko 1 
1 Space Research Institute RAS, Moscow, Russia
Accepted: 15.05.2025
DOI: 10.21046/2070-7401-2025-22-3-9-30
The paper presents spatial accuracy assessment of SRBA (Surface Reflectance Burnt Area), a national product developed at Space Research Institute RAS, CGLS Burned Area 300m 3.1 NTC (CGLS BA 3.1), FireCCI51, FireCCIS311, GABAM, MCD64A1 C6, and VNP64A1 C2 global remote sensing burned area products for the territory of Russia. Validation datasets used in this study (with spatial resolution 10–30 m) span over the territory of Russia and cover more than 106 km2 fire-affected area. In forests in the summer period, the considered products show high accuracy, by the F1-score or the Dice coefficient (DC), of fire-affected area mapping (DC of 0.65–0.8), with the highest result for SRBA (DC = 0.83). In the spring period, characterized by smaller area and low lethality of surface fires in Russian forests, the observed accuracy drops significantly (DC of 0.25–0.6, for SRBA DC = 0.4). In grasslands, CGLS BA 3.1, FireCCI51, and FireCCIS311 show the highest accuracy (DC of 0.55–0.7), while SRBA has the lowest result (DC = 0.33). All satellite-derived products show low accuracy in cropland burning mapping (DC < 0.3). Overall accuracy assessment shows a moderate result for SRBA (DC = 0.5) with higher accuracy for FireCCI51 and FireCCIS311 products (DC ≈ 0.6). GABAM, MCD64A1 C6, and VNP64A1 C2 omit c. 60–70 % fire-affected area. Most reviewed products tend to underestimate burned area by 20–50 %, with the exception of CGLS BA 3.1 due to its high commission error for summer-autumn forest fires.
Keywords: remote sensing, burned area, burned area accuracy assessment, validation
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