This research leverages satellite data to analyze forest changes during wartime.By employing various analysis methods and web resources, the study provides a detailed assessment of forest impacts. While satellite data offers valuable insights, challenges arise due to the diverse characteristics of different data sources. The study concludes that large-scale deforestation is a pressing issue and that satellite image analysis is crucial for monitoring forest damage.
Dombrovska O., Hoptsii D., Kulbaka O., Siedov A., Surkova V. (2022). Modern capabilities of obtaining remote sensing data as an integral tool for maintaining industry cadastres. International Conference of Young Professionals, GeoTerrace 2022. URL: https://eage.in.ua/wp-content/uploads/2022/09/Geoterrace-2022-063.pdf [in English]
Drebot, O. I., Kasyukhnych, V. Yu., & Vaskiv, T. Ya. (2023). Strategic Directions for Post-War Forest Sector Development in Ukraine. Agro-Ecological Journal, (3), 44-52. https://doi.org/10.33730/2077-4893.3.2023.287762 [in Ukrainian]
Hansen, M. C., Potapov, P. V., Moore, R., Hancher, M., Turubanova, S. A., Tyukavina, A., ... & Townshend, J. R. (2013). High-resolution global maps of 21st-century forest cover change. science, 342(6160), 850-853. [in English]
Koshkalda Iryna, Stupen Nazar, Anopriienko Tetiana, Stupen Oksana (2021). Peculiarities of the forestland taxation system. Studies of Applied Economics Vol 39, No 7: Impact of Current Trends in Social Commerce, Economics, and Business Analytics. https://doi.org/10.25115/eea.v39i7.4824 [in English]
Sentinel-hub. EO-Browser. (2024). URL: https://apps.sentinel-hub.com/eo-browser/
Shaw, T. E., Gascoin, S., Mendoza, P. A., Pellicciotti, F., & McPhee, J. (2020). Snow depth patterns in a high mountain Andean catchment from satellite optical tristereoscopic remote sensing. Water Resources Research, 56(2), e2019WR024880. https://doi.org/10.1029/2019WR024880 [in English]
Soleimani, R., Soleimani-Babakamali, M. H., Meng, S., Avci, O., & Taciroglu, E. (2024). Computer vision tools for early post-disaster assessment: Enhancing generalizability. Engineering Applications of Artificial Intelligence, 136, 108855. https://doi.org/10.1016/j.engappai.2024.108855 [in English]
Sopov D., Kyrpychova I., Matsai N., Cherednychenko I., Sopova N., Vynohradenko S & Sadovyy I. (2024) Use of online GIS tools for the analysis of natural recreation resources. Ecological Sciences, 1 (52), 59-64 https://doi.org/10.32846/2306-9716/2024.eco.1-52.1.8 [in Ukrainian]
Zheng, X., Yuan, Y., & Lu, X. (2019). A deep scene representation for aerial scene classification. IEEE Transactions on Geoscience and Remote Sensing, 57(7), 4799-4809. https://doi.org/10.1109/TGRS.2019.2893115 [in English]