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Study of forest fires according to remote sensing data (on the example of the Chornobyl exclusion zone)

Remote Sensing & GIS for Environmental Monitoring & Exploration

Authors

First and Last Name Academic degree E-mail Affiliation
Anna Sevruk No anna.sevruk.mhd.2020 [at] lpnu.ua Lviv Polytechnic National University
Lviv, Ukraine
Lyubov Babiy No liubov.v.babii [at] lpnu.ua Lviv Polytechnic National University
Lviv, Ukraine
Andriy Babushka Ph.D. andrii.v.babushka [at] lpnu.ua Lviv Polytechnic National University
Lviv, Ukraine
Borys Chetverikov Ph.D. borys.v.chetverikov [at] lpnu.ua Lviv Polytechnic National University
Lviv , Ukraine

I and my co-authors (if any) authorize the use of the Paper in accordance with the Creative Commons CC BY license

First published on this website: 29.08.2021 - 18:45
Abstract 

Remote sensing of the Earth plays an important role in monitoring and assessing the effects of forest fires. With the help of various methods of processing multispectral space images, it is possible to determine the risk of fire spread, identify hot spots and set thermal parameters, map the affected areas and assess the consequences. The aim of the work is to assess the severity associated with the post-fire phase on the example of the forests of the Chornobyl Exclusion Zone. The objectives of the study are to determine the area of burned areas from different time space images obtained from the satellite Sentinel-2 using a normalized burn ratio (NBR). Implemented researches show that the use of remote data of high periodicity and the presence of additional bands of surveying systems significantly expands the range of tasks that can be solved using them. Normalized burned ratio allows quickly and efficiently to identify and calculate the area damaged by fires, that gives possibility operatively assess the consequences of such fires and estimate the damage. It is established that in the studied area the accuracy of area calculation using the normalized burned ratio is 6.7% of the template area, which is sufficient for this type of task.

Keywords 
Sentinel-2
remote sensing data
References 

Burshtynska, Kh., Denys, Yu., Polishchuk, B., Tymchyshyn, M. (2018). Monitoring of forest fires by space images of medium resolution (on the example of Arizona, USA). Modern achievements of geodetic science and industry. No. 1 (35), P.179-184.

Kumar, S.; Roy, D. (2018). Global operational land imager Landsat-8 reflectance-based active fire detection algorithm. International Journal of Digital Earth, Abingdon, Vol. 11, No. 2, P. 154-178.

Pleniou, M., Koutsias, N. (2013). Sensitivity of spectral reflectance values to different burn and vegetation ratios: A multi- scale approach applied in a fire affected area. ISPRS Journal of Photogrammetry and Remote Sensing, Amsterdam, Vol. 79,P. 199-210.

Filipponi, F. (2018). BAIS2: Burned Area Index for Sentinel-2. Proceedings of the 2nd International Electronic Conference on Remote Sensing. Vol. 2, P. 364. https://doi.org/10.3390/ecrs-2-05177.

Quintano, C.; Fernandez-Manso, A.; Fernandez-Manso, O. (2018). Combination of Landsat and Sentinel-2 MSI data for initial  assessing of burn severity. International Journal of Applied Earth Observation and Geoinformation. No. 64, P.221–225.