Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2022, Vol. 19, No. 6, pp. 29-38
Method for automatic detection of burned areas by wildfires using Landsat and Sentinel-2 satellite data
1 Space Research Institute RAS, Moscow, Russia
Accepted: 30.11.2022
DOI: 10.21046/2070-7401-2022-19-6-29-38
This paper describes a method of automatic detection of vegetation damage by natural fires using data with a spatial resolution of 10–30 meters per pixel. The area to be searched for fire damage is selected using information on active burning from MODIS data. The fire-damaged areas are identified in this area by data from Landsat and Sentinel 2 satellites. The method is based on the comparison of changes in the vegetation index in the infrared range after the end of the fire and before its start. The accuracy of the method was evaluated using a manually created benchmark database of forest burned areas for the years 2020 and 2021 (total 1112 burned areas). The average Jaccard distance for all the burned areas in the control database was 0.71. Thus, the developed method is quite suitable for mass automatic detection of vegetation damage by natural fires in case of sufficiently strong damage and sufficient number of cloudless surveys. In the future, the developed method may allow to create an annual map of forest damage by natural fires using data with a spatial resolution of 10–30 meters per pixel.
Keywords: Sentinel 2, Landsat, MODIS, remote sensing, satellite data, forest fires, forest fire monitoring, satellite data processing, burned areas detection
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