Geoinformation wildfire mapping of Ukraine: analyzing FIRMS data for effective fire management
DOI: https://doi.org/10.3846/gac.2025.21322Abstract
Sustainable growth in Earth remote sensing data necessitates the advancement of interpretation methods to address a wide array of economic challenges. This research paper proposes the development of a methodology to automate the assessment of fire-affected areas using GIS software such as ArcGIS and QGIS. Data on fire localization from NASA/NOAA Suomi NPP and NOAA-20 and MODIS (M6) satellites, sourced from NASA’s Fire Information for Resource Management System (FIRMS), as well as annual land use/land cover data from ESA WorldCover 2021, are utilized for this study. The series of maps obtained from the aggregation and generalization of fire distribution data for individual years across the administrative regions of Ukraine from 2021 to 2023 allows for the assessment of fire density, their correlation with different land cover types, and spatio-temporal changes. Graphs showing the distribution of fires based on land cover types in Ukraine for 2021–2023 have been generated. Additionally, the dynamics of fire occurrences in 2023 compared to 2022 are presented.
Keywords:
land use, land cover (global land cover), maps, mapping, fires, remote sensing, algorithm, data aggregation, automation, GISHow to Cite
Share
License
Copyright (c) 2025 The Author(s). Published by Vilnius Gediminas Technical University.
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Balabukh, V. O., & Zibtsev, S. V. (2016). Impact of climate change on quantity and area of forest fires in the northern part of the Black Sea Region of Ukraine. Ukrainian Hydrometeorological Journal, (18), 60–71. https://doi.org/10.31481/uhmj.18.2016.07
Çolak, E., & Sunar, F. (2020). The importance of ground-truth and crowdsourcing data for the statistical and spatial analyses of the NASA FIRMS active fires in the Mediterranean Turkish forests. Remote Sensing Applications: Society and Environment, 19, Article 100327. https://doi.org/10.1016/j.rsase.2020.100327
Drozdova, Y., Harasym, A., Bondarenko, A., & Kelm, N., (2021). In Ukraine, there are about 20,000 fires on arable land yearly. https://texty.org.ua/projects/105282/ukraine-there-are-about-20000-fires-arable-land-yearly/
Eugenio, F. C., dos Santos, A. R., Fiedler, N. C., Ribeiro, G. A., da Silva, A. G., dos Santos, Á. B., Paneto, G. G., & Schettino, V. R. (2016). Applying GIS to develop a model for forest fire risk: A case study in Espírito Santo, Brazil. Journal of Environmental Management, 173, 65–71. https://doi.org/10.1016/j.jenvman.2016.02.021
Garzón, F. A. M., & Valánszki, I. (2020). Environmental armed conflict assessment using satellite imagery. Journal of Environmental Geography, 13(3–4) 1–14. https://doi.org/10.2478/jengeo-2020-0007
Giglio, L., Csiszar, I., & Justice, C. O. (2006). Global distribution and seasonality of active fires as observed with the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. Journal of Geophysical Research, 111, Article G02016. https://doi.org/10.1029/2005JG000142
Giglio, L., Schroeder, W., & Justice, C. O. (2016). The collection 6 MODIS active fire detection algorithm and fire products. Remote Sensing of Environment, 178, 31–41. https://doi.org/10.1016/j.rse.2016.02.054
Humanitarian Data Exchange. (2021). Ukraine – subnational administrative boundaries. https://data.humdata.org/dataset/cod-ab-ukr
Jain, P., Castellanos-Acuna, D., Coogan, S. C., Abatzoglou, J. T., & Flannigan, M. D. (2022). Observed increases in extreme fire weather driven by atmospheric humidity and temperature. Nature Climate Change, 12(1), 63–70. https://doi.org/10.1038/s41558-021-01224-1
