Early in the morning on February 24, 2022, a full-scale invasion of the Russian Federation into Ukraine began. It involved heavy, brutal shelling and the bombing of the territory of Ukraine.
War has a negative impact on biological diversity and ecosystems as a whole, which is confirmed by dozens of armed conflicts in the countries of Asia, Africa, the Middle East and Europe. Fires in radioactively contaminated areas increase environmental risks not only because of the loss of biodiversity but also through the emission and transfer of radioactive particles with smoke. Therefore, it is necessary to constantly monitor fires, which obviously became impossible due to the military invasion.
The purpose of the study was to identify the possibilities for fire monitoring exclusively by means of Remote Sensing and to estimate the number and area of fires during the occupation of the territory of the Exclusion zone (EZ).
Materials and Methods
Due to the lack of fieldwork and access to the studied territory, we used available means of satellite fire monitoring and satellite survey data. Such sensors as SEVIRI (Spinning Enhanced Visible and InfraRed Imager), AVHRR (Advanced Very High Resolution Radiometer), MODIS (Moderate Resolution Imaging Spectroradiometer) and VIIRS (Visible Infrared Imaging Radiometer Suite) have been used to detect wildfires. Copernicus EFFIS and NASA FIRMS platforms were used to obtain data and to prepare basic layers for the study area, we applied QGIS software.
After the fires had been detected, they were verified using Sentinel-2 and Landsat 8, 9 satellite data. Sentinel-2 and Landsat 8, 9 images in a combination of SWIR–NIR–RED channels were used to determine the contours of each fire, which allowed us to visually identify the burnt areas and to digitize them with GIS tools. The final stage of the fire monitoring was the assessment of their effect using QGIS and databases with the local forest management database (Ukrderzhlisproekt).
The number and area of wildfires which occurred within the Exclusion Zone (EZ) due to hostilities and occupation of the territory (from 24.02.2022 and to 1.04.2022 until the EZ was liberated by the Armed Forces of Ukraine) were estimated. The accuracy of different approaches to landscape fire monitoring by remote sensing methods and relevant services (FIRMS and EFFIS) was assessed. It was found that MODIS sensors can detect 46% of fires, and VIIRS – 69%. On comparing the burnt area in different ways, we assume that the RDA (Rapid Damage Assessment) service from EFFIS captures about 78% of fire areas and is the most accurate means for fire monitoring. However, it is inferior to the combination of manual identification and determination of fire perimeters in connection – MODIS & VIIRS + Sentinel-2 & Landsat 8.9 still has the highest accuracy.
During the occupation, fires were recorded in the area of about 13,989.2 hectares, including 3,489 hectares of forested landscapes.
The study showed that both the average number of wildfires and burnt area increased compared to the same period (from February 24 to April 1 for the period 1994–2021). Thus, the number of fires increased from 7.65 fires to 48 (more than 6 times); the burnt area increased from 26.4 hectares to 13,989.2 hectares (i.e. 529.9 times more!).
4 Figs., 2 Tables, 10 Refs.
Borsuk, O. A. 2019. Comprehensive assessment of the fire hazard of forests in the exclusion zone. PhD thesis. Kyiv, 222 p. (in Ukrainian).
Dudley, J., Ginsberg, J., Plumptre, J., Hart, A., Campos, L. 2002. Effects of war and civil strife on wildlife and wildlife habitats. Conserv. Biol., 16 (2): 319–329.
European Forest Fire Information System EFFIS. 2022. [Electronic resource]. Available at: https://effis.jrc.ec.europa.eu/ (accessed 12.04.2022).
Filizzola, C., Corrado, R., Marchese, F., Mazzeo, G., Paciello, R., Pergola, N., Tramutoli, V. 2017. RST-FIRES, an exportable algorithm for early-fire detection and monitoring: Description, implementation, and field validation in the case of the MSG-SEVIRI sensor. Remote Sens. Environ., 192: e2–e25. https://doi.org/10.1016/j.rse.2017.01.019
FIRMS, FIRMS Global Fire Map. 2022. [Electronic resource]. Available at: http://firms.modaps.eosdis.nasa.gov/firemap/ (accessed 12.04.2022).
Machlis, G. E. and Hanson, T. 2008. Warfare ecology. BioScience, 58: 729–736.
Mazzeo, G., De Santis, F., Falconieri, A., Filizzola, C., Lacava, T., Lanorte, A., Marchese, F., Nol?, G., Pergola, N., Pietrapertosa, C. et al. 2022. Integrated satellite system for fire detection and prioritization. Remote Sens., 14: 335. https://doi.org/10.3390/rs14020335
Mendez, F. and Val?nszki, I. 2021. Environmental armed conflict assessment using satellite imagery. Journal of Environmental Geography, 13: 1–14. https://doi.org/10.2478/jengeo-2020-0007
Wooster, M. J., Roberts, G. J., Giglio, L., Roy, D. P., Freeborn, P. H., Boschetti, L., Justice, C., Ichoku, C., Schroeder, W., Davies, D., et al. 2021. Satellite remote sensing of active fires: History and current status, applications and future requirements. Remote Sens. Environ., 267: 112694. https://doi.org/10.1016/j.rse.2021.112694
Zibtsev S. V., Goldammer J. G., Robinson S., Borsuk O. A. 2015. Fires in nuclear forests: silent threats to the environment and human security. Unasylva, 243/244(66): 40–51.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright (c) 2022 Forestry and Forest Melioration