Kelm, N. (2023). There have been many times less fires in the fields in Ukraine. https://texty.org.ua/fragments/109429/v-ukrayini-stalo-v-razy-menshe-pozhezh-na-polyah/
Matsala, M., Odruzhenko, A., Hinchuk, T., Drobyshev, I., Sydorenko, S., Zibtsev, S., Milakovsky, B., Schepaschenko, D., Kraxner, F., & Bilous, A. (2024). War drives forest fire risks and highlights the need for more ecologically-sound forest management in post-war Ukraine. Scientific Reports, 14, Article 4131. https://doi.org/10.1038/s41598-024-54811-5
Ordway, E. M. (2015). Political shifts and changing forests: Effects of armed conflict on forest conservation in Rwanda. Global Ecology and Conservation, 3, 448–460. https://doi.org/10.1016/j.gecco.2015.01.013
Oreshchenko, A. (2022, November 15–18). Monitoring of wildfires caused by hostilities using satellite thermal sensors. In XVI International Scientific Conference “Monitoring of Geological Processes and Ecological Condition of the Environment” (Vol. 2022, pp. 1–5), Kyiv, Ukraine. https://doi.org/10.3997/2214-4609.2022580171
Osadchyi, V. I., Oreshchenko, A. V., & Savenets, M. V. (2023). Satellite monitoring of fires and air pollution. Ukrainian Hydrometeorological Institute. https://doi.org/10.15407/uhmi.2023_1
Pausas, J. G., & Keeley, J. E. (2021). Wildfires and global change. Frontiers in Ecology and the Environment, 19(7), 387–395. https://doi.org/10.1002/fee.2359
Sevruk, A., Babiy, L., Babushka, A., & Chetverikov, B. (2021, October). Study of forest fires according to remote sensing data (on the example of the Chornobyl exclusion zone). In International Conference of Young Professionals “GeoTerrace-2021” (Vol. 2021, pp. 1–5). European Association of Geoscientists & Engineers. https://doi.org/10.3997/2214-4609.20215K3010
Shevchuk, S. A., Vyshnevskyi, V. I., & Bilous, O. P. (2022). The use of remote sensing data for investigation of environmental consequences of Russia-Ukraine war. Journal of Landscape Ecology, 15(3), 36–53. https://doi.org/10.2478/jlecol-2022-0017
Tian, X., Zhao, F., Shu, L., & Wang, M. (2013). Distribution characteristics and the influence factors of forest fires in China. Forest Ecology and Management, 310, 460–467. https://doi.org/10.1016/j.foreco.2013.08.025
Tomchenko, O. V., Khyzhniak, A. V., Sheviakina, N. A., Zagorodnia, S. A., Yelistratova, L. A., Yakovenko, M. I., & Stakhiv, I. R. (2023). Assessment and monitoring of fires caused by the War in Ukraine on Landscape scale. Journal of Landscape Ecology, 16(2), 76–97. https://doi.org/10.2478/jlecol-2023-0011
Toreti, A., Bavera, D., Acosta Navarro, J., Cammalleri, C., de Jager, A., Di Ciollo, C., Hrast Essenfelder, A., Maetens, W., Magni, D., Masante, D., Mazzeschi, M., Niemeyer, S., & Spinoni, J. (2023). Drought in Europe August 2023. Publications Office of the European Union.
Witmer, F. D. W. (2015). Remote sensing of violent conflict: Eyes from above. International Journal of Remote Sensing, 36(9), 2326–2352. https://doi.org/10.1080/01431161.2015.1035412
Yakovenko, M., Tomchenko, O., Stakhiv, I., & Liashenko, D. (2023, October 4–6). Assessment of the quality loss, damage of forestry lands affected by military operations in 2021–2023. In International Conference of Young Professionals “GeoTerrace-2023” (Vol. 2023, pp. 1–5). European Association of Geoscientists & Engineers. https://doi.org/10.3997/2214-4609.2023510041
View article in other formats
CrossMark check
Published
Issue
Section
Copyright
Copyright (c) 2025 The Author(s). Published by Vilnius Gediminas Technical University.
License
This work is licensed under a Creative Commons Attribution 4.0 International License.